The 2016 Digital Marketer: Your guide to using data and technology to better engage your customers

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Customers won’t stand for mediocre experiences. When they have a brand experience that leaves them less than satisfied, they don’t just ignore it and hope the brand understands them better next time. They share that experience with social networks and challenge the brand to make things right.

You’d likely be hard-pressed to find a marketer today who does not recognise the significance of knowing his or her customer. Yet this is a top challenge for marketers around the globe, regardless of company size or industry.

Download this guide to learn what today's marketers' biggest challenges and priorities are, and how you can gain a single customer view and provide better customer experiences.

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Survey methodology and demographics

The 2016 Digital Marketer Survey was conducted from Nov. 3-23, 2015. Responses were collected from 1,190 professionals around the globe who have spending or purchasing influence or authority in marketing/ advertising. Respondents included marketers from not only the UK but also the US, Australia, France, Spain, Germany, Brazil, China, India, Indonesia, Japan, New Zealand and Singapore.

An independent research firm researched and targeted the universe of companies and individuals within those companies who would likely qualify for the survey, and then conducted the appropriate outreach online to those individuals specifically. Analytics were in place to determine which individuals responded, or hadn’t. Incentives were then distributed to the business professionals who qualified and completed the interview.

Marketers Struggle To Truly Know Their Customers’ Needs, Wants And Attitudes

In a world that is increasingly connected, customers expect real and authentic interactions with brands. To meet these demands, customer-centric brands are shifting the way they think about “customers” or “consumers” to start thinking of them as people; people who have real lives, relationships and desires rather than just views, clicks or transactions on the other side of a screen.

Brands that can deliver on these customer expectations know the people who buy and use their products at a deeper, more intimate level. This knowledge goes beyond standard demographics like gender, age or income to include their needs, wants and attitudes. How do these people spend their time? How do they engage with your brand and with other brands? How do they behave as individuals; not just members of a specific demographic?

The needs and attitudes of these individuals in the example to the right are likely very different. A message that resonates with one of the sisters may be completely lost on the other. Without full knowledge of their differences, marketers will speak to them in the same way, which risks making each interaction their last.

Although most marketers would agree that it’s better to have a clear understanding of the individuals they’re seeking to engage, this is one of the main challenges marketers at every level struggle with, regardless of company size or industry.

38%of marketers rank knowing their customers’ needs, wants and attitudes among the top three challenges they face.

The second-largest challenge for marketers is to increase brand visibility over their competitors. As company size increases, this is less likely to be a top challenge, as 12 percent of midmarket marketers and only nine percent of those at enterprise-level companies ranked this as their top challenge.

Interestingly, midmarket marketers are most likely to rank integrating technologies their number one challenge. Fourteen percent ranked this as their biggest challenge compared to just eight percent in enterprise-level companies and seven percent at firms with less than $25M in annual revenue.

Enterprise-level firms, however, are more likely to be running crosschannel campaigns and have data coming into disparate systems from a wide variety of sources. So why might integrating multiple marketing technologies rank lower in their list of challenges? It could be because they already have a plan in place to tackle the issue. As you will soon see, integrating technologies was rated the highest priority among enterpriselevel marketers for the next year.

Where marketers in enterprise companies report greater challenges is with:

  • Making messages contextually relevant - 33%
  • Making analytics actionable - 32%
  • Overcoming internal silos - 30%

Marketers in enterprise-level companies can leap over these hurdles by investing in a single technology platform that can perform the functions of the multiple technology systems marketers are dealing with today. Rather than having one point solution for data management, multiple systems for each channel’s execution, another tool for measurement and so on, a single sign-on platform enables marketers to reduce waste, get to the insights faster and engage customers with tremendous precision.

Enterprise Marketers Prioritise Technology To Better Understand Customers

In last year’s Digital Marketer Report, we found that the priorities of senior leaders didn’t align with their top challenges. Fortunately, that is not the case in 2016.

Recognising that the old way of doing business is no longer an option, this year, marketers answered the call of consumers – to refocus priorities and centre business and marketing strategies around the individual.

Overall, a little more than half (52 percent) of marketers named enhancing their knowledge of the customer one of their top three priorities for 2016. If this is your top priority, how do you get there? The answer is technology and data, which are positioned as the second (43 percent) and third (42 percent) top priorities for the year ahead.

A technology solution that can perform data management, advanced analytics and real-time interaction operations all within a single platform can enable enterprise organisations to achieve their highest priorities.

Marketers in enterprise-level organisations ranked cross-channel automation technology ahead of enhancing knowledge of consumers, likely understanding that it’s the means to that end. Integrating technology to automate, orchestrate and manage cross-channel customer interactions was the number one priority for 19 percent of enterprise marketers, and 53 percent ranked it among their top three priorities.

For C-level executives of enterprise companies, technology initiatives are an even greater priority. Integrating technology stays in the number one position, while advanced analytics investments are nearly tied for second. These marketers realise the impact poor customer experiences will have on their brand and they’re planning to use technology and resulting analytics to prevail.

Do you have what it takes to surprise and delight your customers with every interaction?

Ashley Johnston, Senior Vice President, Global Marketing Experian Marketing Services

The future of marketing is driven by sophisticated, hyperconnected, omnichannel consumers who expect exceptional experiences every time. Given that very little is proprietary anymore and consumers can purchase their favourite products from multiple vendors, brands have to work that much harder to win customer loyalty, purchase-by-purchase and engagementby-engagement. To stand out, today’s marketers must take a deep dive into their customers’ individual preferences and purchase paths to customise the experience around their unique and evolving needs.

I am a firm believer that you’re only as good as your last interaction, so it’s incredibly important to always get it right. If you don’t give your customer an exceptional experience, there are hundreds of other companies that will. And consumers will continue to change: new purchase channels will emerge, existing customers will have new needs and life moments that will change their preferences and behaviours, and new generations of consumers will emerge introducing new trends and opportunities for engagements.

So, do you have what it takes to surprise and delight your customers with every interaction?

To keep up – and stay one step ahead – we need to adapt to this reality and build our businesses to support the customer experience.

This starts with asking fundamental questions like

  1. Do we have confidence in how we define our best customer?
  2. Do we have a centralised database where we can analyse behaviour from every channel?
  3. Are our incentive structures and organisational silos dictating the customer’s experience or are they forced to conform to channel-specific P&L structures?
  4. How easily can the customer navigate and interact with our brand regardless of channel?

As technology has progressed and new channels have emerged, many marketing organisations have built teams around these channels. This system no longer works. Instead, it’s time to build around experiences. For brands trying to adapt, this is a fundamental shift. Organisational structures need to be channel-agnostic so the customer receives the same exceptional experience regardless of how they interact with your brand.

Conflicting business priorities and department goals can lead to poor customer experiences and loss in revenue for the business. Data from all channels needs to be consolidated for analysis and action. If you’re still doing attribution per channel, you need to structure and incentivise your teams to work together. If you have channel conflict, pricing discrepancies or conflicting sales models, you need to make it a priority to fix them. Having separate profit and loss statements (P&Ls) and objectives designed around each channel only creates missed opportunities and huge gaps in the customer experience.

Organisations who truly value exceptional customer experiences should review structures and merge their channel-based teams into one intelligent system designed to serve the customer. Those who do will be the ones who win customer loyalty.

All of this change can be intimidating, but it’s also exciting. We have everything we need to surprise and delight the customer with every single interaction. The data, technology and tools exist to help you create and deliver those experiences. Change is only coming faster and the customer is our guiding light; they must always be in our line of sight.

The Move From Channel-centric To Customer-centric Organisations

As we saw in our discussion of the challenges facing marketers, 23 percent of respondents ranked “overcoming internal silos to centre our programmes on the customer” as one of the top three challenges they face. When we take a closer look, we see this challenge increase along with company size.

30%of marketers in enterprise-level companies rank organisational structure among their top three challenges.

They are 31 percent more likely to do so than the overall survey population. This makes sense, as bigger companies are more likely to have larger, more separated teams, which can inhibit marketing efficiency on many levels – most notably the ability to deliver consistent customer experiences across a variety of channels.

Fortunately, while organisational silos are a larger challenge for larger companies, overcoming these silos is also a greater priority.

Enterprise level marketers were 54 percent more likely to name facilitating alignment their top priority, compared to the overall survey population.

Breaking down these silos is a challenge that must be overcome from the top-down. This must be a priority of C-level executives in order for change to happen within their organisation. Our data shows that enterprise-level leadership recognises this and plans to attack this in the year ahead.

42%of C-level executives at enterprise-level companies rank overcoming internal silos as a top priority.

Organisational restructuring at the enterprise level is a massive undertaking, however. The commitment can be risky and some Chief Marketing Officers may not be able to convince their peers of the rewards resulting from this endeavor.

However, while organisational silos are an intra-departmental challenge, they are also interdepartmental, at least when it comes to marketing teams. Overall, 70 percent of survey respondents work in marketing teams that are either fully or somewhat integrated. This is up from 61 percent last year.

Just as overall organisational silos are more of a challenge for larger companies, silos within marketing teams are more prevalent as company size increases. That means different teams control the customer experience for each channel; one marketer covers email, one covers mobile, another covers social and so on.

59% of the enterprise-level marketers in our survey work in marketing teams that are broken out by channel.

It is no wonder that knowing customers’ wants, needs, attitudes and behaviours is a top challenge when marketing teams are not integrated and are challenged to share the insights they learn in one channel with the teams in other channels. What results is a disjointed customer experience – the opposite of the seamless experience today’s customers require. They want to see a consistent brand across each channel in which they engage.

So, even if your organisation can’t undertake a massive restructure, you still have the ability to affect change and deliver better customer experiences by realigning your marketing department from one that is channel-focused to one that revolves around your customer.

The right technology and data can act as a driver of change within your team and organisation.

It can help you on the path to customer centricity by breaking down data silos. Invest in the technology that can make sure data is accessible and actionable across groups.

Structural differences by industry and region

By analysing the data across industries, we see that automotive, retail and ecommerce, and pharmaceuticals and healthcare are most likely to have marketing teams that are somewhat or fully integrated. Financial services is most likely to be broken out by channel (44 percent). While agency and marketing services organisations are near average in percentage of siloed teams, they are also most likely to have full team integration.

Marketers in North and South America are most likely to work in teams that are at least somewhat integrated, at 80 percent and 72 percent, respectively. South American marketing departments are most likely to be fully integrated (42 percent). This can be attributed to teams in that region generally being smaller in size. Marketing departments in Europe, the Middle East and Africa (EMEA) have the furthest way to go toward full integration, as less than one-quarter are integrated today.

Marketing’s Shift From Pure Promotion To Customer Experience

Another organisational change is occurring in marketing departments – the addition of responsibilities. Marketing organisations around the globe are taking on more ownership of the customer experience, shifting responsibilities beyond promotional messaging to include other business functions. This is already happening.

According to our survey, marketers are already responsible for these operational functions:

  • Collecting reviews and customer feedback (69 percent)
  • Customer service responses on social media (67 percent)
  • Operational emails, i.e., order confirmation, shipping alert (67 percent)
  • Integrating the customer experience across channels, i.e., ensuring order history or shopping cart experiences stay the same in app or via website (60 percent)
  • Operational mobile messages, i.e., mobile boarding passes, shipping and delivery notifications (56 percent)
  • Loyalty programme (56 percent)
  • Call centre (52 percent)

Across the board, marketing’s role in each of these is expected grow at least 20 percent – in some as much as 28 percent – within the year. We see the largest growth happening in midmarket companies, where increases range from 22 percent to 33 percent.

Integrating the customer experience is poised for the largest growth across all company sizes. More than three in four enterprise-level marketing organisations are already responsible for this function and 18 percent more expect to be within the year

That means, by 2017, 95 percent of enterprise-level marketing teams will be responsible for ensuring their organisation’s data is aligned and actionable, and that they have the technology to effectively execute a seamless customer experience regardless of channel.

There are not as many midmarket marketing organisations currently responsible for integrating the customer experience across channels (58 percent). However, one-third plan to be taking on this responsibility in 2016, such that by the end of the year, 91 percent will manage this duty, nearly catching up to enterprise-level companies.

