The Performance Marketer's Retargeting Guide

White Paper

To help enterprise advertisers optimise their growing retargeting programs, Marin Software surveyed 233 digital marketers of leading brands and agencies. A majority of the survey respondents maintain online advertising budgets of more than £250,000 per month. The survey yielded surprising results for this powerful performance marketing channel. In addition to the retargeting trend and benchmark data results, retargeting best practices are also presented based on insights from the survey’s findings, this informative report covers important trends, benchmarks, and best practices.

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The Performance Marketer’s Retargeting Guide: Key Benchmarks, Challenges, and Best Practices for Cross-Channel Success


Retargeting is one of the most powerful performance marketing tools. Amidst the buzz around it, there were still a number of questions on the state of retargeting:

  • How prevalent is retargeting?
  • Are marketers retargeting on a single channel or across channels?
  • For those that are retargeting across channels, what added value does cross-channel retargeting provide?
  • How effective has Google’s search retargeting product, Google Remarketing Lists for Search Ads (RLSA), been?
  • What are marketers main concerns with retargeting?

To answer those questions and more, we conducted a survey of 233 enterprise marketers and inquired about their retargeting practices and challenges. To gauge retargeting performance, we investigated a set of Marin Software and Perfect Audience client data to determine an initial retargeting performance benchmark.

In this white paper, we’ve broken out the focus in the following sections:

  • Retargeting practices, trends, and challenges
  • Search, Social and Display retargeting benchmarks
  • Best practices for retargeting across channels


We asked marketers about their current retargeting practices to understand how prevalent it is in the marketing mix, what retargeting-related challenges and concerns they are facing, and how marketers view future opportunities for retargeting.

Takeaway #1: If you’re not retargeting yet...get started soon

Although we knew retargeting was a popular tactic, we were surprised by how commonplace it’s already become. Based on our survey results, 88% of enterprise marketers are already using retargeting to re-engage users when they haven’t converted or purchased on their initial visits. Of those that don’t currently retarget, poor past performance, poor fit with marketing goals, lack of budget, and privacy/regulatory constraints were listed as the main reasons for keeping it out of their marketing mix. However, over half of this group reported that they had plans to start retargeting within the following 12 months.

Takeaway #2: Google is the major catalyst for driving cross-channel retargeting

The most popular channel for retargeting was display, while search, somewhat surprisingly, ranked a close second.

The popularity of retargeting on search and display aligns with Google’s AdWords retargeting offering through GDN and RLSA. 89% of marketers who were retargeting reported using a combination of Google’s retargeting tools, search retargeting through RLSA, and display retargeting through GDN.

Clearly Google has been effective in using its market leadership to drive retargeting adoption across its display and search properties. However, considering some of the premium, high-engagement, cross-device inventory that’s become increasingly available on Facebook and Twitter, the social channel will likely see quick adoption amongst the retargeting crowd.

Takeaway #3: Marketers are redefining what search retargeting is

Although marketers reported doing retargeting on display more so than any other channel, a higher percentage reported doing “search retargeting” than any other type of retargeting. This made us pause and ask, “What does search marketing mean to marketers?”

In the past, search retargeting has often been referred to as a prospecting tool, wherein an advertiser could retarget users based on a search query, even if the user hadn’t visited the advertiser’s website. However, with Google, Bing, and other major search engines moving to secure search, the opportunities to retarget search queries have dwindled. Additionally, the mechanics of Google RLSA, which requires a user to first visit an advertiser’s website to be added to a retargeting list, has likely changed how marketers think of “search retargeting.”

So what is search retargeting?

  • The most basic definition would be site-retargeting users on the search channel, a.k.a. the RLSA model.
  • At a deeper level, marketers may also be leveraging search intent data to create more granular audience segments to improve retargeting efforts across social and display. For example, a user could categorize a set of search queries under a dimension like “luxury” and use that to further segment audience lists based on their first-party sitebehavioral data.

Takeaway #4: Marketers may be retargeting across multiple channels, but their goals and strategies are not aligned

Of those who reported retargeting across multiple channels, over 50% of them reported having disparate goals for each channel they were retargeting on. This lack of crosschannel alignment is consistent with a recent Econsultancy/Oracle report which found that only 10% of marketers said their messaging, execution, and delivery were aligned when performing cross-channel marketing.

There’s a clear opportunity here for marketers to make their cross-channel strategy and messaging more cohesive by taking insights from one channel and applying them to their marketing efforts in different channels. Some of the best practices outlined later in this paper provide use case scenarios for how that could be accomplished.

