In the third chapter of our First-Party Data Programmatic Playbook, we turn our attention to the demand-side of the programmatic ecosystem. We’ll look at the unique ways advertisers and agencies can leverage first-party data – and redefine their position in the industry at the same time.
The programmatic supply chain is maturing. Whether you’re a veteran media buyer with a brand or agency, or you’re just starting out, it’s clear that change is the only constant in this industry – and you’re probably wondering what comes next.
With Google finally closing the door on the third-party cookie in 2023, how can advertisers maintain targeting precision, continue to measure performance accurately, and retain the ability to prospect at scale in the cookieless world? Without question, one of their key tools is going to be first-party data.
Here’s what advertisers need to know.
First-party data: What does it mean for advertisers?
We covered the basics of first-party data in the context of programmatic advertising in Chapter 1 of this playbook, but let’s dial in on media buyers.
For the demand-side, first-party data might not come as easily as publishers who have millions of pageviews flowing through their properties every month. Instead, advertisers need to be a bit more creative about where they source their first-party data.
Among others, advertisers can collect first-party data via:
- Website and app analytics
- Purchase histories
- Past interactions (email, phone, or in-person)
- Social media engagement
- Email questionnaires and surveys
- Pixel / beacon tracking events
- Offline systems such as CRM or mailing lists (using onboarding tools to transform the data to digital formats)
For brands who might not have a regular flow of website visitors, such as CPG brands, the challenge is a bit more robust. In these cases, advertisers might use techniques such as micro-sites, real-world experiences, or launch D2C initiatives to engage more directly with customers.
How media buyers can use first-party data – 5 unique strategies
While there’s no one-size-fits-all solution which will work for all advertisers, there’s always something you can do with your first-party data.
It’s worth noting that leveraging first-party data for advertising cannot match the scale of third-party cookies, because you can only target users who’ve already engaged with you. That said, the accuracy of third-party audiences can be a bit underwhelming, so you can at least rest assured that your targeting will be far more accurate.
That said, here are a few key strategies to make the most of your first-party data on the demand side.
#1: First-party data as fuel for universal identifiers
We’ll talk more about identity and the cookieless future in the next section, but in terms of real-world strategies, advertiser first-party data will have a big role to play.
After all, with PII such as email becoming so much more valuable in the cookieless world, advertisers with this asset have the opportunity to capitalize on it, building segments that can crosswalk from their offline first-party data to an online targetable session on a mobile, PC, or other device. They can do this by hashing their emails, acquired through an existing first-party relationship with the consumer/user, or via an identity partner which licenses the data, into one of the universal identifiers that relies on direct user authentication with email (such as Unified ID 2.0 and RampID), thus making them targetable on the open web.
The reason it’s so important to start the planning process for this strategy now is that there are already many competing universal IDs, frameworks that enable inferred device & ID retargeting, and targeting that can be enabled through cohorts or segments modelled from an advertiser’s first party data — with more in the pipeline.
Any player, no matter where they sit in the programmatic ecosystem, will need to choose, integrate with, and test at least a few of these IDs to discover which will work best to achieve their particular goals. How long this will take is anyone’s guess, but the early bird catches the worm.
#2: Use data clean rooms to securely match first-party data
The concept of the data clean room isn’t necessarily new, but it’s one that’s coming into its own as we approach a future without cookies.
In a nutshell, the data clean room is like escrow for digital advertising; data clean rooms provide a secure environment where advertisers can anonymously share their first-party data with trusted partners, including both walled gardens (Google, Facebook) and third-party partners. The best part? They can do this without directly exposing any of their data or entering into any data-sharing agreements.
Think of the clean room like a secure vault: once inside, any Personally Identifiable Information (PII) is hashed, meaning it can’t be pulled by any other party. Clean room technology can carry out secure first-party data matching in a few different ways:
- Match the advertiser’s anonymized first-party data with the ad performance data of the partner (e.g. a Google campaign). For example, an advertiser may discover that a particular creative coincided with a sale at a particular moment, then use that insight to further tweak their campaign.
- Match the advertiser’s first-party audience with the publisher’s first-party audience on the sell side. Once matched, advertisers can leverage private deals built by the publisher to target supply from matched users.
