In addition to the quality of creative and ability to understand its value, there are other key drivers that can help to influence campaign effectiveness. This chapter evaluates the importance of targeting approaches and how marketers can navigate targeting without having to rely on third-party cookies as access to them continues to decline.

  •  Targeting and retargeting without relying third-party cookies
  • Working with secondary partners
  • Contextual and interest-based targeting
  • Behavioural targeting and lookalike audiences

Targeting and retargeting without relying on third-party cookies

The ongoing decline in the availability of third-party cookies is having a significant impact on the ability of companies to understand the intent of customers and use this information to target and retarget users. However, there are alternatives approaches brands can use to reach audiences effectively without having to rely on third-party cookies.

For years consumers have been tracked across different websites and this data has been used and shared between different parties. This has enabled various parties to understand consumers who may be interested in a company’s products and services and serve them with advertising and retargeting communications.

One option that companies can adopt as an alternative to using third-party data to support targeting is to use their own first-party data, enabling them to reach specific audiences and track their activity. The insights they gather about customer segments can then be used to help predict future customer behaviour and as the basis for targeting, as well as supporting identifying similar customers.

“A key challenge as third-party cookies go away is that companies won’t know if people (intent-based audiences) are in the market to buy something. Cookieless solutions like usage of first-party data, server-side tracking, privacy-enabled IDs and contextual targeting can help mitigate the challenge. Sky is currently trying to ascertain through test and learn how we channel the same volume of spend within a cookieless environment to deliver the same volume of sales and effectiveness, or better, and whether contextual audiences in a contextual environment deliver the same outcome or not.”

“With first-party data, the most important thing for a business like Sky is finding more people who look like our customers. If I am trying to acquire new customers, I should be certain that I am not mistargeting to existing customers. That is when first-party data becomes important for suppression of existing customers from marketing, thus delivering cost-saving efficiencies.

“Using a CDP, Sky’s capability of identification of our existing customers has doubled, who we can prevent from seeing a prospect advert. At the same time, for our existing customers’ marketing, we can be more targeted and personalised – managing what they see, and at what point in their lifecycle, thus enabling us to surface the right content to them.”

Kumar Amrendra, Head of Digital Marketing, Sky UK Ltd

An interesting point made by the experts interviewed for this research was around the importance of companies going back to the segmentation of their customers. Deepening a company’s understanding of their existing customer base can help them to identify where and how best to find similar audiences.  Once a company knows the type of audience they want to reach, they can then explore options, such as whether to target similar audiences through Google and Meta, use YouTube audiences, or retarget customers through matching audiences.

Working with secondary partners

Working with a second party gives a company access to the partner’s trusted first-party data, as discussed in the chapter on Data Clean Rooms and Partnerships. A key advantage of working with secondary partners such as publishers, platforms and retail media providers is how their data can support a company in its targeting and retargeting.

“In this part of the globe, the challenge around the effectiveness of retargeting without third-party cookies has advanced faster versus in the west, because of our mobile-first environment in Asia. Social is driving a large degree of traffic to our websites, and a lot of it is mobile-heavy. Therefore, reliance on just purely cookie-based data has gone down quite significantly over the last couple of years.

“Instead, we are adopting a privacy-compliant way of doing typical retargeting with secondary partners.”

Sebastian Cruz, Regional Digital Marketing and Media Director, Shiseido, Asia Pacific

Data partnerships are enabling marketers to enrich audience segments within the partner’s first-party data. The data opportunity in retail media is explained by Dunnhumby in Econsultancy’s Retail Media Best Practice Guide.

Dunnhumby’s Global Head of Product, Strategy and Partnerships, Retail Media and Personalisation, Julie Jeancolas, described four main benefits and opportunities for marketers in retail media:

  1. Access to unique shopper insights: This can help brands better understand their customers and their (often rapidly changing) shopping behaviours, whether that comes from the shift to online or evolving choices due to the rising cost of living.
    .
    Using Dunnhumby as an example, a brand can log into the Dunnhumby dashboard to understand brand performance at an SKU level (such as sales, brand share, number of shoppers, average spend per shopper) against a category level and make period on period comparisons. Brands can also see their shopper profile including level of affluence, lifestyle, what other categories brand shoppers buy, and where they shop (e.g. online and/or offline, locations of stores). This can help brands not only plan retail media campaigns but also other brand activity.
  2. Shopper targeting: Access to a retailer’s first-party and loyalty programme data can enable more precise consumer targeting based on actual purchase behaviours (as opposed to interest, intent or panel data). This can eliminate wastage and deliver better conversion rates. For example, Unilever can target people on Facebook that have shown an interest in baby products, but on Tesco.com they can target customers that have actually bought baby products in the past three months.
  3. A brand safe environment: Many retail media networks have high levels of transparency around ad viewability rates and offer environments which are inherently brand safe, alleviating the concerns that marketers may have with use of programmatic advertising.
  4. Closed-loop measurement: Access to transaction data means that marketers can track the direct impact of their advertising in retail media on sales. This ‘closed loop’ measurement opportunity ensures that retail media is highly accountable.

