3 Smart Segmentation Techniques: Look-Alike Modelling, Segment-Based Retargeting, Segmenting Loyalty Tiers

1. Lookalike Modelling

Look-alike modelling is all about understanding the key attributes of a small subset of your most active customers.

By understanding these attributes, you can learn a lot about what makes these customers tick. But more importantly, you can then target other people who fit the same bill.

It takes some data wrangling. But with ‘double and triple the results of standard targeting’, it’s a tactic worth adopting.

Why it's a smart move

Instead of looking for prospects and lists by demographic attributes like gender and age only, look-alike modelling gives you the chance to get a lot more specific by including psychographic attributes and behavioural data too.

For instance, if your best customers turn out to be college students who read the Wall Street Journal and buy Red Bull by the 12-pack, then it makes sense that your targeting efforts shouldn’t be restricted to college students alone.

By leveraging your offline customer data and third-party data enrichment vendors, you can build incredibly specific look-alike models and target those who are most likely to buy.

Look-alike modelling example

A leading bank wanted to expand its direct marketing campaigns to reach prospects online.

So they turned to data onboarding and look-alike modelling to find prospects that fit the criteria of their best customers. The results were impressive: 150% improvement in response rates and a massive 40% improvement in ROI.

2. Segment Based Retargeting

The most common form of retargeting is a function of cart abandonment, where the pair of shoes you nearly bought (but then didn’t) follow you around the internet.

In this case, the only contextual data available to those ad units is the fact that you were looking at a certain product or product range. While that’s a great place to start, you can do a whole lot more when you add data about your segments.

Why it's a smart move

By tying your retargeting tactics to your segmentation strategy, you can go a whole lot further than product-centric retargeting. You could, for example, be as specific as retargeting female customers from Estonia who bought summer shoes for their winter break in 2014.

That is, you can use retargeting ad units to target people at different stages in the customer decision journey, depending on the kind of behaviour they’ve demonstrated on your site and other platforms too.

If a certain segment of yours has a higher propensity to buy during certain seasons, then your retargeting ads can dynamically deliver certain customised messages to that segment, while targeting others with more general acquisition offers.

Segment-based retargeting example

Even though retargeting is most prominent in the retail industry, it has been successful in other verticals. For instance, one niche insurance vendor that offered online quotes in real-time (as opposed to over the phone) used retargeting to make sure small-business decision-makers completed the request-a-quote form online.

Not only did users who left the form midway come back after being retargeted, a meaningful proportion of them actually ended up converting into sales.

You Should Also Consider: CRM Retargeting

CRM retargeting is all about using the data stored in your offline CRM systems (purchase history, contract expiration dates…the good stuff) to retarget your customers online.

And it makes sense for any brand with a CRM system and customers – so, pretty much anyone reading this sentence.

First, because sending acquisition deals to customers is a waste of media spend and just plain ineffective. And second, because as any salesperson worth their salt will tell you, you’re a whole lot more likely to sell to someone you’ve already sold to before.

But even beyond retargeting, your offline CRM data can give you a lot of important insight about buying patterns and trends. So it’s worth using it to fuel a lot of the tactics we’re writing about in this eBook such as audience suppression, look-alike modelling, segmenting your loyalty tiers, and reactivation.

3. Segmenting Loyalty Tiers

If you think about it, marketers have used loyalty tiers to segment their customers for years. From tiered credit cards to frequent flyer programmes, it’s been a good idea to have ‘gold’ and ‘platinum’ members for some time now.

So when it comes to digital marketing, targeting those tiers with specific offers is really just low-hanging fruit. And the smartest digital marketers are already picking it.

Why it's a smart move

By onboarding your offline customer data and segmenting it into different loyalty tiers, you can target those customers with unique offers online. You can also optimise your bidding strategy for audiences that are likely to convert at a higher rate and spend more.

Your offers become more specific, you maximise the value of your dynamic digital ad units, publishers, and platforms and most important of all – your most loyal customers get exclusive experiences.

Segmenting loyalty tiers example

As you’d imagine, this is a tactic most popular among industries where loyalty tiers already play a big role, such as financial services, retail, and travel.

But even if you don’t already have a tier-based loyalty program already set up, it makes a lot of sense to build one around your offline customer data.

One of the most famous uses of loyalty tiers is Starbucks Rewards where customers get better offers the more they use Starbucks’ mobile application. And the more information they share, the better the offers get. For instance, gold card members get treats and drinks for free on their birthdays.

Smarter Segmentation for Seamless Marketing

When segmentation is informed by in-depth customer data insight, it offers improved intelligence and targeting for marketers across all niches and verticals.

Of course, look-alike modelling, segment based retargeting and segmenting loyalty tiers are just three of many options marketers have. Combined with other segmentation tactics like audience suppression, geo-targeting, targeting based on anonymous activity and more, segmentation strategies become immediately more intelligent and effective for precise results.