Operational mobile messages and loyalty programmes tie for the second-highest growth potential (26 percent). The fact is, the addition of any cross-channel, cross-functional messages requires the ability to link customer information so you have a clear picture of your customer regardless of channel. If yours is one of the marketing departments undertaking these operational tasks in 2016, you need to arm yourself with powerful data and technology tools. It’s no easy feat to accomplish on your own – especially under the pressure of customer expectations and market competition.

The Chief Data Officer is a marketer’s new best friend

Courtney Cunnane, Vice President of Marketing, Experian Data Quality

Marketers have long sought to gain as much information as possible about the consumer. The more we know, the more likely it is that we’ll be able to increase conversion and customer loyalty. However, data is not always easy for a marketer to access or manipulate, making insight difficult.

This is especially true when we consider the state of data management today. Most organisations suffer from a high degree of inaccurate data and segmented data sources. Most data management occurs within individual departments, many of which lack the technology and human resources to manipulate data for insight. It should come as no surprise that 83 percent of businesses believe data is a valuable organisational asset that is not being fully exploited, according to a recent Experian Data Quality study.

Marketers have certainly begun utilising more sophisticated technology practices and analytical staff in the past few years, but they have only begun to scratch the surface of the insights that data can provide.

However, a new trend is emerging within many larger organisations that could improve a marketer’s ability to mine data for insight: the advent of the Chief Data Officer (CDO), a new role that is seen as a trusted advisor and guardian of data within the business. In the organisations we work with frequently, the key reasons for needing a CDO are to manage risk during data-driven projects, curb increasing costs around poor data quality and assist with an increasingly regulatory environment.

This new individual isn’t alone. The CDO comes with a team of data specialists that often includes data analysts, data scientists and data warehouse specialists. The CDO often reports into the Chief Information Officer or Chief Executive Officer.

While this role is only seen today in a small number of businesses, adoption of this role is accelerating quickly. Gartner predicts that 50 percent of all companies in regulated industries will have a CDO by 2017, according to research conducted by Debra Logan, Vice President and Gartner Fellow.

Several years ago, the Chief Marketing Officer (CMO) had to adjust to working with the Chief Technology Officer when adding a host of new technologies. The CMO now needs to work with the CDO to gain better access to information and insight around data. This individual can help provide the marketer with easy access to data that is prepared for given marketing tasks. With all of the struggles marketers have had finding quality, accessible data over the years, the advent of the CDO could bring about a new chapter in data intelligence.

Data Quality Reduces Waste

Whether your organisation or marketing department is aligned or siloed, you need a single understanding of each customer if you hope to deliver intelligent interactions, every time.

84% of organisations see data as an integral part of forming a business strategy.

As the saying goes, however, “garbage in, garbage out.” Smart organisations make data-driven strategic decisions, but what happens if those decisions are based on poor quality data? Customers will not only have poor experiences with the brand, but waste from inappropriate business decisions could put the company out of business altogether.

Seventy-six percent of respondents in the Experian Data Quality study believe inaccurate data is undermining their ability to provide an excellent customer experience. Human error remains the leading source of inaccurate data. However, technology issues – either inaccuracies in current technology or a lack of the relevant technology – have increased year-over-year (YOY).

In total, the study found that 94 percent of companies have experienced internal challenges in improving their data quality. Most of these challenges are people-related. It is wise to fix these issues, as improved data quality brings tangible commercial benefits.

On average, these organisations believe they could increase overall sales by 29 percent if all their data was fully accurate and to the highest quality.

A Complete Customer View, Your Ultimate Goal

Media fragmentation presents a host of new opportunities for brands, but it also means that customers have an increasingly complicated path toward purchase. According to ABI research it’s going to get even more complex; they predict that by 2020 there will be 40 billion connected devices in the world. That’s a 167 percent increase in just five years. Finding that single customer view is more critical than ever before. And you can’t wait to get started – the mountain of data is only getting harder to scale. Reports show marketers are eagerly starting their ascent.

According to the Experian Data Quality study, 97% of organisations are looking to achieve a complete view of the customer.

The most common reason is to increase customer retention and loyalty, followed by the desire to increase revenue. Forty-two percent want to improve their strategic decision-making, placing it as the third mostpopular reason for achieving a complete customer view. Almost all organisations seek a complete customer view, but attaining it means overcoming many hurdles. In the 2016 Digital Marketer survey, 81 percent of marketers reported having challenges achieving a single customer view.

This is down from 89 percent in 2015, which shows marketers are on the right trajectory but they still have an uphill climb ahead of them.

Accurate data means actionable insights

Spencer Kollas, Vice President, Global Deliverability Experian Marketing Services

Incorrect data, especially an invalid or incorrect email address for a customer, has huge potential for lost revenue. For many organisations, email is the hub of the marketing strategy. An email address is the key data point that connects a customer’s activities across multiple channels and devices.

Without an accurate email address, your chances of linking your customers’ cross-channel behaviours are vastly slimmer, leaving you in the dark about both their behaviours and their preferences. That’s why it’s so important that organisations collect the right email address as early as possible in the customer lifecycle.

Here are three things to consider and three things to avoid when planning your email acquisition and data quality programmes. Because in marketing, what you don’t do is just as important as what you do.

Three things to consider:

1. If you have a brick-and-mortar store, collect email data at point of sale. This is one of the most common forms of email data collection. According to Experian Data Quality’s 2016 Data Management Benchmark Report, human error is the leading cause of inaccurate data. To minimise this risk, use an email validation solution and make sure you get the right data from the beginning.

2. Determine the ROI of email validation technology. Depending on how large an organisation is, implanting email validation technology in every store could be a huge undertaking. Therefore, it’s important to determine the return on investment (ROI) of this sort of technology at the beginning of the process.

Try this quick exercise: Take a random sample of the data you’re collecting at point-of-sale today without validation systems in place. See how many email addresses you could potentially save at the beginning. Let’s say you determine that 10 percent of the email addresses you collect at the point of sale are incorrect – whether from “fat fingers,” “dummy domains” or the like. Multiply that by the lifetime value of an email address for your organisation.

That simple equation will tell you exactly how much revenue you could be losing in the long run. If your organisation is willing and able to implement email validation and data quality technology on the front end, it will pay off in dividends on the back end.

3. Maintain the quality of your data. During regular intervals (depending on your sales cycle), make sure to ask your customers if you still have the right information. Provide opportunities for customers to update their current information and add more if necessary. You can do this through a request to update a preference centre or directly through emails. This allows you the opportunity to continue providing them increasingly relevant content.

Three things to avoid:

1. Asking for data you’re not going to use. Think creatively about what you are trying to achieve and ask for information that will allow you to create the experiences that are right for your customers. As long as you use their data in a way that they find beneficial – more relevant content or better offers, for example – customers are usually willing to provide more details. Then you can deliver the personalised, relevant messages they want to receive.

2. Asking for data you can get elsewhere. Third-party data providers, like Experian Marketing Services, can add specific data to your database in order to enhance your understanding of your customers.

You can also use website browsing behaviour to drive email communications. Customers want you to personalise their communications without having to give you additional or repeat information. For example, did a customer like a product on your site? Send them an alert if that product goes on sale. Did a customer leave something in their cart? Send a quick reminder so they can easily check out later.

3. Not analysing the data you’ve collected. Analysing the data you have allows you to take your overall marketing programmes to the next level. It is important to understand what types of messages are relevant to your customers and how often they want to receive them. Use past data to discover common behaviours and opportunities. Are you able to tell, for example, how often a customer might go inactive or the reasons why? Can you determine the types of mailings that keep customers updated and active within your brand? Small changes can make your email marketing campaigns even more successful.

Take another look at the lost revenue you calculated. In reality, that number could be even higher when you consider that your analytics are derived from your data. Accurate data means actionable insights. The ability to engage customers in a more meaningful way is priceless.

Lack Of Technology Restrains Marketers In Their Quest For A Single Customer View

The biggest challenge to creating a single customer view is acquiring the technology to integrate customer data points in real time. This ranked number one for 18 percent and among the top three for 46 percent of marketers in our survey. The second-biggest challenge, having access to data from across the organisation, ranked among the top three challenges for 43 percent of respondents.

As we’ve seen, siloed data makes it impossible to understand your customers. Imagine this scenario:

A customer receives an email for a 24-hour flash sale that also includes an additional 10 percent offer during the flash sale if they download the brand’s mobile app. The customer downloads the app and waits to receive the email for the additional 10 percent off. Unfortunately, the email with the additional 10 percent code arrives after the flash sale has ended.

It’s clear that this is a poor customer experience and it stems from the lack of a single customer view. The brand made the customer do extra work – download the app – in exchange for the additional offer, but the brand’s promise of additional savings was not realised. In addition, this is a massive waste for the brand in terms of time and effort and lost revenue from the flash sale that didn’t reach its full potential because customers were waiting for an offer that never arrived.

Client spotlight:Golfsmith - Single customer view informs growth strategy


In 2012, Golfsmith merged with the Canadian brand Golf Town to form the largest golf specialty retailer in the world. This resulted in two disparate customer databases. The multichannel retailer struggled to fully understand cross-channel customer behaviour, integrate customer preferences into its existing marketing programmes and develop a strategy to intelligently build brand loyalty


To fully understand their identified customer base, Golfsmith first had to link separate data sources. Through the Identity Manager of the Experian Marketing Suite, Golfsmith was able to create a persistent ID for each customer, matching data points from across online and offline data sources.

From there, Golfsmith had the foundation to answer important questions that directly impacted its marketing strategy, such as:

  • Which customers shop across both brands?
  • How many customers shop in multiple channels (online and offline)?
  • How does shopping behaviour and customer health differ across these segments and within product categories?


By developing a single customer view across its disparate databases, Golfsmith discovered actionable insights about its customers’ behaviour. Specifically, the brand identified customers’ typical shopping cadence over time and that customers purchasing in specific categories are more likely to remain loyal shoppers. Armed with this information, Golfsmith is focusing heavily on encouraging cross-category shopping to enhance customer loyalty and retention, targeting customers in multiple channels including email and direct mail.

Bringing A Single Customer View Into Focus

The challenges around creating a single customer view understandingly vary by company size. As noted, smaller companies are likely to have fewer data sources and more organisational integration, whereas larger companies are more likely to have many data sources and siloed organisations.

It makes sense, then, that companies with an annual revenue of less than $25M are much more likely to say they do not have challenges creating a complete view of their customers (10 percent compared to 2 percent of enterprise level companies). Marketers in these smaller companies are also more likely to report a lack of customer data among their top challenges.

Enterprise-level companies with more than $1B in annual revenue, on the other hand, are much more likely to rank real time integration technology at the top of their list (26 percent ranked it number one and 54 percent ranked it among their top three). Having access to data from across the organisation was second most likely to be ranked in the first position, tied with the inability to integrate multiple data sources and technologies when expanded to the top three challenges.

Therefore, marketers in enterprise-level companies – more siloed companies – are much more likely to see achieving a single customer view as a technology issue rather than solely a data issue.

While it may be more difficult for those on channel-centric marketing teams to achieve a complete view of the customer, it is not impossible. Technology exists to put these challenges behind you and ease data alignment within the organisation.

The right technology acts as a lens through which a single customer view can be achieved. It can also provide insight, via advanced analytics, that will bring your best customers into focus.

Remove the disconnects causing a disjointed customer journey

Matt Tipperreiter, Product Strategy Director Experian Marketing Services

The term “single customer view” gets used in many different ways and it can mean different things to different people. For our purposes, a single customer view is a person’s identity – the core attributes that bring together marketing events such as each individual’s behaviour, contact data, preferences and motivations.

Managing identities isn’t just an academic exercise. Every organisation needs a strategy to understand who each individual customer is no matter when or how they are engaging with your brand. Doing so demonstrates that you have a firm grasp of your customer’s potential needs and their value to your brand. But how do you get started when there are a multitude of identifiers across numerous customer touch points?

