Digital Targeting Evolution, First View ’22.

The Digital Targeting ecosystem has changed significantly over the past few years and the rate of change shows no signs of slowing. 2022 will bring about a major milestone in privacy navigation, as Brands respond to losing the remainder of third party cookies. In this series of Quarterly reviews over the course of 2021, I’ll be monitoring and mapping this ever-changing landscape into an illustrative blueprint for inform Brand’s plans for both the immediate and longer term.

As part of each update, I’ll reflect the latest “state of the ecosystem” from a Brand perspective, as we reassess targeting and journey towards the aforementioned Cookie deprecation. I also nod to the importance in endeavouring to seek out privacy centric solutions that not only protects the integrity of User data, but also future proofs the brand against potential wider e-privacy legislation.

Update One – Q1 2021.

Let’s overview the current state of affairs that have informed the Q1 update.

  • We’ll imminently lose the key Apple MAID, the IDFA, as part of the IOS14.5 update being rolled out in the coming weeks. If not mitigated, it’ll reduce the match rate % of 1st party data into platforms like Facebook. It’ll also potentially hurt the platform’s audience scale if there’s a high rate of attrition, as platform’s battle with consent opt-out. It also likely won’t be the last on Apple’s privacy roadmap once implemented.
  • The existing accuracy of targeting via third party cookies, after previous privacy updates left their integrity compromised, is poor. Meaning searching for an alternative makes sense not only from a user standpoint, but also from the perspective of maintaining effective investment decisions. “I’ll just move the budget to Search”, unfortunately doesn’t stand up in the wider context of Media optimisation – so solving this is an important priority, albeit Brand dependant.
  • Third Party cookies will disappear entirely in February 2022, based on existing timelines, as browsers search for alternative methods of building audience cohorts (see Google’s FLoC and the mixed response from other browsers in adopting the concept).
San Francisco, Lombard Street.

In light of the above, I’ve made some key observations in the Q1 update.

Adopting an agile solution for Server to Server integrations is going to be key. The ability to supercharge targeting, algorithm optimisation and reporting by feeding platforms more data, including any Brands that have any offline event dependencies. Facebook’s Conversion API is one essential example for anyone that has a heavy Digital investment in the platform. As I’ve illustrated above, key web events and user actions still classify as 1p data and making more of this available to partners will benefit optimisation. One additional point to make here is the ability to optimise towards some kind of Value parameter compiled by Data Science. A really interesting way to get the algorithm searching for users who look like those who show a certain propensity score for example.

Direct to Publisher relationships are going to be a crucial part of maintaining Programmatic Reach exposure with some level of logic applied, either harvested via logged in users (Reach plc) or wider conglomerates (like the O-zone project). Again, a use case for server to server integration in being able to tell how a certain % of your user base is interacting with a publisher ecosystem and where. A powerful audience measurement conversation to be having. Yes you’re not getting the scale that an open marketplace provides, but you’re covering off a solid % of the premium inventory available and creating a miniature ecosystem for a directly negotiable price.

San Francisco, Lombard Street.

Finding the next big alternative identifier outside of Cookies has been spoken about enough in Q1, so let’s focus on something a bit more interesting in Data Clean Rooms. Outside of finding the aforementioned identity alternatives, you should also be looking at solutions like Data Clean Rooms, a data match-make between your brand and other relevant brands that would provide impactful insights and eventually, targeting. Take a look back at a brilliant presentation and deck that Mighty Hive put together a few years back for a deeper dive here. Essentially what we’re looking at is a completely privacy centric method of being able to query a database for insights that’ll help you answer certain questions such as “do my high value customers attend live sport events”, via partnering with an event ticketing company. Neither have access to the other’s data and everything takes place within a “clean room” environment. It’s absolutely one to be exploring in response to the privacy measures we’re seeing and will continue to see over the next 12-36 months.

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That’s all for the first iteration of the Digital Targeting Evolution series. I’ll be releasing quarterly updates in the form of newly written articles, as well as getting some other opinions from around the Digital Marketing industry on how Brands and Agencies are tackling some of these transformational milestones. As usual, get in touch with any questions or future content ideas.

Neil Jones.

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