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Posted By:
Jürgen Galler
CEO & Co-founder at 1plusX
Why Post-Cookie Digital Marketing Can’t Rely On Solutions From One Single Entity
How to access consumer data amid rising global privacy restrictions with third-party 🍪🍪🍪 facing stricter limitations.

Why Post-Cookie Digital Marketing Can’t Rely On Solutions From One Single Entity

Amid rising global privacy restrictions, accessing the data needed to understand consumer behaviour and serve content that breaks through has become increasingly tough; especially with third-party cookies facing stricter limitations.

Of course, this isn’t news to marketers. According to WARC, digital privacy is a key priority for 88% of marketers this year, while over half (52%) are working to strengthen data policies. But the search for alternative methods of tracking and targeting rolls on.

So far, the industry has looked to technology to deliver the answer. In particular, the focus has centred on walled gardens and their efforts to develop fixes that will create a balance between privacy protection and data-driven marketing. Yet as we inch closer towards Google’s cookie cut-off date, marketers are facing a tricky question.

Should they keep waiting for the silver bullet— and if not — what can they do to keep the digital marketing engine running?

Levelling the playing field

Many marketers see Google as the obvious candidate to find a way of addressing digital privacy challenges and it’s not difficult to see why. With a sizeable slice of ad spend and its Chrome browser accounting for 69% of desktop internet use, the media giant has plenty of motivation to protect digital advertising. Moreover, Google has also declared its aim to build a better online ecosystem with its Privacy Sandbox project, and specifically TURTLEDOVE.

In brief, the concept proposes to enable continued targeting by curbing data flow. Using two uncorrelated ad requests to send key information to ad servers — including page URLs and user interest groups — the application performance interface (API) will allow auctions to run on user devices but hold data in browsers, instead of remote servers.

While the project has promise, there are several possible pitfalls. Beyond the fact it is still only a conceptual proposal, the API would see advertisers lose access to vital user-level data; any data would be hidden inside the user browser, blocking transparency, quality evaluation and any other use a marketer would benefit from. In addition, the data can only be used for advertising purposes, and not for reporting, simulating or creating consumer “personas”. At the same time, browsers keen to stay competitive by launching their own rival frameworks could make the complex digital landscape even more confusing and harder to navigate. Instead of pinning their hopes on concepts that will widely limit the way marketers are able to use data, the best move is to create stronger data independence. Exploring solutions for data enrichment and data exchange, that are ready to be deployed now, will give marketers stronger independence from vendors such as Google. Many of these solutions are available from independent players which automatically gives those companies, and the wider open web, a greater chance to come to the table with viable input and therefore foster fair competition in the long term.

Looking for intelligent answers

First on the list of actionable alternatives for marketers is making efficient use of existing data. Obvious as it might seem, the first-party information brands hold about customers has huge scope to fuel more refined targeting that doesn’t depend on third-party cookies or monopolies, particularly when leveraged with smart tools.

Developments in artificial intelligence (AI) have driven significant innovations in data orchestration. But the capabilities of AI-assisted platforms aren’t limited to bringing disparate information into useable order; they can also conduct a holistic analysis of data pools and instantly obtain granular insight into individual interests and behaviour — thereby giving marketers the information they need to build better customer profiles and deliver more personalised, impactful ads.

The most sophisticated tools allow using algorithms to identify customer needs and predict what they will do next. Through integration with key activation channels — such as ad servers or exchanges — marketers can use this insight to align their campaigns with individual requirements in real-time, maximising the likelihood of engagement and conversion. Additionally, there are also opportunities to combine predictive analytics with performance assessment supported by machine learning; resulting in a constantly improving picture of what works for the customer that can be used to drive continuous targeting optimisation.

Finding a way forward together

Success in the new era of digital advertising will depend on closer collaboration with publishers. As a solo entity, owned customer data has vast, and often under-utilised, power. But connecting their data to first-party publisher information will help marketers achieve larger scale and more precise advertising within the open web — and without the need to bring in external cookie-based data.

The biggest advantage of publisher partnerships is enhanced audience matching. Bringing together brand and publisher data makes it easier to determine which audience segments have the highest level of crossover, especially if matching is driven by automated tools.

But once more, this is only a small part of what today’s marketing intelligence can do. Modern AI platforms have the capacity to look deeper than broad audience groups. For example, they can pinpoint the unique attributes of high-value customers and analyse publisher data to find individuals with similar traits; meaning ads will not only reach relevant users, but also those with the highest probability to convert.

Similarly, the same principle allows for considerable campaign expansion. Using a basis of ‘ground truths’ about known customers, intelligent tools can run advanced modelling and pattern analysis to identify core characteristics; enabling marketers to find and target lookalike audiences across multiple publishing partners, filtering by an array of attributes from interest to age, gender and other demographic categories.

In an industry known for its continual innovation, it’s not surprising that confidence in big tech to solve cookie challenges is high. But for now, the best efforts of major players are still looking like castles in the sky. To safeguard the future of the digital economy, marketers must stop waiting for the reinforcements to appear and start taking action. By using the AI tools already available, they can harness the full value of their own first-party data and build connections with independent publishers that enable them to reach further and thrive, independently.

(***This article also appeared on AdvertisingWeek360.com.)

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