Econsultancy | Retail Media Best Practice Guide

An example of the potential for a data partnership could be where a company has a particular segment of customers with certain behaviours, but they want to understand the customer behaviour of those buying a different product or brand. By developing a data collaboration, which might be with a supermarket through a retail media solution, they can gain insights about customers that buy a competitor product or other related products. This might also include whether those customers are receptive to discounts or pricing sensitivity. The data gathered can then help with lookalike modelling to reach and target prospects.

Technology providers and platforms are playing an important part in the retail media ecosystem. Examples of these include The Trade Desk, LiveRamp, Dunnhumby, Teads, Criteo and CitrusAd. These platforms have developed sophisticated capabilities, facilitating the improved use of retailer data and easier retail media targeting and trading.

Several platforms have also partnered with retailers to power their retail media offerings, while others act as aggregators of retail media inventory enabling ease of access to multiple retailers via a self-serve platform. To understand more about the retail media landscape and how companies can work with different partners to reach and target new audiences, see Econsultancy’s Retail Media Best Practice Guide.

An increasing number of retail media networks are also developing partnerships with connected TV companies. Laura Chaibi, Director of International Ad Marketing and Insights at Roku Inc, describes how the company is working with other parties to support brands in understanding how their advertising is working across different channels. “We’ve developed partnerships with the likes of Walmart and DoorDash, where these companies already have a very mature data infrastructure. Brands are using clean room technology for privacy-compliant data sharing, and with cookie (tracking) deprecation in digital, media mix modelling and econometric studies are seeing a resurgence to understand where advertising is working.

“In a connected TV environment, there are emerging capabilities being pioneered that allow viewers to engage with ‘shoppable’ action ads using the remote across the TV streamer’s journey. We see quick service retail (QSR) delivery apps and wellness apps being downloaded, or financial brands offering credit card applications or new banking applications. Automotive brands are also finding it a successful way of encouraging potential customers to sign up for more information about car models or to ‘press OK’ to locate a dealer. We’re helping companies to use different techniques to help people get to the next step. But more specifically, it’s about trying to shorten the distance from the communication to sale and remove friction along the way.”

Opportunities therefore exist for companies to form data partnerships and work with secondary partners to not only understand how a campaign has performed within a particular partner’s platform but to reach and target their customer base.

Contextual and interest-based targeting

Contextual targeting is playing a prominent role in the online ad market and the global investment in contextual targeting is set to reach $376.2bn by 2027.[1] This form of targeting is having a resurgence as it offers companies an alternative to third-party cookies.

Contextual ad targeting is a method of delivering relevant ads based on the content of the page a user is viewing, where advertising is aimed at matching a user’s interests, rather than who the user is (or is thought to be). Marketers are then able to put the most appropriate ad in the right context for the customer using contextual signals. It therefore benefits from not requiring large amounts of first-party data or needing consent to work. It can also be served within media like videos, audio and images, drawing on data such as sound, speech, image analysis and metadata for context.

LeasePlan, an online savings platform, wanted to grow its customer base and reach German consumers that were actively researching their financial options. It chose to deploy a contextual targeting strategy, rather than use demographic variables such as age, to reach people interested in topics such as investing, saving, stocks and property.

The company tested the effectiveness of contextual targeting on pages with content related to savings and investment against the use of interest-based audiences across a broader range of websites. The results showed contextual targeting to be especially effective.

LeasePlan combined various data points and analysed website behaviour, conversion rate, customer experience and drop-off rates. It then used AI to detect factors influencing customer behaviour that could not be observed by human analysis, and used the findings to map the typical customer journey from the first brand interaction to opening an account.

Using this approach, LeasePlan was able to optimise its campaign to achieve a lower cost per account opened and increase its account openings in Q1 2023 to more than three times the previous quarter’s figure.

