Changes in the digital ecosystem, driven both by regulators and the evolving policies of big tech companies, require a substantive response from brands, argues Brian DeCicco, NA Chief Data Strategy & Analytics Officer at Mindshare.

The way that consumers engage and transact with brands evolves almost every day. Today, according to research from GroupM, 77% of consumers globally have concerns with how companies use their data. For brands, the pursuit of knowing your current and potential customers better than anyone else is thus paramount to success.

Commonly, we call this building an identity strategy – the focus on creating an accurate and persistent view of the consumer journey and relationship with a brand across touchpoints. And the ecosystem that supports these strategies is undergoing a major reset, from Apple's iOS tracking updates and Google phasing out third-party cookies to the American Data Privacy and Protection Act (ADPPA) and still more changes to big tech policy and privacy regulation on the horizon.

Building the intelligence to holistically, authentically and directly serve your customers today is akin to the dynamics of modern dating. It’s about banking shared experiences to build upon that foundation of trust and mutual value. And it’s about being respectful in what you ask, identifying boundaries and crossing them on the right terms.

Imagine going on your fourth date with someone but forgetting what you talked about on the first date. How do you think that potential partner is going to feel about the prospects of a relationship if you cannot keep key pieces that make up who they are straight – how big their family is, what they do for a living, what they picked off the menu that first time? They’ll think this person isn’t that into me because they aren’t listening to me.

Considering how consumer expectations of brands have changed dramatically, let’s take the dating analogy a step further. Just as important as listening to your date is acknowledging their boundaries and appreciating what they choose to NOT share with you out of the gate or in certain contexts.

The platform age enables this, creating the ability for each of us to portray different versions of ourselves within each digital environment. In Mindshare research on identity and culture, we have found that preferences, opinions and moods can all change based on context.

Between these consumer and ecosystem changes, the once-semi-stable status of the digital identity ecosystem has begun to destabilize.

So what do brands do in this new world? How do they keep from falling behind? And, yes, falling behind is a reality despite the updated delayed timeline on retiring third-party cookies announced by Google earlier this year.

There are four immediate actions marketers can take to keep their foot on the gas and ensure the durability of their data and technology strategies:

1) Audit your dependency on third-party cookies and other identifiers

If you haven’t started doing this yet, you are already behind – but you can catch up.

Every brand must audit their strategy to determine the current dependency of their marketing mix on various identifiers, and its resiliency to the changes in the identity landscape to come.

You can diagnose this by looking at delivery by channel, operating system and tactic type (e.g. contextual, data-targeted, etc.). Leverage those insights to identify where to place your bets across identity resolution technologies, machine learning and more.

Across Mindshare and GroupM, we do this regularly, and thoroughly, through a codified assessment framework that we developed.

For brands to continue to deliver on the data-driven strategies of today, it’s imperative they own and control not just the data and the tech, but also the identity mechanism that makes that data actionable across marketing touchpoints. Audit your dependency and then build a roadmap that takes you from renting to owning identity to reduce the risk in your martech stack.

2) Determine your right to direct, consented first-party relationships and invest to scale that intelligence

It’s easy to argue that direct, consented consumer relationships are more important than ever. Often these recommendations fall on the frustrated ears of brand marketers who have never had, and may never have, a good value exchange for the consumer to rationalize the collection of personal information.

The answer isn’t that data-poor brands shouldn’t care about identity (which is an overused retort). Data-rich and data-poor marketers have, and will continue to find, value in precision marketing strategies.

Start by determining what data you can collect within reasonable expectations of the consumer using a value exchange exercise that takes into account the ethical considerations of collecting different data as well.

Having a data ethics framework answers the "just because we can, should we?” conundrum for many marketers. We call this a data by design strategy, and it will ensure you’re set up to capture your fair share and depth of consumer relationships.

3) Manufacture new, unique signals through a more diverse data strategy

As marketers seek to combat the shrinking scale of in-app activations as a result of Apple’s iOS changes, it’s critical to find ways of scaling your first-party data through data fusions, modeling and other enrichment techniques to unlock intelligence on your terms.

Retail media networks will increasingly gain in importance in this world as a larger and larger share of consumer purchases occur in these platforms. Every marketer, especially in the consumer packaged goods (CPG) space, needs to have an identity strategy that includes data collaboration, not just data collection, with retail media walled gardens. Often that is through those partners’ own data clean room solution or neutral clean room service.

All of this allows marketers to embrace a philosophy of data diversity as opposed to chasing a single, universal source of truth – increasingly a lost cause – in the pursuit of information asymmetry.

4) Invest in artificial intelligence and machine learning to democratize data science

The explosion in artificial intelligence (AI) and machine-learning applications for personalization have finally made the integration of precision media with tailored creative an economically viable option for more brands.

As personally identifiable information (or other deterministically informed) matching is likely to become an increasingly rare avenue for activation in the changing ecosystem, probabilistic matching and cohort-based solutions will become increasingly important.

This requires more sophisticated analytics enabled by machine learning applications, more often leveraging multiple match keys to stitch together actionable intelligence. As deterministic match rates decline with activation endpoints, probabilistic matches and constant experimentation to validate the accuracy of those predictions is the difference-maker.

AI is at the heart of all of this emerging capability; unleashing it across your marketing use cases by democratizing data science application for better, faster campaign optimizations is the key.​

While some big tech solutions can feel more like an exercise in preservation, resulting in more isolated impact within their walls, consumer behaviors will continue to shift to places and spaces beyond those walls (e.g. via connected TV, virtual/augmented reality and the metaverse). In this new landscape for brands – data-rich or data-poor – creating an enduring identity strategy is about winning the space between regulation and ethics.

If done correctly, despite all the changes in the ecosystem, marketers can still activate consumer intelligence that is earned directly and/or harnessed respectfully. Managing to maintain the strength and optionality of that asset is the name of the game.