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Pierre Naggar : brands that build advertising equity needn’t fear the “no data zone”

GDPR recently celebrated its fifth anniversary, yet privacy-first advertising remains a work in progress. The triple-whammy of regulations, cookie deprecation, and Apple’s ATT framework have scattered the once connected web of signals that powered modern advertising. This has led some to declare that the industry is lost in a “no data zone” unreachable by DSPs and SSPs, where only context or first party data solutions can deliver results. Others are pushing solutions that replicate the capabilities of cookie-based targeting — perhaps too closely.

In this fragmented ecosystem, it feels as if data is both everywhere and nowhere. Many brands are sitting on more data than they know what to do with, but it’s locked away in disconnected silos or spread across multiple partners. Meanwhile, platforms with actionable data guard it closely, hoping to monetise their exclusive insights and avoid the data commodification of the cookie era.

With everyone out for themselves, it’s time for brands to look inwards and build independent and enduring advertising equity. But first, let’s get a lie of the land.


“Hedged gardens” are keeping audience data under lock and key

Advertisers have long lamented having to navigate Google and Meta’s “walled gardens” and inscrutable black box models, but the post-GDPR goldrush for first-party data has turned many brands and media owners into mini-walled gardens themselves — let’s call them “hedged gardens.” The first-party data these hedged gardens encircle can be activated for customer retention, user experience, and re-marketing, but without paths connecting beyond the “hedge,” its scale is limited to internal uses.

Tools such as clean rooms and identifiers can help to lay these paths and expand audiences beyond a brand’s borders, but come with many caveats. Clean rooms are too costly for many brands to adopt and require extensive groundwork to get data in order before it can be dropped in, while match rates for identifiers are still low.

Those without much first-party data of their own — such as CPG brands — must instead turn to those who do, such as retail media networks, the latest generation of walled gardens which have activated their vast stores of shopper data to open targeted advertising space within ecommerce and in-store platforms. As with any other walled garden, retail media networks are rich with addressable audiences, but dependence on them prevents brands from building advertising equity of their own.

Advertisers must also exercise caution in the post-GDPR ad tech market, where “privacy-safe,” “privacy-compliant” or “privacy-first” have quickly turned from necessary reassurances into easily tuned out buzzwords. While there have been many genuine innovations on this front, if the goal is to replicate the overbearing targeting capabilities that landed the industry in regulatory hot water in the first place, won’t we simply end up back at square one?

If the end result is that an individual can be identified without their explicit consent, then whether or not the component parts used to build their profile were “privacy-safe” becomes a purely academic distinction.

So, what we have is not a “no data zone” but an industry suffering from data noise. Data is everywhere, but advertisers struggle to make sense of it. Privacy regulations and big tech platform changes have severed the links that the industry once depended on to improve its signal-to-noise ratio. But it’s here that technology, and in particular AI, can be put to good use, bringing clarity to noise by uniting all data assets within an advertiser’s reach.

AI can orchestrate data noise into a powerful symphony

A piano or a violin may sound beautiful in isolation, but ask every musician in an orchestra to play their instrument at once and you’re left with a cacophony. The same is true of data. Many data sources are useful in isolation, but layer them on top of each other and the result is noise. What advertisers need is the technological equivalent of a conductor: a solution that can step back and harmonise disparate data sets into a unified symphony, turning noise into music.

Not long ago, such a solution wouldn’t be possible. One very talented individual may be able to conduct an orchestra, but integrating, collating, matching, and visualising the data generated across today’s complex advertising supply chain is a task that even an entire department of data scientists would struggle to complete. Even if such a feat were easily achievable, few brands or agencies would be able to justify the expense.

But today we have access to an effectively infinite supply of virtual data scientists thanks to the rapid acceleration of AI, allowing once impossible tasks to be fully automated and completed in lightning speed. This enables an entirely new breed of advertising technology: Advertising Resource Management (ARM).

Much like the finance industry’s Enterprise Resource Planning (ERP) platforms or marketers’ Customer Relationship Management (CRM) systems, ARM provides a holistic, top-down view of all advertising activity, from media planning and asset creation to campaign optimisation and performance measurement. Each platform used in a multi-channel campaign can be compared side-by-side, with the remarkable speed of the AI technology in the backend allowing in-flight adjustments to the media mix based on real-time reporting.

With all operations — and their associated data — in one place, brands can focus on building advertising equity, an enduring knowledge base of all advertising assets that is entirely owned by the brand and consistently accumulates value. This value is retained regardless of whether supply chain partners, agencies, or key staff change, allowing the brand to be more shock-proof and adaptable — essential traits for survival in today’s turbulent times.

The technology required to build advertising equity may be cutting-edge, but the approach it enables is highly traditional: study what worked and what didn’t in past campaigns, refine the strategy for the next one, then rinse and repeat. By accelerating this tried-and-true process with AI and leaving humans to focus on creativity and strategy, brands can improve campaign performance without turning to intrusive targeting, scouring the web for audience data, or becoming dependent on third parties.

No data zone? No problem. Brands already have the data they need to unlock growth, they just need the tools that allow them to make sense of it.

Pierre Naggar is director of sales, MINT.

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