Econsultancy | Case Study Library

From a user perspective, contextual targeting has the potential to offer an improved user experience, where ads served should be more relevant to them. It can also prove beneficial to publishers, with one article highlighting research showing a potential for companies of 2.5x incremental revenue by serving more appropriate, rather than intrusive ads.[2]

Econsultancy has discussed the boom in contextual advertising and how brands can take advantage of it and the developments which are happening in this area, highlighting how Reddit’s acquisition of Spiketrap, an audience contextualisation company, provided the platform with more than 100,000 active interest-based communities.[3]

Further discussed is TikTok’s introduction of a new contextual advertising tool, TikTok Pulse,[4] which is said to enable brands to advertise alongside top-performing content in the For You feed. The emergence of a non-tracking-based and privacy-conscious approach on one of the biggest social media platforms is symbolic of the future of the digital advertising industry.

Connected TV (CTV) and contextual targeting

CTV is a rapidly growing channel for contextual targeting which is providing another means for marketers to reach audiences they are interested in, without having to rely on cookies. Laura Chaibi, Director of International Ad Marketing and Insights at Roku Inc, describes how they are seeing three different marketer types who are maximising CTV to target customers (Figure 1).

Figure 1: How marketers can use CTV to reach audiences

Source: Roku Inc

Viewers can also be targeted in real time based on what they are about to watch as a result of new AI-based targeting tools. Chaibi describes how targeting audiences via CTV is enabling this to drive real-time responses. “In Canada and the US, automatic content recognition (ACR) technology is being used as a form of fingerprinting the programming of live or on demand TV, or even gaming, on the screen. We can then understand whether an ad has been shown to a viewer, so that we can then help the advertiser find what audiences have not yet been shown a particular ad.  

“We can then help brands find incremental reach. For example, with an automotive brand, they may have a linear TV campaign and want to find additional nonlinear TV viewers in our ecosystem, such as those that have accessed a free TV streaming app with ad-supported programming. As the TV streamer’s journey goes on, advertisers have increasingly more creative options to be part of the journey, such as being part of Roku City, or featured on the home screen to reach all TV streamers.”

CTV presents an exciting opportunity for marketers to explore to reach potential audiences and according to Econsultancy’s 2023 Future of Marketing report, almost half of marketers (43%) see this channel as playing an important role in the future.

Behavioural targeting and lookalike audiences

The continuing decline in access to third-party cookies places even more importance on the need for companies to gather and utilise their own CRM data. Even without using information from third-party cookies, CRM data provides quality information about target groups and enables companies to create lookalike audiences of prospective customers.

Segmentation enables an existing set of customers to be categorised or grouped based on four key types of data: behavioural, geographic, demographic and psychographic data. Econsultancy’s Segmentations and Personas Best Practice Guide looks at how companies can use these data types to understand and segment their audiences.

Segmentation provides marketers with clearly defined groups against which hypotheses can be mapped. Without using third-party cookies, companies can look at the characteristics of their target audiences at a high level and determine, based on their analysis, which are more likely to use certain channels and devices. Then across the chosen platform, companies can target similar characteristics and find similar audiences using their own first-party data.

“A key starting point for companies is their segmentation. They can explore the data to create microsegments to understand the different types of audiences and their behaviours. Once you know how to provoke that behaviour it can be tied back to the forensics to see what was the last action someone took and what group they belong to. Then based on someone exhibiting similar behaviour to that group, give that person another set of actions.”

Amy Blasco, Partner, Enterprise Data, Experience and Marketing Lead, IBM

A company can use first-party data for the segmentation and modelling of cohorts and lookalike audiences for future targeting. Google and the social platforms now offer some form of this lookalike targeting. In the past, lookalike models were often based on demographic factors such as age, location, B2B role, etc. Increasingly, these models are also incorporating behavioural data to identify and target new potential customers who behave similarly to existing customers – or even just to target people who behave like a company’s most valuable customers.

Ritual is a premium vitamin subscription brand. It was looking to acquire higher value customers and lower its customer acquisition costs. To do this, the brand partnered with the agency Retina.AI to run a campaign that leveraged the lifetime value data of existing customers to target similar, potentially high-value customers, while also excluding low-value ones.

As a result of building a lookalike model based on lifetime value, the campaign saw a 29.5% reduction in cost per acquisition (CPC), with customers targeted in this way also delivering higher lifetime value versus those acquired through the usual method of audience targeting.

Retina.AI[5]

Kumar Amrendra, Head of Digital Marketing at Sky UK Ltd, describes the broadcaster’s approach: “For lookalike models, we are exploring cookieless technologies for the future including clean rooms, federated learning, server-side tracking, etc. – all of which is enabled through our CDP. We are sharing our first-party data and onsite behaviour like page views, product added to basket, sales, etc. with platforms like Google and Meta to optimise campaigns in a better way through targeting lookalike audiences.”