Assess your current strategy

Identity data is constantly flowing into organisations. In many cases, there are specialised applications that manage this data such as CRM systems, marketing databases and other platforms for email, social media and so forth. The problem is, for most organisations, there isn’t a seamless connection between each of these data sets.

First you need to uncover all of the places in which your organisation is capturing customer identity data. From there, it’s a matter of pinpointing which processes are currently in place for connecting disparate pieces of data, then highlighting what is working and what is not.

Build identity profiles

To begin building identity profiles, start by using the first party data you capture from all of your customer touch points. This should give you a good foundation from which to begin. Increasingly, organisations are also relying on third-party data to help fill in the gaps of what is still unknown from using first-party data alone. The key is to make sure this is done in a privacycompliant manner, using a trusted third-party data provider.

While it may be fairly easy to capture all of this data, it is much more challenging to maintain these profiles over time, as well as adapt to new and different kinds of data as they emerge. You will need to put mechanisms in place that can intelligently determine which pieces of data belong to which consumer and manage these identity profiles over the long-term.

Get organisational buy-in

Once you have defined your needs, it’s time to get organisational buy-in. Of all of the steps needed to build a single customer view, this is perhaps the most daunting. Ultimately, you need to reach the key decision makers. But along the way, you must seek out others in order to gain support and momentum toward making any changes to the status quo.

Start by figuring out who owns the data and the systems that consume, use and store it. These individuals may need to be engaged in decisions to make changes. Other points of contact include those who ultimately use the data. This includes marketing, analytics and even customer service teams, who can help isolate how the data is being used and point out any gaps that exist between the current and ideal state.

Define value

The next key activity is to define the value of a single customer view to your organisation. Most organisations operate with a set of key performance indicators. There are several areas that may be relevant to your organisation. Some examples include cost savings, revenue lift or brand experience.

Also, don’t forget to build your business case for funding and determine next steps. Each organisation will be different in this regard, though most companies require that new investments go through a formal process. Knowing all of your stakeholders, as well as the value you define as part of this step, will be important when making your case.

Implement, test and expand

Finally, it’s time to implement and test what’s working and what’s not. For example, after you launch an identity management solution, are your email programmes improving because you now leverage offline and in-store behaviours? Is your website conversion improving because you are able to more carefully tailor content and messaging? And for the ultimate test, is actual customer feedback improving as a result?

Linking organisational data and gaining a single view of the customer transforms generic experiences into meaningful ones. It’s what makes intelligent interactions no matter where you reach the customer.

The Role Of Advanced Analytics In Your Marketing Strategy

More than three-quarters of respondents in the previously cited Experian Data Quality study think inaccurate data is hurting their ability to deliver excellent customer experiences. The demand for data is only going to escalate. In fact, in the next five years, respondents believe data management will evolve to improve the overall customer experience (95 percent), to protect customer’s security (93 percent) and to help inform decision-making through better real-time analytics (90 percent).

Already we’re seeing that advanced analytics like real-time decisioning, predictive modeling and marketing attribution are a requirement for companies that want to compete for consumers’ limited attention – and it’s paying off. According to recent research from The Relevancy Group:

Marketers who make the investments in advanced marketing analytics generate more than two times the revenue of those that do not.

When each interaction could be your last, the best time to put good analytics strategies into practice is today. Lay a foundation of good data management practices and the sky’s the limit for the customer relationships you can build now and in the future.

Real-time Decisioning

Real-time marketing and decisioning is a trending topic in the marketing world, and for good reason. Customer expectation of immediacy means that when they are ready to act, they are not willing to wait. For marketers, this offers tremendous opportunity if they can respond in a contextually appropriate way with the information the customer needs, right at that moment.

The task seems daunting, but the reality is that many marketers already incorporate aspects of real-time marketing into their current programmes. In the survey, 69 percent of respondents shared that they use automated, real-time decisioning as an active component of their current marketing programmes. Well-known tactics like operational triggers (order confirmation emails, for example) use real-time data to populate the message and activate the send. But the possibilities for real-time data can go far beyond the simple triggered email if marketers can align their data and use advanced analytics to optimise decisioning and messaging.

Is automated, real-time decisioning an active component of your current marketing campaigns?

Of the 25 percent of marketers who shared that real-time decisioning was not an active component of their current strategy, 37 percent said that this was due to being unable to prove the value in it, followed closely by lacking the necessary technology (36 percent). A distant third, 19 percent shared that they didn’t have access to the right data.

A lot of marketers don’t realise that they might already have the technology needed to enable real-time decisioning. If you’re on a flexible platform, you can go through the first two phases of real-time decisioning with the technology and programmes you’re already running today. Simply by running side-by-side tests on people who are engaged in relevant, real-time communications versus normal streams, you’ll be able to prove the value of further investment in the more complex data sources.

- David Evans, Senior Director of Solution Consulting, Experian Marketing Services

A crawl, walk, run approach to real-time decisioning

David Evans, Senior Director of Solution Consulting Experian Marketing Services

When marketers think of real-time decisioning (RTD), they tend to think of cutting-edge techniques like predictive analytics and advanced modeling. While these advanced concepts are certainly making headlines, most marketers have a long way to go before they can realistically implement these complex strategies.

The reality is that a lot of marketers aren’t adequately addressing the basics when it comes to using their real-time data. In your current marketing programmes, do you collect your data in real time? How deep is the data that you’re collecting? And are you able to connect this data to your other first- and third-party data sets?

Real-time data and decisioning requires a crawlwalk-run approach. The key is to be realistic about the resources you have and your starting level of sophistication. Remember, real-time decisioning isn’t just about being quick. It’s about focusing the right response at the right speed based on the customer’s needs.

Crawl: Collect and connect data in real time

Without real-time data, there is no real-time decisioning. Email data – not only clicks and opens but location, time of day and device type – is often the easiest type of data to collect. But stopping at email only gives you a slice of an understanding about your customers’ relationship with your brand.#

That’s why it’s imperative to marry your realtime email disposition data with other data sets, like web activity data, social data, offline data (including in-store, point of sale, kiosks and call centre data) and mobile behaviour.

Collecting and linking real-time data requires an infrastructure to house the data and help you link it to your initiatives. This is the beginning of real-time decisioning. I’m always amazed at how few people either don’t collect data or don’t house it in a place where it’s actionable “at the edge” to the Marketing team.

Walk: Design and test programmes using that data

The second phase of real-time decisioning is simply using the data you collect to make decisions. It’s a bit like a game of table tennis. When a customer serves you the ball, you need to come back immediately with the most appropriate response and be ready for their next move. To do that, you have to be prepared for all of their possible interactions and have the right responses ready to go. Understanding your customers allows you to map a response plan to any of their actions at any given time.

There are two ways in which you can use real-time data in this stage. The first is decisioning. What do you do when you see real-time data? What is your immediate response? The second is a bit more subtle, and it has to do with how real-time data can inform the communication itself. For example, if you see that a customer just responded to a specific product category in social media, how can you highlight that category in the content of your next promotional or operational communication?

By using real-time data, marketers can not only ensure that the timing or cadence of the communication is optimal, but also provide the most relevant content to that customer.

Run: Automate and predict using advanced data science

The next evolution of real-time decisioning is about predictive analytics, automation and data science; essentially making instant decisions based on many different variables. This strategy can be used to inform offer optimisation, cadence or channel delivery, or to personalise inbound channels. Additionally, advanced RTD is only improved when more advanced data sources are included in your decisioning engine. All channel response data, purchase data, external data sets such as weather or Internet of Things (IoT) data streams all help paint a more accurate picture of a customer.

It is recommended that marketers approach advanced RTD with caution. Jumping directly to these niche, advanced tool sets without first mastering the crawl and walk steps may backfire. You might be able to power a really unique, singleoffer campaign with an advanced tool, but if the systems, architecture and partnerships aren’t in place to form a sustainable strategy, you’re winning the battle rather than winning the war.

Don’t be intimidated by the overwhelming opportunities in real-time decisioning. You don’t necessarily need to collect all possible data sources to get your feet wet. Take a look at the data you already collect and think about how you may be able to utilise it to create more relevant communication frameworks. If you already collect email data, bring in one or two more sources and use those data points to make decisions about how to react. No matter which data you use first, the process is the same: Find the data source, then design and test programmes around that data source. As you do, find ways to automate and conduct more advanced programmes around them. Then wash, rinse and repeat.

Real-time decisioning around the globe

Of the 69 percent around the globe who are already implementing some aspect of real-time decisioning in their cross-channel campaigns, which forms of data are they using most? According to our survey, online purchase data is the most popular data used to inform decisioning (49 percent), followed by website behavioural data (like browse or cart abandon) at 41 percent and social behaviour at 40 percent. Among data sources that lie outside of channel-specific transactional or behavioural data, propensity modeling and external data like weather are both used by 31 percent of respondents.

The opportunities for using real-time data are numerous, and they vary by type of business and goal. In our survey, we found multiple purposes with fairly equal citations. Real-time decisioning is most commonly used to “Personalise content displayed on website, apps and emails,” “Show the most relevant offers” and “Personalise products recommended on websites, apps and by contact centre agents.”

Respondents in North America and EMEA are least likely to have real-time decisioning as part of their campaigns – 45 percent and 34 percent, respectively, are not using it. Respondents in South America and Asia Pacific (APAC) are much more likely to use real-time decisioning. Online purchase data is most popular in APAC and online chat agent data is commonly used in South America to “Personalise products recommended on websites, apps, and by contact centre agents” and “Personalise content displayed on website, apps and emails,” respectively.

Predictive analytics: A return to fundamentals?

Emad Georgy, Chief Technology Officer Experian Marketing Services

These days, people are always looking for the latest buzzword. For a while it was big data, which introduced a level of scale and speed in terms of processing and making sense of data that no one had experienced before. Today’s buzzword is predictive analytics, but many organisations don’t know where to begin to make it a reality or to translate it into business value. They look to my team for guidance on what we’re doing and best practices we can share.

Ironically, the spotlight on predictive analytics has actually emphasised the need for marketers to return to fundamentals. Brands know their customers the best, so predictive analytics must essentially pass the smell test: Do these insights align with the intangibles you know about your customer? My best advice for creating a predictive strategy is not to aim for the next shiny object. Don’t focus on the algorithms and the technology, but lay a solid foundation of questions you are trying to answer on which you can build a successful analytics programme. Specifically:

  • Set up your organisation so that you have a clear understanding of your goals and what you want to accomplish
  • Make sure you have clean enough data and the technology to make it actionable
  • Forge the right partnerships to succeed

Set up your organisation

Marketers are constantly trying to understand and improve customer experience. The problem is that marketing organisations are not structured in a way that allows them to effectively engage the channel-agnostic consumers of today. It’s nearly impossible to deliver a cohesive experience when the email team is fighting with the social or mobile team for budgets.

Advanced analytics, like cross-channel attribution, can actually help to solve this problem. Proper attribution allows an organisation to look at the customer journey regardless of channel and start to understand the best ways to engage customers, negating the basis for internal feuds.

Specify your goals

Before you write your first algorithm, however, you need to document what the organisation is trying to accomplish and make sure the data is ready to produce actionable insights. Talk with relevant business users to identify the questions you’re trying to answer: What don’t you know about your customers? What challenges are you having? Where are you losing engagement? What do you wish you knew? These questions will become the foundation for your predictive analytics initiative.

Check your data

The exercise invariably leads to analysis of your data inventory, in which you’re likely to see data quality issues arise. Executing advanced analytics programmes requires data quality and identity management. No amount of predictive analytics and insights can replace what you know about your customer.

Attacking the flaws within the data is the first step. Aligning the data is next in line. But remember, customers are more than just a transaction. Your level of understanding needs to extend above and beyond their purchases. That means being able to marry transaction data with behavioural data, lifestyle data, campaign history and so on, to create a cohesive picture of your customer.

Finding the right technology and partners

When you have a platform that’s a one-stop shop, like the Experian Marketing Suite, you can look at performance and levels of engagement across channels all on one screen. This gets teams on the same page, talking about the same customer experience. With a clear layout, you can easily pinpoint organisational silos or areas where the customer experience is disjointed. If you focus on the goals set up front, it becomes hard to justify why those silos exist in the first place.