Takeaway #5: Attribution, sufficient list volume, and lack of transparency are ongoing challenges

Not surprisingly, attributing performance across different channels is an ongoing conundrum. Algorithmic attribution providers can help marketers provide some definition to the “credit” each channel should receive in a conversion. However, even without advanced attribution models, marketers can still get a better idea of how to attribute performance. They can do so by setting up lift tests to determine how much lift is attributable to the retargeting campaigns, and what, if any, cannibalization there is from other marketing efforts.

Generating sufficient list volume, particularly when retargeting through Google RLSAs, is something we’ve heard from clients repeatedly, both quantitatively and qualitatively, as an ongoing challenge, even for large brands and advertisers. However, list volume tends to be less of an issue on the social and display channels.

The ubiquitous “lack of transparency” rounded out the top three challenges with retargeting. Lack of transparency, as generic as the term is, seemed like it required more digging into.

Transparency means different things to different marketers. However, the common themes seem to involve a mix of media transparency, performance transparency, and pricing transparency. Fortunately, most of these concerns are addressable. Many of these issues could be attributed to the misaligned incentives that can exist when a brand works with a retargeting company who charges on a CPC or CPA basis, while purchasing inventory on a CPM basis. Although it’s true that in this scenario, the retargeting company assumes some risk in the event that the inventory they purchase performs poorly in driving conversions cost-effectively, but it also increases the potential for abuse.

For example, if a retargeting company buys inventory on a CPM basis, but sells it on a CPC basis, its incentive is to buy the highest performing, lowest cost inventory possible. In theory, this sounds great – cheap inventory that drives tons of conversions, who wouldn’t want that? But in practice, this can lead to ads running on low-quality inventory such as parked domains, or web sites that align poorly with a brand’s image. Additionally, because in this scenario the retargeting company profits when relative CPCs are higher than the CPM, the incentive to ferret out click fraud and suspicious activity is weakened.

In most scenarios, issues with lack of transparency can be avoided by working with a retargeting partner who buys and sells inventory on a CPM basis and makes campaign data and reporting available for the advertiser to view at any time.

Takeaway #7: Retargeting represents a small, but growing portion of budgets

By one metric, with nearly 90% adoption, you might consider retargeting as already being a mainstream tactic. On the other hand, when we looked at how budgets were allocated, it became apparent that marketers are still treating retargeting as an experimental tactic that needs to prove its performance.

Retargeting budget is often carved out of existing marketing budget, with about half of marketers reporting that they did not have a dedicated budget for retargeting. Additionally, retargeting spend still remains a small portion of the budget, with 51% of marketers reportedly spending 10% or less of their budget on the tactic.

However, retargeting’s proven ability to drive positive ROI appears to be successfully increasing its presence in marketing budgets, as over half of marketers expect to increase their retargeting budgets across search, social, and display over the next 12 months. Even emerging retargeting channels such as mobile and video retargeting look to be promising opportunities for growth in the next year.


In a prior white paper, The Multiplier Effect of Integrating Search & Social Advertising, we investigated the collaborative power of running search and social ads concurrently compared to marketing each channel in isolation.

Specifically, we found that customers who clicked on search and social ads were more likely to buy and spend more. Additionally, we found that search campaigns performed better when they were managed alongside social campaigns.

For this section, we wanted to investigate if a similar effect existed when marketers retargeted across multiple channels. Specifically, we compared performance for advertisers running retargeting campaigns on Facebook and the Web holistically, compared to advertisers who were only retargeting within a single channel. We also took a look at performance metrics for advertisers retargeting on Google search via Google RLSA, although this data was pulled in isolation from the social and display retargeting efforts.

Google RLSAs drove higher CTRs and lower CPCs

Not surprisingly, RLSA campaigns performed better than non-RLSA campaigns, with RLSA campaign CTRs 2-3× higher compared to non-RLSA campaign CTRs. While it’s no surprise that the search retargeting campaigns performed better, one of the more interesting trends was the increasing performance gap between RLSA and non-RLSA campaigns over the 3-month period.

There are a number of factors that could have contributed to this performance gain. Marketers could have improved their audience segmentation efforts by creating more targeted, actionable segments; they could have optimized budgets by increasing spend on the higher performing segments, and reducing spend on worse performing segments; or they could have refined their creative strategy and messaging to drive better results.

We’ll be keeping a close eye on performance data to see if these trends continue, but the early results are very promising and indicate that there could be additional performance benefits to be gained as advertisers continue to identify new ways to leverage and optimize their RLSA campaigns.