- Matching first-party data sets in order to derive consumer insights about the users within those segments. You may already have plenty of information about these users, but matching in this way can enrich the data with even more valuable data points.
The result of using a clean room for an advertiser is valuable insights into their audience which can be used to enrich their first-party data, opening the door to new segmentation possibilities.
#3: Retargeting existing customers on the open web
Of course, there’s still plenty of road left before 2023 hits us and cookies disappear. In the meantime, you can still make the most of your first-party data using third-party strategies, like retargeting.
Retargeting remains one of the most popular and effective forms of digital advertising, offering a second chance to engage with prospects off-property. But won’t it be a victim of the third-party cookie cull? Well, yes and no.
Yes because many marketers currently rely on third-party solutions to run their retargeting campaigns; and no because it’s still possible to do this using your first-party audiences. To do so, advertisers will need to rely either on the data clean room approach discussed above, or rely on one of the universal ID solutions being developed across the industry.
#4: Prospecting for new customers using lookalike audiences
Another strategy which relies on third-party data, at least for the time being, is lookalike audiences.
Lookalike audiences provide a means to take the positive attributes of your existing customer base, match them up with third-party prospecting audiences, and — with luck — have a higher chance of conversion.
For example, you might want to focus on those customers who spend more on your site, visit more frequently, or simply convert more often. You can then peek into the bidstream and identify what you know about them — device type, operating system, browser language, geo-location, etc. — and combine that data with any third-party sources, like age and gender.
The core assumption here is that people with similar attributes are likely to make similar purchases. If you’re not seeing the results you want, you can shift your parameters, update your lookalikes, and try again. Of course, at least for now, this side of the equation still relies on third-party cookies, but it’s safe to assume that cookieless solutions (likely powered by universal IDs) won’t take long to hit the market once cookies go away.
#5: Leveraging first-party data to inform your creative strategy
Your creative strategy is another area which will gain focus in the future, to make sure that your messaging resonates with your current and target consumers.
For this reason, you can (and should) take the opportunity to use your first-party data to tweak your creative strategy based on first-party insights via Dynamic Creative Optimization (DCO).
For example, you might use your visitor’s on-site activity to deploy creatives which specifically target users who have taken specific actions:
- Added a product to their basket, but never checked out.
- Serve ads dynamically based on a user’s attributes. For example, showing platinum credit cards to specific visitors based on income bracket.
- Engaged with content about specific products or services, but never booked a demo.
By enriching your own audiences in this way, you can reduce time-to-value for customers actively engaging with your brand. You can also use these creative strategies to discover what works on which type of user, then adjust your strategy to generate creatives which convert more customers.
Facing the cookiepocolypse on the demand side
As the months tick by until the loss of third-party cookies, you should focus on the strategies mentioned above to start building a silo of proprietary data.
Of course, the industry is working on a multitude of third-party identity solutions to replace the cookie – but it never hurts to have another arrow in the quiver.
For media buyers, perhaps the biggest casualty of the cookiepocolypse will be the loss of measurement accuracy and ROI calculation, as well as a reduction in addressability at scale. With the reliance (or perhaps overreliance) on third-party audiences from data providers and buying platforms, advertisers have become comfortable being able to address enormous audiences. The only problem is that, even at their very best, third-party audiences were always a little questionable in terms of accuracy. One study conducted by ChoiceStream found that 84% of users within a certain third-party segment were identified as both male and female.
So, in reality, while the loss of the third-party cookie will still impact measurement and ROI calculation, its effect on addressability might not be as severe as we anticipate. In fact, thanks to the deterministic nature of first-party data, targeting might actually improve, but at the cost of scale. While the industry knocks their heads together to agree on an identity solution, the best thing advertisers can do is begin building their first-party data silos and learning how best to activate them.
Not sure where to start with first-party data?
The next chapter of the First-Party Programmatic Playbook will be published on the IPONWEB blog very soon, and we’ll link to it right here.
In the meantime, whether you’re an agency representing multiple advertisers, or you’re an advertiser who’s working with one, now is the best time to start thinking about first-party data.
If you’re not sure where to begin, or you’d like tailored advice about how your business can leverage first-party data on the demand side, just get in touch with the IPONWEB team today.