Predictive analytics is a buzzword for a reason, and it’s one you can’t ignore. According to our Digital Marketer survey, two-thirds of marketers plan to incorporate predictive modeling programmes into their strategies this year. If you’re part of the 33 percent who are not, be forewarned: you will be left behind.

As you build out your predictive strategy, don’t just go hiring data scientists to chase the next big trend. Make sure you have a solid foundation and a clear understanding of what you are trying to achieve. From there, you can start to build really cool predictive analytics to intelligently engage your customers.

Predictive Modeling

Predictive analytics is a branch of advanced analytics which is used to predict unknown future events, behaviour patterns and trends by extracting information from existing data and information. Predictive analytics uses many analytical techniques including data mining, statistics, modeling and machine learning to analyse existing data to make predictions about the future.

Simply speaking, predictive analytics uses what’s known to predict what’s unknown.

Examples include predicting the likelihood of an individual to convert given exposure to an offer or marketing message. This can help marketers allocate marketing spend and determine what happens to return on investment (ROI) if spend changes across channels.

As reported, organisational roles and responsibilities are shifting. This is especially true in advanced analytics. Historically the IT group owned the data warehouse and the marketing team worked with them to execute and code queries. However, the lag time on resulting reports could be weeks.

This simply is not sustainable now. The need for in-moment marketing has caused much of the data responsibility to start to shift from IT to the marketer. You need the right tools in your hands to expose insights in an easily understandable and actionable way – and with ever-increasing speed.

66%of marketers in our Digital Marketer survey plan to leverage historical campaign analytics for predictive modeling over the next year.

Larger companies are more likely to be building predictive modeling into 2016 strategies. For 88 percent of enterprise-level companies, the future is now. If you’re among the 7 percent who are not developing a strategy that includes predictive analytics, beware: you will likely be left behind.

This kind of advanced analytics is very resource intensive and not easy for companies to tackle on their own. For smaller firms, resources like cost and expertise are bigger challenges, while enterprise-level companies struggle with organisational silos, proving value to senior management and the inability to connect data sets. Midmarket companies are somewhere in the middle. They struggle with cost as well as siloed organisations.

A reoccurring theme of this research, we see organisational silos and disparate data cited as more significant problems as company size increases. Without that single customer view, predictive modeling, as with any advanced analytics, is nearly impossible to execute effectively. The maturity level of off-the-shelf tools was a pretty consistent concern for marketers from all company sizes. “Generic analytics engines don’t really work for marketers anymore,” explains Emad Georgy , Chief Technology Officer at Experian Marketing Services. “Without a tremendous amount of customisation, they act more like an analytics factory line where customers are just ones and zeros. The resulting insights are not based on individual customer needs and wants. They don’t allow marketers to create targeted experiences.”

Interestingly, when we look at predictive modeling challenges by job title, we see that C-level executives struggle most with proving value to senior management. Fifty-nine percent of C-level executives overall, and 58 percent of those at enterprise companies ranked this among their top three challenges to leveraging predictive analytics. At least half of enterprise executives also ranked the maturity of off the shelf tools, siloed organisations and the inability to connect data sets as big barriers.

This suggests that leaders in enterprise companies are not able to convince their peers of the benefits to breaking down data silos and investing in the proper solution. This is dangerous because while the investment may be high, the cost of not investing in analytics is astronomical. The right analytics tool, combined with the right data and expertise, can unearth a wealth of insights that lead to a better understanding of your customer and, in turn, better customer experiences.

Customer loyalty has gone away. It’s about the experience. Your competitors are developing toward a cohesive customer experience and they’re going after your customers. You can’t rest on your laurels.

Three top trends that will impact marketing analytics in 2016

Hairong Crigler, Vice President, Marketing Analytics Experian Marketing Services

There are three main factors influencing what lies ahead for digital marketing analytics and how analytics play in the marketing and decisionmaking arena. First, enhancing the customer experience through automated marketing activities has advanced significantly. The progress in the past two years will only continue to have greater impact in 2016. Second, media usage is proliferating across a variety of formats. As a result, a lot more data is flowing into marketing organisations making “Big Data” even bigger. Third, digital and traditional marketing will integrate even further. Cross-channel marketing will be the standard going forward.

So how do these factors impact the future of marketing analytics? Here are what I foresee as the most important trends to watch in predictive marketing analytics:

1. Predictive analytics will go far beyond modeling

Right now, marketers are using historical data to predict what consumers will do next. But knowing what happens next is only the first stage. Predictive analytics has to go way beyond “next.”

All of the data available to us now, or “Bigger Data,” will allow us to look into the future, not just the past. Predictive analytics will not only look at what’s happened in the past and use that information to predict what’s going to happen next, it will see further into the future and forecast the next few steps.

In addition to using data and analytics to create an audience and increase customer value, we see some clients doing interesting things using their first-party data along with Experian data and analytics. For example, a consumer packaged goods client is using predictive modeling to project their customers’ household expenditures on particular products.

2. Prescriptive analytics will become the new normal

While predictive analytics provides us with insight, prescriptive analytics is all about decision making. It enables us to look at the data from the predictive analytics and go a step further into the future. It examines data or content to determine what decisions should be made and what steps need to be taken to achieve an intended goal. Prescriptive analytics tries to see what the effect of future decisions will be in order to adjust the decisions before they are actually made. Taking future outcomes into consideration vastly improves decision making. Prescriptive analytics provides the optimisation process that helps you decide how to use the insights when making a decision and informs you regarding which is the best decision to make.

Nowadays, most marketers who are using data and analytics to drive decisions are focusing simply on predictive analytics. To me, the prescriptive piece is the most important one for marketers. With better education and consulting, marketers will see the importance of prescriptive analysis. With predictive analytics getting more and more sophisticated, marketers will become more comfortable using prescriptive analytics to make decisions. This will definitely will step up and become the new normal.

3. Data visualisation will facilitate interactive data storytelling

Technology advancements will make data visualisation a lot more accessible. It will become increasingly important to use visualisation to tell a data story. On a more sophisticated level, it enables a visualisation of the customer journey so we can actually see the insights. The technology will make data visualisation more accessible and it will be easier to achieve the result we are looking to find. This is a really exciting time to be in marketing analytics.

Marketing Attribution

As marketers take on a larger responsibility for the customer experience, their influence on conversion increases to a level that has never been before. Proper revenue attribution is crucial to determining each channel or touch point’s role in the customer journey. In reality, however, many marketers have little to no understanding of what their increased investments are actually netting them.

Despite the abundance of cutting-edge technologies, the majority of marketers in our survey (51 percent) use overlysimplistic or inaccurate forms of marketing attribution – or simply use none at all.

More than one in ten marketers do not track revenue attribution. This means they have no insight into how their marketing programmes contribute to the bottom line. They must rely on favourite channel biases and gut-based hypotheticals rather than a data-driven understanding of how channels and tactics perform. The majority of those who are not tracking attribution work in smaller organisations. Due to the complex nature of attribution and the high upfront investment, this is not surprising. Additionally, they are probably not communicating in as many channels, so the need to understand how the channels interact is not as imperative. Conversely, enterprise level companies are more likely to integrate multiple channels and have much to gain from finding an attribution solution that can help them understand and optimise their marketing programmes.

When it comes to marketing attribution, you don’t have to compromise

Jonathan Zhang, Senior Data Scientist Experian Marketing Services

Imagine that all of your marketing channels work like a symphony orchestra to deliver music to your customer’s ears. To determine the right mix of sound, you need a maestro who will set the tempo and direct traffic for your marketing efforts. Multichannel attribution is that maestro

There is a variety of marketing attribution solutions available today, from digital and list-based solutions to hybrids of the two. Solutions that focus only on digital or traditional marketing provide a limited view within those channels and create blind spots across them.

If you work in digital alone, for example, your attribution results will be comparing the merits of digital campaigns relative to one another. You can’t know how a digital channel fares against a direct mail piece without additional work, because you’re only looking at a subset of your marketing efforts rather than the entire marketing environment.

This means that marketers have been compromising. While you’re probably better off with partial knowledge from one set of solutions than no knowledge at all, the fact is, if you don’t bring all of the relevant channels together, you won’t get a holistic view of your marketing effects.

The challenge lies in bringing online and offline data together. Most vendors in the attribution industry are simply not able to do this effectively. Marketers need to work with a company that has expertise in bridging that gap, providing the solution that matches your organisation’s needs and maximising your return on investment.

The hybrid attribution solution – which will be the standard in the future – integrates mass media data with the individual level attribution solutions (digital or traditional), essentially dissolving the online and offline divide.

With hybrid solutions, like many we have implemented for our clients, all channels are connected through modeling so you’re able learn how TV advertising affects other marketing areas, for example. We also know the impact of your individual-level marketing tactics. We bring them together to give you a sense of how TV performs against email, against direct mail, etc. When this occurs, it opens up an understanding of the data that wasn’t visible before.

The ramp-up approach to attribution

Embarking on cross-channel attribution can be intimidating at first. One way to ease into the effort is to ramp up channel by channel, starting with the two channels that are most critical to your strategy (or have the most easy-to-access data). Let’s say email and direct mail, for example. First, replicate what you’re seeing in the individual channels so there’s a baseline in each. Then, look at the channels in combination to get an idea of how those channels work together.

Attribution experts can help you pinpoint the differences when looking at the single-channel results versus the fractionally attributed results. We can help you see the results of customers who engaged only with email or only with direct mail, as well as those who engaged with both, providing a clear frame of reference.

Once this framework is set up, you can easily bring additional or emerging channels into the platform. You can continuously add layers of complexity, but always built on top of what you already know.

The ensemble approach to attribution

Another way to start with attribution is the ensemble approach. Here, several attribution methods such as first touch, last touch, fractional, etc., are applied so you can see and compare the range of variations by method and combine results. Again, it’s important to work with a team who is well-versed in attribution methodologies. They can help you understand the merits of each option, narrow them down and determine the appropriate methodology based on what’s reasonable for your business.

Which approach is best?

When working with clients, we ask two main questions to determine which approach to attribution is best for their business.

1. Can you get all of your marketing data in one place?

If you’re in a very large organisation with siloed data, you’re less likely to have a single customer view. You might be working with multiple vendors, which makes accessing data a bigger challenge. You’ll probably want to build your attribution efforts using the rampup approach. On the other hand, if your company already has data aligned, you can implement a full-scale attribution solution and experiment with the ensemble approach to find the best methods.

2. How much managerial input do you want to have into your numbers?

This determines whether you use a method that is 100 percent data driven or one that allows you to incorporate business rules and managerial input not captured by data. We’ve seen hybrid attribution with a ramp-up onboarding work very well for our clients. It means you don’t have to compromise. In the end, you will have the necessary channel performance measures to guide budget allocation.

Attribution models

Overall, 40 percent of marketers in our survey use basic forms of attribution like first touch/last touch (17 percent), in which the entire sale is attributed to either the first or last interaction, or multi-touch (23 percent), in which equal revenue is attributed to each interaction in the customer’s journey. This limited view is better than none, but it does nothing to help break down operational silos and provide truly improved customer experience.

The good news is that 45 percent of marketers in our survey employ more advanced attribution methods. Thirty percent use fractional allocation, which accounts for multiple channels and touch points, dividing a response into weighted values that are measured incrementally and allocated to each channel. There are varying degrees of sophistication within the fractional attribution method. The key is to consistently test and refine the weightings to establish the best equation for your programme.

The most sophisticated marketers in our survey use algorithmic attribution models, either static or learning. Algorithmic attribution models use robust statistical techniques to credit weighted influence across all interactions, typically by comparing the path of customers who convert with that of those who do not. Provided the models are robust and transparent, this is the most objective and reliable methodology available to attribute credit – and it’s the approach we recommend.

This approach provides marketers with a true view into a customer’s interactions across their marketing channels. It’s one of the keys that can drive further analytics. An inaccurate view of the customer’s interactions across marketing channels can negatively impact further analytics. Machine learning algorithmic attribution models are used with more volatile data sets and require alternative statistical techniques that refresh the model on a more regular basis.