Google is also helping companies to target users based on their behaviour via the Privacy Sandbox tools Topics API[6] and Protected Audience APIs,[7] as summarised:

  • Topics API: Enables interest-based advertising without the use of third-party cookies or tracking user behaviour across websites. The user’s device would infer topics for a user based on device usage during a period of time. A topic would then be randomly selected for targeting from the user’s top five topics for the time period.
  • Protected Audience API: An in-browser API that enables advertisers and ad tech companies to show interest-group targeted ads without relying on third-party cookies. It is also designed so that it cannot be used by third parties to track user browsing behaviour across websites.

An interesting point raised by Roxane Panopoulos, Group Manager of Regional Measurement & Insights – Netherlands and Nordics at Snap, is that companies should also consider the wider customer funnel to reach a broader audience and to drive incremental sales.

“If a company does a broad targeting impression-driven campaign, which is going to reach as many people as possible and get clicks, we will be able to identify who clicked on an ad and then retarget these users.

“We are trying to serve this new narrative of not targeting people who are likely to do what you want them to do, because it’s very likely you’re actually paying for dollars you would get anyway. Instead it is about thinking incrementally and using a platform like Snapchat, or another platform, to drive reach and awareness, and then driving people down the funnel using first-party data because we know what people did on the platform.

“Getting the right purchase that drives your brand is important, and we are seeing that the more advanced companies are thinking about this the more they focus on incrementality.”

Roxane Panopoulos, Group Manager, Regional Measurement & Insights – Netherlands and Nordics, Snap

This very much fits with a point made by Byron Sharp about how sales growth will not come from relentlessly targeting a particular segment of a brand’s buyers, which he believes harms marketing effectiveness.[8] This was the case for P&G who some years ago found that sales of Febreze air freshener stalled when it targeted Facebook ads exclusively to people with families and pets, but improved after the campaign was opened up to anyone over the age of 18.[9]

  • When looking for an alternative to using third-party cookies, targeting and retargeting can be approached through a completely new lens which prioritises consumer privacy.
  • Moving forward, marketers should collect and leverage their own first-party data, which will help to create reliable customer segments and predict future customer behaviour.
  • Consider where secondary partnerships with publishers, platforms and retail media providers – which have a wealth of first-party data – may help to enhance audience segments and targeting.
  • When used effectively, alternative approaches such as ‘lookalike’ targeting can identify new high-value customers and reduce cost-per-acquisition.
  • Retail media is opening up new and exciting opportunities for marketers, offering access to unique shopper insights, a brand safe environment and enabling more precise targeting based on actual consumer behaviours.

This guide is based on primary research which involved exploring findings from two reports:

  • Econsultancy’s 2023 Future of Marketing report, which was based on a survey of 835 client, vendor and agency-side marketers. The survey was fielded to Econsultancy and Marketing Week’s audiences between 9 June and 3 July 2023.
  • The Language of Effectiveness 2023 report has been produced using responses to an online survey of 1,369 qualifying marketers conducted by Econsultancy’s sister brand Marketing Week between 27 March and 28 April 2023.

In-depth interviews were carried out with industry experts. Econsultancy would like to thank the following interviewees for their invaluable contribution of time and expertise to this guide:

  • Kumar Amrendra, Head of Digital Marketing, Sky UK Ltd
  • Amy Blasco, Partner, Enterprise Data, Experience and Marketing Lead, IBM
  • Laura Chaibi, Director, International Ad Marketing and Insights, Roku Inc
  • Sebastian Cruz, Regional Digital Marketing and Media Director, Shiseido, Asia Pacific
  • Gary Danks, General Manager, AIM, Kochava
  • Mauricio Ferreira, Marketing Effectiveness Lead, Confused.com
  • James Hurman, Founding Partner, Previously Unavailable
  • Gabriel Hughes, CEO and Founder, Metageni
  • Dr Grace Kite, Economist and Founder, Magic Numbers
  • Chloe Nicholls, Head of Ad Tech, IAB UK
  • Roxane Panopoulos, Group Manager, Regional Measurement & Insights – Netherlands and Nordics, Snap Inc
  • Marina Peluffo, Head of Business Intelligence, Prima (speaking as industry expert)
  • James Sharman, Northern Europe Digital Acceleration Lead, Haleon
  • Steven Silvers, EVP, Global Creative and Media Solutions, Kantar

Lynette Saunders is a Senior Analyst at Econsultancy, where
she works on delivering industry-leading research, briefings and
reports for the digital marketing industry and speaks at a number
of external conferences.

Lynette’s previous experience includes delivering web analytics, measurements and insights, as well as leading usability and
customer experience programmes focusing on improving the
overall online customer experience for Cancer Research UK
and the Royal Mail Group.