Another interesting finding was that not only did RLSA campaigns have higher CTRs, but they also achieved those CTRs while delivering those leads at a lower CPC2 compared to non-RLSA campaigns. Initially this seems counterintuitive because the basic RLSA bidding strategy is to apply a bid boost to RLSA audiences. If marketers are increasing bids on RLSA campaigns, CPCs should then be expected to be higher.

However, there could be a couple of factors at work here driving down the CPC:

  • The RLSA list is a much more targeted audience, so there could be less competition for those clicks. Accordingly, because RLSA CTRs are higher, the better performance may also be increasing the quality score for those ads, leading to potentially higher placements at relatively lower costs.
  • Additionally, because this data was pulled from a set of Marin Software clients, they may be reaping some of the benefits of the bidding algorithm, which allowed them to algorithmically optimize bids for their RLSA campaigns instead of applying a blanket bid boost.

The key takeaway is that RLSA has been delivering tremendous performance. Not only have marketers gotten better engagement through RLSAs, they’ve done so while decreasing the cost of each engagement.

Marketers who retarget on both Facebook and Display enjoyed better performance

As mentioned above, when we previously looked at the performance data for marketers running search and social (non-retargeting) campaigns, we found a multiplier effect when marketers optimized those campaigns holistically. When we looked at data of advertisers on the Perfect Audience platform, we found a similar effect when they were retargeting on both Facebook and Display channels, compared to only retargeting on one of the channels.

The data above shows that marketers who were simultaneously retargeting on Facebook and the Web enjoyed higher click-through rates on Facebook compared to a cohort of similar marketers who were retargeting only on Facebook.

The findings were similar for marketers who simultaneously retargeted on both Facebook and the Web, compared to similar marketers who were retargeting only on the Web. In this case, the performance gap for display retargeting was even higher than the performance gap for Facebook retargeting data above.


Best Practice: Use search intent to build better cross-channel intelligence

One of the major benefits of including the search channel in cross-channel retargeting campaigns is that marketers can leverage search intent data to create more targeted, higher-value retargeting lists.

For illustration purposes, take the most standard retargeting scenario: A user visits a company’s web site, clicks through to the product page, and then leaves without taking an action, at which point the company now has the opportunity to retarget those users through search, social, or display.

Typically, that’s where the retargeting use case starts and ends. However, without any insight into the user’s intent, it’s difficult to say what value the user actually has, and what the right next step is. A product page visit alone doesn’t ensure that the user was interested in buying the product; the user could have been doing research to become familiar with the category, been comparison shopping, or may not even be in the market for the product at all.

Without intent, a marketer can’t be sure what the right message should be, what creative elements to include, or whether the user is worth targeting at all.

However, if you can overlay search intent on top of your basic retargeting lists, you can segment and refine them to give you more insight and increase the likelihood of conversion. By knowing that a person came in on a particular term, such as a price comparison term, the marketer could know what elements of the retargeting campaign they should tailor, whether it’s the retargeting window (shorter windows for those further along the buying cycle), the creative (featuring the product the user viewed), and the messaging/promotional language (a discount code or comparative claim).

Best Practice: Use Search Intent Data to Build User Personas

A similar concept to the above use case, marketers can group certain search terms together to develop broad user personas, even without the assistance of third-party data.

For example, a clothing retailer may have two primary user personas they target:

  1. Trendy and fashionable, price is no matter
  2. Classic and traditional, price-conscious

Marketers could group a set of keywords that aligns with those targets:

  • For the first user persona, keywords associated with luxury and high-fashion brands, specific product lines, and modern design language could be bundled into a dimension to categorize the persona.
  • For the second user persona, keywords associated with classic brands, traditional colors, and price or discounts could be bundled into another dimension to separate this persona.

By doing so, the marketer can then leverage gained insights when they retarget these users across search, social or display.

An example – two users visit the “Calvin Klein” section of a retail web site – a brand that could be considered both trendy and classic. One user enters the site using a search term for a color that is particularly trendy. The other user enters the site using a search term indicating some price conscientiousness. By using the search intent to segment these two users into the different persona buckets, the retailer could then retarget to these users using creative and language that is tailored to their needs. The first user might see product ads featuring the hottest colors, while the second user might see product ads that also include language for free shipping.