These forms of advanced attribution allow for the most accurate insights, which can uncover answers to questions like:

  • Which channel or channel combination generated the highest response?
  • Where and when along a buyer’s journey did a prospect convert?
  • In what way, if any, did a particular campaign or channel influence response?

This level of understanding can have a profound impact on marketing organisations. Cross-channel transparency leads to improved interdepartmental collaboration, the abolition of channel silos and ultimately a more accurate allocation of marketing spend. All lead to reduced costs, maximised return on investment, better customer response and overall improved performance.

Advanced marketing attribution is not easily achieved on your own. You’ll face a variety of barriers such as siloed data and organisations. Senior level buy-in is a requirement in order to allocate the time, resources and budget to derive meaningful results. It’s also important to realise that attribution is a long game. Joining with the right partner is essential to your success. You can leverage their experience and understanding to ensure you’re implementing the right attribution strategy for your organisation.

The role of marketing attribution in a customer-centric strategy

An interview with Victoria Dames

We interviewed Victoria Dames, Director of Global Product Management at Experian Marketing Services, for her point of view on the importance of marketing attribution.

Q. Why is attribution such an important part of the marketing strategy?

VD | Attribution helps you optimise your marketing strategy across channels and therefore is a pivotal piece to increasing efficiency in building successful relationships with customers. Accurate attribution stems from the ability to capture a comprehensive view of your customers. Once you have that you can use the results of attribution to learn things like lifetime value, interaction frequency and channel engagement preferences without needing to directly contact them. Therefore entire organisations are able to make smarter decisions and provide a superior customer experience. This not only leads to increased marketing return on investment and decreased cost per action, but also increases brand loyalty.

Q. Why should marketers bring attribution into their strategy?

VD | There continues to be a growing pressure for marketing teams to show the value of their campaign strategies and attribution can help with this. It should be a key component to any multichannel marketing programme. In recent years we’ve experienced the need for more analytic data to be readily available to our marketers and this trend remains strong. Consumers have changed their purchase behaviours and are using more digital channels. With that comes new information. Marketers have had to adjust how they interact, measure and attribute accordingly, and attribution technology and methodologies have evolved as well.

We are going to continue to see an increased need for relevant and personalised content to fuel the customer journey framework. This raises the level of urgency to engage in attribution across your touch points and begin to baseline your data and measure your growth. It’s more important than ever to be able to reconcile and measure disparate touch points to a single customer, which requires a combination of technology, automated analysis and experts to help interpret the results.

Q. What do you see as the greatest benefit of automated attribution?

VD | There are many obvious benefits to automated attribution when it comes to analysing lots of data across multiple online and offline channels; benefits such as speed, people effort and time savings, etc. However, we recognise that fully automated attribution is a big leap for organisations in the first place. Experian Marketing Services offers a self-service tool that really focuses on ease of use

This enables our clients to focus on the customer’s experience. We are enabling marketers to utilise the same tool they are familiar with for marketing execution to take them a step further in the reporting and analytic arena. Experian has a unique offering by providing years of expertise and service in combination with the automated tool providing clients the ability to utilise different methodologies in parallel as they evolve.

Q. What is holding marketers back from implementing successful attribution programmes?

VD | We are still finding challenges around organisational silos. This is the hardest challenge to overcome because there are many factors within each organisation beyond marketing measurement that must be taken into consideration. The good news is that many marketing organisations are recognising the need to break down data silos and focus on the full customer experience and business outcome rather than performance of one marketing department over another. Attribution can help with this. It utilises a central repository where all of the necessary data is in one location and is actionable by anyone in the organisation.

Q. What can marketers do to overcome the challenge of organisational silos?

VD | A marketer’s focus needs to remain on the desired outcome for the business as a whole. Often times channel managers or business units are measured on their own key performance indicators (KPIs). If we want to increase customer loyalty, then collaboration between channel managers, marketing vice presidents and Chief Marketing Officers is essential and possible. The insight that attribution data brings to organisations helps business silos work more closely together as they approach attribution, and fosters a customer-centric culture.

Q. How can someone get started with marketing attribution?

VD | When starting a marketing attribution strategy, I always recommend starting small. Focusing on a couple of channels and delivering results will help your channel partners and manager gain confidence. It invites the opportunity for a larger discussion around more channels and strategies. The best way to execute for success is to align with a partner that can help drive bringing all of your data together, understanding your customers through a comprehensive view and tracking those different customer journeys – even if it’s only with two channels. This will build the foundation you need to add in more channels as your organisation is ready.

Enhancing Customer Engagement Throughout The Customer Lifecycle

As we’ve discussed, marketers are taking on more responsibility for customer engagement throughout the customer lifecycle – beyond traditional marketing activities. With data and technology positioned with the customer as the central focus in a way that drives organisational change, marketers are able to realise the sought-after goal of crosschannel marketing.

We define cross-channel as a marketing programme that is integrated or coordinated across two or more channels. It means the data coming in from the integrated channels is actionable in each channel. This experience is different than a multichannel programme, which is simply a campaign that uses consistent messages in each channel.

A cross-channel strategy is driven by insights derived from advanced analytics and respects the customer by meeting her where she is – not where a brand expects her to be.

The Traditional Customer Journey Is Dead; Long Live The Customer Journey Framework

There’s a lot of talk about the customer journey and knowing the path to purchase. However, the traditional customer journey, based on aggregate trends among groups of customers, is too rigid to consider each customer’s individual decisions. It’s forced, and customers can feel it. We have to stretch beyond that limiting structure and create a scalable customer journey framework.

Imagine the customer journey framework as a “choose your own adventure” novel. Each reader takes a different path through the novel, just as each customer takes a different path toward engagement. A framework allows you to develop a unique path for each customer, which is flexible based on the exact steps she has taken up to a decision point. It’s the optimal way to deliver the relevance that customers want – when they want it.

Our “We recently held a webinar on this exact topic. In it we covered how to create a flexible framework that allows you to fluidly react to a customer’s interactions - regardless of where they are in the sales cycle.”

Personalisation, The Quintessential Aspect Of Delivering Relevance

Personalisation represents a great chance to create interesting and relevant interactions with the people you are trying to reach. Ninety-three percent of marketers in the 2016 Digital Marketer survey are personalising communications to some degree. As expected, basic demographic data like first name, gender or birthday is the most popular.

Surprisingly, fewer than half of respondents overall use first-party interaction data like email clicks, web browse behaviour or past purchases to personalise their communications. Retail and ecommerce marketers recognise the value in this kind of data and are 38 percent more likely than all other industries to personalise using first-party interaction data. They also over index for using loyalty programme data (36 percent) and preference centre data (10 percent).

Overall, the more sophisticated data points like attitudinal or lifestyle data and third-party behavioural data are less likely to be used. Agency and marketing services and automotive marketers over index for using third party data points for personalisation. While it makes sense that financial services marketers over index for using financial data (15 percent more likely than other industries), agencies and marketing services marketers are the most likely to use financial data; they are 24 percent more likely than other industries to respond that they use financial data.

Consumer electronics were 34 percent more likely to respond that they used geo-location data than all other industries combined.

Getting personalisation wrong can have disastrous results not only on an individual campaign but also on that person’s perception of your brand. Brands that employ first, second and third-party data in conjunction, and do so responsibly, will reap the rewards. However, resources to execute – be they technology, personnel or data resources – are holding marketers back. The lack of technology to execute personalisation is the leading challenge, especially in APAC, where 41 percent of marketers rank this among their top three.

In the UK the top challenge was the ability to easily access information, something that probably stems from issues with siloed organisations. Surprisingly,the second and third biggest challenges were a shortage of data and lack of budget. However, this could be the result of UK marketers being more advanced compared to their global counterparts in terms of access to technology and an understanding of the importance of personalisation.

Actioning on the data in a timely manner and not having enough team members tie for second overall. For marketers in EMEA and South America, personnel stands out as the top challenge (ranked among top three by 39 percent and 42 percent of marketers, respectively). Inaccurate data also plagues the South American marketers in our survey; 40 percent ranked it top three, making it their second biggest challenge.

Enriching data for segmentation and personalisation

Christine Frohlich, Product Management Director Experian Marketing Services

Enriching your first-party data with thirdparty data to enable intelligent segmentation and personalisation isn’t a new concept. It’s been a core marketing practice for several years. By overlaying third-party data such as demographics, behaviours and purchase history, marketers are able to gain a deeper understanding of their consumers’ characteristics and preferences.

This enhanced view of their customers enables them to fine-tune their marketing messages, promotions and product mix to capture their attention. Data enhancement also provides marketers with the insight they need to target prospects who look like their very best customers based on like behaviours, demographics, etc. However, like all aspects of marketing, technology and the expansion of digital media has amplified the opportunities marketers have to achieve that elusive one-toone relationship with customers.

It’s time for marketers to take third-party data seriously. Nothing is more important than your first-party customer data, but it only represents a portion of your customer’s life. Third-party data gives you insight into what your customers are doing when they aren’t interacting with your brand, such as life events they are experiencing, as well as where they are spending their dollars when it’s not with you.

“Smart data” is not only about knowing what data is important, but also knowing how to use it. This means you either need to become a data expert and learn how to sift through the available third-party data options, or work with a company that has the expertise and can help you reach your goals.

In that sense, data education is a key factor in overcoming the challenges associated with smart data. Organisations need to know what data they have internally, what they can access from third parties and how they can use it in a compliant manner. Additionally, marketers must achieve a basic understanding of analytics. As a result, data and analytics education is important for ensuring that the compliance, legal and marketing teams are all comfortable with the intended use of first- and third-party data assets.

Here are some steps for ensuring your organisation is operating in a modern framework around data enhancement for segmentation and personalisation:

Know what you have

Audit your first-party data. If you have data residing in disparate parts of your business, employ tactics to create a single customer view.

Fill in the gaps

Once you know what data you have internally, it will probably become evident that you do not know everything about your customers. Can you develop a strong customer profile with the data you have? Does your first-party data answer the business questions you need to know for segmentation and personalisation?

For example, if you want to better optimise your spend by channel, do you know in which channels your customers are most receptive to marketing messages? If not, you’ll need to work with third parties that can fill in the gaps and enhance your single customer view with data points such as demographics, channel preferences and wallet share to enable segmentation and personalisation.

Not all data is created equal

Whether you’re buying demographic data or digital behavioural data, marketers should assess third-party data on three key factors:

  • Ensure you are working with a reputable, consumer-privacy compliant data provider. Ask how they procure the data and what measures they take to ensure consumers are given notice and choice about the use of their personal information for marketing purposes.
  • It’s not always about who has the most data. Instead, consider the completeness and consistency of the data. You want to know the quality and reliability across the entire database and have full transparency on potential regional or demographic biases.
  • Do the hard work of evaluating the data. In your evolution from data-driven to insightdriven marketing, data performance should be your differentiator in evaluating alternatives. Whether you measure data performance on model dispersion or another method – simply make sure you do it.

Foster an insight-driven marketing mindset

Use customer insights to drive marketing campaigns and deliver relevant and engaging personalised content. Allow the data to tell the story and generate your content in line with that story. Create a collaborative environment between your marketing and data teams. Don’t get handicapped by organisational silos. Band together to create a unified voice and customer-centric programmes.

Align your technology

Executing personalised marketing campaigns requires technology. It touches nearly every aspect of campaign design from data enhancement to analytics, and of course media channel delivery. Many times, technology limitations drive our data and marketing design. Instead, technology infrastructure should be driven by data and business objectives. As an industry, we need to realise that more than just data and marketing need to be aligned. Technology must be aligned as well.

In order to evolve from a data-driven to an insight-driven approach, relevant behavioural data and the technology and analytics that make sense of that data are a requirement.

The Personalisation Spectrum

You’re probably targeting customer segments, using name personalisation in subject lines and building dynamic content blocks on your website – or at least you’re aware of those techniques. But what about real-time individual customer experience management and prequalified product selection? Personalisation, like most marketing disciplines, is continuously evolving both creatively and technically. The result is a wide range of practices, from the simple and familiar to the more complex and seemingly daunting.

Don’t be fazed. We’ve created a personalisation spectrum so you can easily see the various levels and determine what kind of personalisation is best for each type of communication you send.

Stage 1: Static

The first stage in our personalisation spectrum is actually the absence of personalisation. Even the most sophisticated marketer may conduct static campaigns, but this doesn’t necessarily mean a lack of consideration. Campaign-level analysis can provide insights that are subsequently fed back into the campaign optimisation loop. Monitoring campaign performance in response to variable changes (for example, a change in the day of week on which a campaign is sent) shows an appreciation for the customer’s experience. But in treating an audience as a whole, it’s not considered personalisation.

Stage 2: Identity

In seeking to treat customers as individuals – as opposed to homogenous groups with identical needs – the most basic step a marketer can take is to address them as such. This stage can include many quick wins to enhance currently static campaigns. What’s more, these seemingly trivial details really do make a difference. In Q3 2015, emails with personalised subject lines had 32 percent higher unique open rates versus industry benchmarks. Other identity variables can include gender, location and age. Each of these can help you use relevant language or make basic content selection decisions.

Stage 3: Insight driven

Using insight to design customer segments based on characteristics such as engagement status, propensity to purchase or membership tier takes a personalisation strategy to the next level. Though often fairly broad, segments allow you to move away from generic messages and communicate with specific groups in meaningfully different ways. Knowing the commonly held interests or needs of a segment drives more relevant dynamic content or creative. Relevancy is not an end in itself, though. The objective is to use these relevant communications to increase efficiency, engagement and, in many cases, revenue.

Stage 4: Enriched insight

An enriched insight approach is broadly the same as the previous stage, in that communications are refined based on segment preferences gleaned from analysis and insight. The crucial difference is that an enriched insight approach adds further granularity by increasing the number of variables by which a group or segment can be defined. This highlights one of the limitations of an insight-driven approach: access to data. You may have a limited number of fields per record available and will therefore be forced to base your segment preferences on fewer variables than you might like. Enriching insight with second or third-party data helps to work around this limitation by enhancing a record with additional fields. This enables you to develop more accurate views of your segment as well as their preferences, needs and interests.

Stage 5: Single customer view

An effective single customer view provides real-time, individual customer experience management across channels. Where insight-driven and enriched-insight personalisation base communications on segment or group preferences, a single customer view enables you to tailor communications to an individual identity, behaviour and circumstance.

For real-time email, this involves using information about a specific customer and data from that customer’s device to present highly targeted, contextual content. There is an important distinction to be made here between real-time email and dynamic content: the latter is created using fixed data that cannot be updated once a campaign is deployed, whereas the former is crucially more fluid, taking into account circumstances local to the opener such as geo-location, local weather and device language settings.

Live maps are a great opportunity to interact with customers in a personalised, real-time way. In this example, the brand used Movable Ink technology to generate a map of the user’s unique location, placing it prominently within the email creative. This can be particularly effective when paired with a compelling offer, such as encouraging a customer to visit your local store (sign posted on the map) to redeem the offer.

Stage 6: Predictive optimised

Predictive optimised marketing is at the more advanced end of the personalisation spectrum. It takes the single customer view approach a step further by using personal data to anticipate the customer’s future needs. Predictive scenarios – or “next best actions” – can be calculated using variables such as past purchases and browse, click and cart activity, with the end goal of enhancing your communications with highly targeted offers.

Offering products that are pre-qualified to a specific individual is a good example of predictive optimised marketing. Pre-qualified product selection can help increase both engagement and conversion by removing some customer legwork. This type of predictive model is particularly relevant in relation to more complex transactions that are subject to approval – think financial products such as loans and mortgages, or larger items that may require financing.

At the core of any decision on personalisation is the need to keep the customer first. Is your personalisation strategy adding value? Do you have the right data assets and technology to execute effectively? As you can see, the more sophisticated techniques require a fuller understanding of who your customers are, a robust set of actionable data and the technology to seamlessly bring it all to the customer to build better relationships.

Beyond the first name

Ashley Lockridge, Associate Director, Cross-Channel Marketing, Strategic Services Experian Marketing Services

Customers are granting us access to more information about themselves than ever before, and when they enter into a relationship with your brand, they expect you to use their data for good. It’s 2016; basic personalisation is no longer a surprise nor a delight. Consumers expect to be greeted by first name and to receive a special gift on their birthday. Without these standard aspects of personalisation, it becomes clear that they are simply part of the masses.

Marketers, there is even more we can do. It’s time to deliver hyper-personalised experiences that speak to more than just demographics or first name, but also to the many actions that your customer takes each day. Here are four opportunities to consider:

Personalisation of offers based on purchase + browse

Brands are beginning to see huge lifts by segmenting offers based on past transactions combined with recent website browsing behaviour. This takes browsing behaviour one step beyond the one-off remarketing campaign, tying this information to current sales and promotions being delivered to the user. For example, rather than telling a user that there is a 20 percent off sale site-wide, try personalising the deal to reflect the categories browsed and purchased, i.e., “Get 20 percent off summer dresses and the entire site!”

Send time optimisation

You can personalise more than just content. Use behaviour data to personalise the time at which the message is delivered, based on when each subscriber has the highest propensity to open.

This concept is even more effective when you belong to a consortium like Experian’s Email Insights, which can tell you not only when each user interacts with your brand, but when they interact with other brands in their inboxes as well.

Recognition across devices

By using statistical device identification in tandem with recognising, connecting and resolving other identification data, marketers can now understand consumer behaviour across devices and environments. Use this information to personalise the experience in more channels than just email. Retarget users that have abandoned the site with a text message or push notification. Engage users in email by displaying the products browsed in your app. These methods continue the conversation and brand messaging regardless of device.

Changes in the media mix at a one-to-one level

Response attribution for cross-channel campaigns is instrumental in understanding the ideal media mix per user. For example, if you find that direct mail drives a higher engagement rate for customer A, while television is more effective for customer B, you can adjust your contact strategy for each to ensure you’re reaching them in the environments in which they’re most likely to respond while continuing to drive costeffective visibility and repeat messaging across channels.

Personalisation, even in something as simple as the subject line, can drive real business results. Imagine the results when you achieve a unique experience for each customer. This is the way of the future – marketers need to expand their strategies to optimise content, timing and channel for each user.

Pushing the envelope with kinetic email

David Kepets, Creative Director Experian Marketing Services

Now is the time to push the envelope with email. Marketers have been apprehensive to test new ideas with email marketing but are intrigued by the possibilities kinetic email brings to the table.

So what is kinetic email? It’s the ability to include interactive and dynamic actions in email that are executed within the code via HTML and CSS. Interactive is the key word here.

At times “interactive” can be interpreted in a couple of ways:

  1. Multiple taps or clicks: the user interacting with the content
  2. Movement: items moving within the email

The expectation with kinetic email is for the user to spend more time engaging with different areas of the email. These new enhancements go beyond the one tap and actually simulate a web experience with multiple taps all within the email.

We’re not going to see adoption of these new enhancements overnight. The reason is twofold. First, the average user isn’t aware of and doesn’t expect emails to have this kind of functionality. Email historically has been a one click or one tap environment. Even with mobile, which has changed how and where consumers engage with email, the fact is that the average time a consumer spends with any given email is getting shorter and shorter.

Second, as with any emerging trend, there is a transitional period that involves making the consumer aware of the new level of engagement they can expect within their inboxes.

For example, Gmail has been fairly consistent in testing new approaches to how we digest and manage our inbox. Over time we’ve seen several enhancements become the standard while others simply come and go.

We’re seeing new CSS enhancements crop up all the time. For example, we’re testing scenarios that allow the consumer to play several classic games right in their inbox. We’re also paying close attention to engagement levels for different types of kinetic approaches: Do users realise they can actually play the games? Do they understand that they have multiple chances to tap in the email before leaving the inbox?

In the future, these new approaches could be transformed into promotion opportunities, such as playing a game for 20 seconds to reveal an offer or potentially simplifying the purchase process by taking those steps in the inbox versus online.

What marketers need to do is be smart about execution. When kicking off your kinetic email tests, remember to be strategic with the technology and make it actionable. Think of these new enhancements as tools to produce positive end user experiences. Take baby steps to infuse kinetic elements and don’t overdo it. The entire email doesn’t need to be completely interactive. Think about what is going to get a consumer to take action and get to the next level. That way you are not straining your creative and technical resources to create extensive kinetic emails that the consumer will open but never really understand.

Focus on your main goal. Is it to drive the user to your site? If so, too many taps or clicks may not be the right approach.

Advancements in mobile and social continue to push and pull at how consumers interact. There is a constant battle for a consumer’s attention and email is part of that. Kinetic is just one way to keep the user engaged in the inbox. We’re all excited to have these new tools and to be pushing the inbox even further.

Cross-channel Marketing Is The Way Of Life For Enterprise And Midmarket Companies

In today’s world, a single channel programme doesn’t cut it. Customers engage in multiple channels, sometimes at the same time. And they aren’t likely to go searching for brand communications, so brands must meet customers where they are. Being there is not enough, however. Consumers don’t just want to see a clever TV spot or be offered the lowest price – they want to be appreciated, heard and entertained.

29% of marketing teams overall and 59 percent at enterprise companies are still operating in channel-based silos

These teams are failing to coordinate their messages and strategies across promotional channels and devices. This means inconsistent experiences across channels and possibly the loss of an engaged customer – as well as the loss of their current and future business. Marketers can no longer treat each channel as an island. Silos must be smashed so cohesive strategies can be implemented to create a unified experience no matter how the customer wants to engage.

After all, no customer wakes up in the morning and says, “Today, I feel like shopping via email.” THE GOOD NEWS: COMPANIES GET IT.

Do you plan to run cross-channel campaigns this year?

Overall, the website is the most likely channel to be integrated into these cross-channel programmes (62 percent), followed by social (60 percent) and email (55 percent). When looking at responses of marketers in enterprise companies, mobile apps jumps to the top of the list (65 percent) and email moves into second (63 percent). The dark horse, addressable TV, leaps from 29 percent overall to 49 percent.

Uncover hidden opportunities within your email subscriber base

Scott Paprocki, Director of Global Product Management Experian Marketing Services

As marketers continue to examine the effectiveness of new channels and devices to incorporate into their marketing mix, email remains a key ingredient. Whether being used as a personal identifier across channels or as a tried and true channel for delivering marketing messages, marketers will continue to see benefits from maintaining an email marketing programme, even beyond the inbox.

Maintenance is essential to keeping that email marketing programme moving and hinges on managing the overlap between sender reputation, large inactive lists and driving return on investment (ROI). In order to effectively manage reputation scores, marketers end up creating large inactive files, even though this leads to leaving money on the table. To begin addressing the challenge, start with understanding your email subscriber list and you’ll uncover hidden opportunities to ignite engagement.

Gain a comprehensive view of your subscribers

Understanding your best customers is the key to developing your ideal buyer personas when you’re trying to grow your email database. However, because marketers are often incentivised on how quickly they can grow their email database, this can result in opting in various customer personas that don’t all have the same purchase cycle or email usage behaviours and could even fall outside your target market.

The key to identifying the person behind the email address is linking it to your CRM data, then enhancing the profiles with third-party data. Are some of your customers new parents? Have they recently moved? What buying characteristics and categories makes them likely to purchase? These are the types of questions that can be answered by enhancing with third-party data. The answers will give marketers a more complete view of the person behind the email address. Those insights then create opportunities further down the funnel.

Identifying segments for re-engagement

When determining whether or not to keep some inactive subscribers on your email file, keep in mind that seemingly underperforming emails may be inspiring actions across channels. For one online and brick and mortar retailer, an email reengagement campaign drove 3.6 times more in-store purchases than it did direct online conversions. This level of insight is crucial; it’s why linking your own data will help you know which individuals to keep on your list.

What about the inactive subscribers that don’t appear to be engaged with you through other channels? To capture these customers, you need to extend your data-driven approach to create the right re-engagement strategies. Here are three options for confidently identifying “inactive” subscribers that are most likely to re-engage with your brand.