Best Practice: Maximize reach and optimize returns by selectively combining retargeting and negative retargeting across different channels

A common use case for Google RLSA involves increasing visibility to past site visitors by broadening the keyword list an advertiser might bid on. So for example, an advertiser who typically wouldn’t bid on a higher-cost, broad term such as “NYC hotels” could choose to do so for the subset of users that had previously visited the advertiser’s web site. While this is one of the more effective ways to leverage RLSAs, it comes with a couple disadvantages:

  1. It doesn’t drive a whole lot of volume. Not only does the user have to first visit the advertiser’s web site, they also need to enter a particular search term the advertiser is targeting.
  2. More obviously, it doesn’t reach new users. While it may be an efficient tactic, it’s not one that will drive a lot of new business growth. For large retailers, spending in broad, higher-cost keywords like “NYC hotels” is necessary to obtaining new business and maintaining brand awareness.

But what if you could expand your reach and be more efficient at the same time? Isn’t that the best of both worlds? This is where a mix of retargeting and negative retargeting can help drive not only repeat business, but reach new customers more efficiently as well.

Take the above example of a travel retailer bidding on a high-cost, generic term like “NYC hotels” on Google. The advertiser needs to bid on the keyword to attract new customers, but would prefer to avoid incurring multiple clicks on the same high-cost ads from the same users.

To achieve that, a marketer could bid on the initial click and pay the high CPC fees. However, once the user has clicked on the ad and visited the advertiser’s site, the marketer could immediately start negatively retargeting that user on Google to minimize costs. Simultaneously, the marketer could start retargeting to this user on the web through the display ad exchanges, and on social channels through Facebook and Twitter. This allows the marketer to achieve a significant increase in reach and frequency, and stay top-of-mind with the potential customer while doing so more costefficiently than if the marketer had relied on search alone.

Best practice: Leverage search insights to cross-promote and upsell across channels

Another typical RLSA use case involves negative retargeting on those brand terms to reduce marketing spend on navigational terms, especially since larger brands usually have good visibility in the organic search results for any brand-related terms. This is fine if reducing cost is the primary objective, however, it seems like a missed opportunity to simply negatively retarget those brand terms and call it a day. Brands often report higher returns when bidding on their “brand” terms compared to “unbranded” terms. This is likely because the user that searches for and acts on the brand term is familiar with the brand, and closer to making a purchase decision than a user who types in an “unbranded” term and may still be in the earlier research stages. If any semblance of the 80/20 rule applies, it’d make sense to try to reach those brand-aware users with marketing that could help increase business with them.

What if you could take the first-party data you’ve collected about your customer and use that to help cross-promote or upsell products or services that the customer may not have been aware of, but could be in the market for?

Take an example of a customer who clicks on a branded search ad, visits the website, and purchases a purse. Based on these series of actions it could be inferred that the customer is familiar and comfortable with the brand, and could be a good opportunity to upsell or cross-promote. Rather than simply negatively retargeting “branded” terms for this user, the marketer could alter their creative strategy to cross-promote a related product or service. Or if it identified that a particular customer hadn’t registered an account, it could offer an incentive to return to the site and create a login to increase the likelihood of future engagement. By testing different approaches, marketers could turn cost minimization opportunities into revenue generating opportunities.

Best Practice: Sequentially message across channels to move customers along the buying journey

While sequential messaging can already be achieved by leveraging different targeting windows, incorporating search insight data into sequential messaging retargeting campaigns enables marketers to more systematically tailor messaging strategy, rather than simply relying on assumptions around time lapsed, phased periods, or impression sequencing.

For example, search is often a starting point for potential customers researching a product or a category. An advertiser could identify visits from this type of user by categorizing a set of keywords as “research stage” keywords. Subsequent ads targeted towards this user might be focused on promoting educational materials or research tools, or reinforcing the brand image.

The user may then return back to Google with a different query in mind, whereupon the advertiser could have categorized another set of keywords to identify a potential visitor as “buying stage.” At this point, ads across Google, Facebook, Twitter, and the Web could be focused on moving the potential customer further along the buying cycle, perhaps by featuring product images, superiority claims, or promotional language to drive the user back to the site and complete the purchase.

By taking and blending insights from each channel, marketers can get a more complete view of who their potential customers are and how they’re interacting across all of their marketing campaigns, in order to drive increased returns.


At this point, we’ve gone through a whirlwind of different topics from trends, to benchmarks, to best practices. The best practices outlined in the previous section can be effective tests to help marketers take their retargeting campaigns to a deeper level of sophistication. However, many marketers are still value testing retargeting as a strategy, and simply getting the first few audiences set-up and retargeting campaigns running across search, social, and display can provide significant returns.

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