  1. Use your current email data and include all recently added inactive email addresses.
  2. Leverage data enrichment (i.e., name and address associated to an email address) or pinning solutions that can help connect your cross-channel interactions with your inactive subscriber base, as described above.
  3. Use a third-party programme, such as Experian’s Email Insights, to identify email addresses that are active with other brands, but appear inactive with your brand.

By using all three practices of linkage,data enrichment and activity within a global consortium, marketers can target as much as 40 percent of their inactive subscriber file.

Optimise your messaging

By identifying both your target customers and those most likely to re-engage via email, you’ve put yourself in the position where you can focus on your content. Now you can be more relevant and timely with your communications.

Ask yourself, “What content might resonate with the identified re-engagement target segment?” Furthermore, just as third-party programmes can provide predictive modeling for active subscribers, they can also predict the best time of day to send your email communications.

However you decide to recapture your customer through email, it’s important to employ email best practices when doing so. Test your creative and subject lines and always ask your customers for feedback. Combine these practices with creative offers based on what you now know about the people behind the email addresses, and you will achieve the best results.

Target your buyer personas across channels

Keep in mind that email can inspire cross-channel activity from some of your best customers. Sometimes it might even be more relevant to target a customer via different channels to maximise your overall ROI. There are a number of cross-channel activation services that allow you to reach your inactive subscribers via display, mobile, social and even addressable television.

In the hot seat: 5 musings on mobile

An interview with Justin Orgel

We interviewed Justin Orgel, Director of Strategic Services at Experian Marketing Services, to hear his take on the mobile landscape and the year ahead.

Q. What excites you most about the mobile space?

JO | I, like almost everyone else, spend a psychotic amount of time on my phone. When brands do mobile right, they have the opportunity to actually become a part of my daily routine. That’s such an exciting opportunity for marketers to engage at a level that is so much deeper than simply transactional.

For example, Yahoo has created an ecosystem of apps and content that is based on daily habits, and it’s the first thing their customers look at when they wake up. They can check sports, the weather, their email and Yahoo Finance, all from their mobile phone. Their content provides actual value, and as a result, builds a much stronger relationship with the brand.

The most exciting thing about mobile is that it’s nowhere near maturity and has many applications that have yet to be developed. From a marketer’s perspective, there is so much room for new and different customer experiences that are not intrusive, but actually add value and complement the full brand relationship.

Q. How can marketers walk that line between personal and intrusive?

JO | It’s a really interesting topic right now. I think each brand has a different definition, because every brand has a different relationship with its customers. The key is to listen to your customers and test ideas systematically.

That said, there are a few tactics that are generally “best practices.” A big one is creating a preference centre where the customers can decide on the types of messages they want to see and opt out at any time. Giving customers control over how they engage is ultimately the best way to ensure that you’re respecting their individual wishes.

Another recommendation I often offer to clients is to be very upfront and transparent about what you plan to send, how often, in what channels and what the value is. When customers subscribe to your text message programme, or enable push notifications in your app, be clear about how often you plan to engage and the added value these messages will bring to their experience.

Finally, make sure that the messages you’re sending are relevant! Take advantage of technology and machine learning that can understand what interests your customers and send contextual push notifications at times that make the most sense for them.

Q. What’s the most common mistake you see clients make when they build a mobile programme?

JO | Definitely the most common mistake I see with mobile programmes is not connecting the mobile ecosystem with other marketing efforts. For example, I’m working with a retailer who has a mobile app, but they’re not currently connecting that data into their email channel. Because they don’t have a holistic view of what the consumer is doing, they’re not able to message appropriately and target her with better offers. Really, this is a big challenge because of the many systems marketers are using to drive their various channel campaigns, but as we’ve seen with a lot of our clients, being able to bring that data together can have a significant impact on customer relationships as well as revenue.

Q. What is your advice for marketers who are trying to get into the mobile space?

JO | My biggest piece of advice is that you have to assess what your audience will be responsive to. Walk in their shoes to get into the mindset of your customer and try to understand: What’s the value or purpose of marketing on mobile? For some brands, apps make perfect sense. But for other brands (and I see this often with retailers), they are simply replicating the catalogue experience or their website in app form. If there is no added benefit from the web experience, it’s going to be very hard to convince customers to download and interact with your app.

For marketers who want to start slow with mobile, I often suggest starting with a text message campaign. Use SMS promotions to capture email addresses or begin building a mobile subscription list. Text message programmes require much less development and investment than apps, and for operational messages especially, they can be highly effective. They can also help you gauge interest and value, and ultimately make the business case for expanding your mobile strategy.

Q. Any other predictions for 2016?

JO | I think this is the year that retailers will really start to use mobile as a way to bridge the gap between online and in-store data. The app experience is going to become a lot more robust, and along with that, mobile payments and beacon technology will become more regular. Data from these emerging technologies will help marketers tie in-store behaviour to the rest of their marketing efforts. For example, if location data shows that a customer comes into a physical store but doesn’t purchase anything, marketers could target them with a reminder email the same way they do for online shopping.

In general, I think that 2016 will still be a bit of a struggle as marketers try to figure out the best way to engage in the mobile space. But the biggest opportunities will come when brands can create an infrastructure that facilitates the exchange and marriage of all data to create segments and messaging that make sense in many different channels.

Enterprise Marketers Are Moving To Mobile First

68% of marketers in our survey report that they run mobile campaigns.

Not surprisingly, respondents’ most common mobile programmes are promotional in nature. For example, outbound campaigns like offers via text message (39 percent) and inbound campaigns like having a customer text in to request a coupon (38 percent), are the most popular programmes.

There is a persistent trend that mobile users visit or research products on their mobile devices, but convert on desktops or laptops. However, a Business Insider BI Intelligence report predicts that by 2020, mobile will account for 45 percent of ecommerce – as mobile web and app platforms improve and as mobile Millennials start to earn more. That’s more than three times what’s expected for 2016; BI Intelligence predicts mobile commerce will hit 20.6 percent of overall e-commerce, or $79 billion.

Industry Differences In Mobile Integration

Marketers in the agency and marketing services industry are most likely to integrate mobile into their cross-channel marketing programmes. Mobile app is a top channel these marketers plan to integrate into their cross-channel campaigns, second only to the website. Marketers in media and entertainment are the second-most likely to run mobile campaigns, but are the most likely to prioritise mobile app integration. It ties with social as their most-integrated channel.

Marketers in the financial services industry are highly likely to be planning mobile app integrations. Behind email, a mobile app is the channel most likely to be integrated into the cross-channel programmes of financial services marketers. Many financial services companies use mobile apps for banking and enabling quick access to account information. SMS/ MMS is much lower on their list of planned integrations, however.

Pharmaceuticals and healthcare marketers are least likely to run mobile campaigns. “[This] seems like a missed opportunity for these brands. The personalised nature of the industry marries well with that of the mobile channel,” says Chang. “Texting or a mobile app could be an opportunity to provide optimal customer service experiences. Having to log onto a website and sift through a lot of information can be tedious. However, an app that shows doctors nearby or enables customers to easily submit a claim, or even a text reminder about an appointment, would make for perfect personalised mobile experiences.” This highlights the opportunity to make sure mobile, as a part of the customer experience, is not just about marketing but operational and service-related tactics as well.

It might be that promotional marketing messages via mobile is not the right approach for financial services companies, due to privacy or other concerns. We see financial services clients asking about service-related tasks, like transferring money or depositing a check. Incorporating these into the mobile app experience can help financial services companies deliver better experiences and run leaner, more efficient in-branch operations.

Casey Chang, Mobile Marketing Manager, Experian Marketing Services

Mobile Apps And In-app Messaging

By now, marketers have no doubt about mobile’s impact on the customer experience. As we saw on page 90, of those who run cross-channel campaigns, the mobile app is the fourth most likely channel marketers plan to integrate into marketing programmes; for enterprise marketers it is number one.

Overall, mobile apps are 32 percent more likely to be a part of an integrated marketing plan than SMS/MMS and 9 percent more likely than display ads (including mobile ads).

According to The 2016 App Marketing Guide from Localytics, time in-app increased by 11 percent in 2015, average launches and session lengths increased and retention rates also increased in the U.S. There is risk in creating apps, however, because only so many are actually used regularly. The guide reports that 58 percent of app users go inactive within the first 30 days. The more engaged someone is during the early days after download, the less likely they are to churn. Additionally, app engagement is higher among push-enabled users and apps with in-app messaging experiences.

This highlights the need to have a strong engagement strategy in place from the moment a consumer downloads your app. In-app messaging is the top mobile initiative marketers in our survey plan to focus on this year (44 percent). Push notifications are fourth on the list (38 percent). But 53 percent of marketers say they integrate mobile apps in their crosschannel campaigns, which highlights a clear gap, as these should go hand-in-hand.

In a market where apps fail so often, you need a push and in-app strategy to swing things in your favor.

In-app messaging with the Experian Marketing Suite provides the opportunity to engage app users with context-aware mobile app messaging. This enables customer engagement via apps ranging from push notifications for deals and discounts to personalised app content based on user preferences and learned behaviour. Advanced mobile analytics report on any range of app user behaviour like last product viewed, time in app, items in cart and more, allowing brands to intelligently reward loyal mobile customers with special offers in any channel.

While beacons are lowest on the list of mobile initiatives on which marketers plan to focus (18 percent), they are a key way to integrate mobile experiences with physical stores. Location-based app features mean marketers can trigger any range of messages based on a user’s proximity to an in-store beacon. Applications generally involve promotional push messages, but beaconing can also be tied to email, web, social, SMS/MMS and in-app campaigns. They can also be used simply to gather data on customers as they move through retail locations for the purposes of understanding customer journeys in-store or enriching customer records.

With the Experian Marketing Suite, you can identify and link the disparate data of your best customers across all mobile touch points – from devices like smartphones and tablets to platforms like browsers and mobile apps. That means you have a comprehensive, single customer view to support customised and relevant mobile campaigns.

Developing a mobile app? Don’t forget about SMS

Casey Chang, Mobile Marketing Manager, Strategic Services Experian Marketing Services

Marketers are fascinated by mobile, and for good reason. It’s increasingly the device of choice for consumers. SMS and MMS messages, push notifications and the app inbox all offer marketers the ability to communicate directly with customers in a way that is immediate and friendly. Yet there seems to be an interest gap between developing mobile apps and building other mobile initiatives. In this year’s Digital Marketer Survey, 53 percent of respondents indicated that they plan to integrate a mobile app into their marketing programme in 2016, compared with only 40 percent for other mobile programmes like SMS or MMS.

Without a doubt, well-designed apps can be incredibly useful for building the brand relationship. Good apps focus on improving the customer experience by making their lives easier – by tailoring the content to their personal experience or lessening the number of steps it takes for them to perform an action. In service-based industries, apps can alleviate the need for in-store or in-branch services, helping companies become more lean and efficient. For example, consumer bank apps have redesigned the experience of depositing a check or transferring money between accounts, allowing them to cater to their customers’ needs faster and more efficiently than ever possible through a physical teller.

That said, mobile apps are also time- and resource-intensive to develop, especially if they are well designed. Other mobile initiatives, like SMS and MMS text messaging programmes or mobile wallet, require less investment to create and maintain. Additionally, imagine if every marketer who shared a plan to build an app actually followed through. That would mean a lot of competition for customers’ limited phone space.

This is why I find the interest gap fascinating. Mobile apps are useful, but they should be part of a cohesive mobile strategy, supported with other mobile programmes like SMS and MMS messaging. These programmes are less costly and can serve as an effective alternative for communicating with customers who have push notifications disabled, are inactive users, don’t have compatible phones or simply haven’t downloaded your app.

This is especially important for brands that use the mobile space to communicate servicerelated or operational messages, such as shipping and delivery notifications, fraud alerts or travel delay notices that require immediacy. These kinds of messages are time-sensitive and valuable. Customers who don’t have your app will benefit from their receipt if you offer it to them via another channel.

Of course, it’s important to remember that not every business fits usage of SMS and MMS or app programmes. Consider the needs and preferences of your unique customers to determine the need to develop a mobile programme. After all, mobile experiences that are not well thought through may be more damaging than beneficial. According to a Google study of smartphone users, 66 percent of consumers will take negative action if a mobile site or app doesn’t satisfy their needs, such as being less likely to return to the site or app (40 percent) or purchase products from the company in the future (28 percent).

Ultimately, if you’re investing in a mobile app experience, don’t forget about the power of a complimentary text message strategy. Mobile app marketing and text messages can go hand in hand. Develop an SMS experience that proves the value of your brand in the mobile space. Once you do, your customers and prospects will be more likely to believe in the value of your full app experience.

Addressable Advertising Turns Display Into An Engagement Channel

Display advertising is an important component of a cross-channel strategy, yet many marketers view it separately from the rest of their programmes. While direct and owned forms of communication like email, mobile and direct mail all require a known piece of customer contact data, display advertising relies on anonymous identifiers like cookies or device IDs.

For this reason, display advertising is often viewed as an acquisition channel rather than an engagement channel. But when considered part of a holistic cross-channel strategy, display can affect action at all points in a customer’s journey.

Eighty-six of the marketers in the 2016 Digital Marketer survey reported that they build segmented audiences for paid advertising campaigns.

There are a few options available to you when building audiences, the sophistication increasing from one option to the next. The most common is segmentation using standard demographics, such as age, gender or stated interest; 65 percent of surveyed marketers use this tactic. To increase relevance, you can also use lookalike modeling based on the behaviour, attitudes and demographics of your current subscriber base or customer file. But if you’re looking to deliver truly cross-channel campaigns, consider addressable advertising; more specifically, finding your known contacts in the anonymous world and targeting them accordingly at a one-to-one level.

the sophistication level of the targeting tactic increases, the more barriers there are and the less likely marketers are to be using it. Respondents were 12 percent more likely to be using standard demographics than they were to be using lookalike modeling, and 35 percent more likely than they were to be matching subscribers at a one-to-one level

There are seemingly endless ways that marketers can use this technology to their advantage. Some of the ways we’ve seen our clients use it include:

  1. Targeting their most loyal customers or subscribers with upsell offers
  2. Uploading their current subscriber list to use as a suppression file, ensuring they only reach prospects
  3. Specifically reaching inactive subscribers with offers they are missing in other channels

AdTech/MarTech convergence enables companies to meet consumer demands

An interview with Bridget Bidlack, Vice President of Global Product Management, Experian Marketing Services

Q. What does the convergence of advertising and marketing technology mean for marketers?

BB | The collision of ad tech and mar tech, or what is now being coined “mad tech,” is revolutionising the brand experience for both marketers and consumers. We’re now able to move beyond the relevant ad and the personalised email to create experiences that transcend the channels.

Traditionally, advertising and marketing have been separated, with a small degree of connectivity at the cookie level. Advertisers can use their own first-party data, but without a true persistent match, they have to supplement that data with third party data, at the cookie level, without ever being really sure about the data’s precision.

Conversely, in owned channels such as email marketing, where first-party data is primarily used, marketers can enhance their customer contact data with behaviours and preferences. The problem is that they often only use this data within a single channel, resulting in a different view of the customer between paid media and owned channels.

Q. How can marketers surpass these limitations?

BB | When you can break down the wall between paid and owned channels as well as match cookie data to behaviour data, you can reach your audiences across channels with messages that will create the best customer experiences. As the ad tech world continues to become more addressable, it is important for marketers to work with a third-party that has a persistent view of the customers across all channels.

You shouldn’t have to log in to different platforms – which may tell you different things – and try to manually distil that information to understand your customers and their behaviours. What’s exciting about the Experian Marketing Suite is that we can host all of your first-party data in our platform, easily validate that data, then enhance it with our powerful third-party data. You can get to the source of that data for a full picture of those users, all in a single platform.

This helps marketers execute some advanced techniques like creating models that find customers (or lookalikes) in other channels. For example, you may have a subset of email subscribers who don’t open emails, but they do go on Facebook. They are on other sites and in other channels. Now you can extend your reach to them in those display channels and continue the conversation with them even if they’re not opening your emails. For those who do respond to your emails, you can engage them with relevant information based on their behaviours.

Q. What can marketing leaders do to propel the ad tech/mar tech convergence in their organisation?

BB | When information is siloed as I just described, teams are often rewarded based on key performance indicators (KPIs) within their individual programmes. Chief Marketing Officers (CMOs) are in the best position to set the stage for how the team operates and reward collaboration. CMOs need to work with the Chief Executive Officer (CEO) to set up a customer-first overall strategy. That way, every touch point with the customer follows that model, not just the touch points managed by the marketing team in traditional marketing roles.

CMOs also have to team up with the Chief Information Officer (CIO) to ensure data is working in one centralised platform where it can come in and out effortlessly – and in a secure and compliant manner – and be surfaced for stakeholders in an easy-to-use way.

A single platform can help marketing leaders drive organisational change and transform company culture. It enables the paid media, email and other channel teams to share data, insights and understand the full scope of how their customers are behaving.

They can then work together to launch the kinds of programmes that create combined experiences for the customer, whether it’s through email, mobile, direct mail or paid channels. When the CEO buys in, this extends to sales and customer service functions as well. Every engagement with a customer is a marketing opportunity that must be informed by a holistic strategy.

Q. What is the biggest benefit organisations can see from this convergence?

BB | The biggest benefit is meeting consumers’ demands for relevant experiences and providing more value in each interaction. In conjunction, there’s less waste. If someone purchases a product, you’re not wasting dollars by continuing to advertise that product. Instead you can offer related products or user guides. If someone signs up for a programme, you can advertise or market to them about an upgrade. Marketers and advertisers who do that really have an edge over competitors. You can meet the consumer where she is and build on what you know about her to deliver the right message.

Addressable Beyond Webpage Banner Ads: Facebook And TV

The addressable advertising space is not limited to webpage banner ads. Thanks to partners across the web, social and even television, you can use the concepts of addressable advertising to reach your customers at a 1:1 level. One area where this is particularly effective is through Facebook advertising. In our survey, 83 percent of respondents shared that they use Facebook ads as a part of their marketing strategy. It’s most common to use Facebook followers or demographic information to build advertising targets in this channel, but 48 percent of marketers surveyed shared that they are also uploading their email lists to target specific subscribers. Even more promising, 44 percent are taking it a step further and using actual email behavioural data (like clicks or opens) to build more targeted audiences on Facebook.

Another exciting area of opportunity is through addressable television. Similar to display advertising, television is typically a paid, anonymous channel. Unlike display advertising, traditional TV advertising offers even less in the way of individualised response and measurement of those responses. Yet as a powerful channel with very broad reach, TV still accounted for the largest percentage of marketing spend in 2015. TV is a great channel for reaching eyeballs, but its mass-media nature makes it challenging to offer a personalised, integrated brand experience.

With addressable TV, however, advertisers can define their audience based on first-, second- and/or third-party data and serve specific ads to the direct households they are looking to reach. Just as marketers can send targeted emails or direct mail, they can now choose which households will view their ad.

The ability to specify audience at the individual level is exciting not only for the possibilities it offers for targeting, but also for measurement. When you are certain that a specific household viewed your advertisement and you can match that action to a subsequent purchase, you have much greater insight into the impact of your campaigns. Closed loop reporting like this is uncommon in the television space; in our survey, only 32 percent of marketers responsible for television ads shared that they have used this method.

On Facebook, the campaign targeting individuals who had received the email significantly outperformed the control group. Thanks to the cross-channel approach, the audience was engaged in a more cohesive manner, and Mark Group has its lowest cost per acquisition (CPA), even outperforming pay per click (PPC). Facebook advertising has been deemed invaluable in driving brand growth and recognition.

Supercharge your marketing campaigns with addressable advertising

Brie Pinnow, Digital Product Manager, Experian Marketing Services,

This is an exciting time for digital marketers, with the growth of new devices and channels bringing more opportunities to intelligently and creatively engage. However, this rapid channel growth also means there is more potential to overspend on marketing and advertising programmes that do not achieve maximum impact.

For this reason, it’s more important than ever to leverage the addressability of both traditional and emerging channels. Through addressable advertising, you can use first, second and third party data to provide a better consumer experience and higher return on ad spend.

Think of a campaign as a vehicle which uses data as its fuel. In the past, the data that fueled the vehicle was basic demographic information such as age and gender. For example, a marketer may have wanted to target women between the ages of 25 and 35. This gets the car going and, in general, marketers see better performance than they would with no targeting parameters at all.

However, not surprisingly, with limited data and targeting capabilities comes a limited return on marketing investment, campaign effectiveness and reporting capabilities. By supercharging campaigns with richer data to fuel performance, such as customer relationship management (CRM) data, the campaign can travel much further. So where do you start when building an addressable media strategy? There are essentially four different types of data that can be activated for a campaign:

First-party data (CRM data)

First party data is data the advertiser owns and can use for marketing purposes. For example, an insurance advertiser may want to create a win-back campaign to re-engage past customers. In this scenario, the advertiser would select all of the records of individuals who have not been active customers over a certain period of time, then provide that data to an outside party to conduct a privacycompliant match process to the selected media partners across channels. Using their first-party data ensures that the insurance advertiser is targeting their win-back offer with accuracy and precision, the same way they would through traditional direct mail or email.

Second-party data (partner data)

Second-party data is typically referred to as partner data. It is not part of an advertiser’s own customer or prospect records and would not typically be available to buy from a thirdparty data provider. In this example, the insurance company may have a brand partner relationship with an automotive manufacturer.

The auto brand may make a list of recent SUV purchasers available to the insurance company for a co-branded, targeted campaign. This enables the insurance advertiser to create customised, creative messages for the target audience.

Third-party data

Third-party data is data that can be purchased from either an offline or online data provider, such as Experian. With addressable advertising, it is very common for advertisers to combine third-party data with first- or second-party data to enhance their segmentation and targeting criteria. In our scenario, the insurance advertiser has a list of current automotive insurance customers and would like to cross-sell either a homeowners or renters insurance policy to them. Because the insurance company is not sure which customers are homeowners and which are renters, they need to purchase and add a layer of third-party data to complete the picture. Once they do, the insurance brand can target two distinct segments – one of current auto insurance customers who are homeowners and a second of current auto insurance customers who are renters. This is a great example of how multiple data sets can be combined for intelligent audience creation.

Custom models

This last category includes look-alike and custom models. These models can either be built by the advertiser or by a company such as Experian. For example, the insurance company can look at their CRM data and select all of the individuals who have been loyal customers for more than five years by always paying their bill on time and maintaining a low risk to the business. Then a look-alike audience can be created for prospecting purposes. The insurance company is now going to be able to reach individuals who look like their best customers.

Once the audience has been defined, it’s important to figure out where you can reach these individuals across channels and media partners. The scale and reach of an addressable audience is uncovered once the audience matching process takes place. Use a neutral partner like Experian to ensure that you are matching customer records with media partners in a privacy-compliant manner.

By matching audience data to a user universe of media partners, marketers can not only deliver one-to-one messaging, but also measure campaign impact through closed loop reporting. That means advertisers can directly tie campaign exposure data back to both online and offline sales in order to truly understand the ROI of their marketing dollars. The end result is an efficient, engaging, omnichannel strategy.

Where Do You Go From Here?

Let data be your North Star in the quest to develop the perfect relationship with your customers: a mutually beneficial experience that allows your customers to engage in the ways they want and allows you to achieve the goals your organisation sets out to accomplish. Like any pioneer, you need the right tools. For marketing excellence, those tools are data and technology. But data and technology aren’t solutions in and of themselves. The strategy behind the tools is what makes or breaks a marketing programme, and creating a winning strategy comes from working with leading industry experts.

Expert guides can lead you through this expedition. They can help you mine the data to unearth precious insights and understand the best ways to put them into practice. Armed with that intelligence, you can turn your customers into loyal brand advocates by creating exceptional interactions, every time.

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