Iconic brands produce disproportionate growth because they have strong, even unassailable bias in their favour even before consumers enter the market. Icons convert from bias to purchase more often than their peers, a strong defence against competitor tactics, price differences, downturns and new category entrants. Strong brands grow faster and are more valuable.

To build that strength of brand equity, you must know how to build presence and perception among your total addressable market, including potential future buyers.

For decades, iconic brands have relied on projecting claimed behaviours from smaller sample surveys and focus groups onto the total population. This enabled marketers to build media plans to connect with audiences, working well across a limited number of mass channels and monoculture society. Then came the internet, increased media fragmentation, a new communications economy and the era of 'big data,' where ID-based solutions – powered by cookies and device IDs – promised unparalleled personalisation and precision for advertisers, an approach not entirely accepted by consumers.

However, while IDs provided a currency for effective people-based marketing between brands and their known customers, to become or remain icons, they can’t simply rely on these existing customers or on the immediate in-market signals (e.g. clicks, likes, views) provided by ID-based solutions as a predictor of future growth. Marketing investment has a tougher job in a world where media is everywhere and everything, tasked with maximising the value of current customers whilst also consistently penetrating and converting new ones. But, reaching everyone continuously, especially in this fragmented modern media environment, is not a viable, cost-effective strategy either, especially in intermediated, low-margin sectors like CPG.

To add to the challenge, identity solutions are providing an increasingly narrow view of addressable media, thanks to growing consumer concerns regarding data privacy and corresponding government regulation. The walled gardens are also tightening control of valuable consumer data, making it more challenging to have a centralised view of all relevant data. The reality for iconic brands is they are operating within the confines of an ecosystem that’s never quite been able to deliver on the promise it’s been constructed against. Gaming, podcasts, TV, social, influencers, immersive OOH and in-store experiences – it would be malpractice to not include these channels on a media plan today. Yet, all these channels remain largely invisible to third-party ID solutions.

The inevitability of rethinking data: the era of AI

Thanks to advancements in AI, we can uncover the new recipe for growth. The world’s biggest brands need to pause and rethink their data strategies if they are to retain their icon status and not be eclipsed by challengers who will skip the legacy systems and dive straight into modern approaches.

The move away from ID-based solutions stems from two compounding challenges, exacerbated by the heightened privacy risk of solutions still too often reliant on moving data into closed systems and syndicating PII (personally identifiable information) across the media ecosystem:

1. Declining match rates: ID solutions can only learn from the data between parties that can be matched to an ID. But as consumers increasingly opt out of sharing PII, match rates are plummeting – especially among younger and more diverse consumers essential for long-term growth. This creates a major hurdle for traditional ID-based marketing. If your matched audience doesn’t reflect your target audience, your campaigns risk missing valuable consumers entirely.
2. Shrinking inventory: ID solutions can only value and act on impressions in the open web that carry a matching ID. Privacy regulation, browser policies, cookie deprecation and platform fragmentation are reducing the volume of inventory available that meet that requirement. Today, nearly two-thirds of open web impressions are invisible to ID solutions. With global ad spend shifting toward walled gardens and emerging 'hedged gardens' like retail media networks, the pool of matchable impressions continues to shrink – forecasted to represent less than 2% of total global media spend by 2024 (source: GroupM This Year, Next Year).

Beyond IDs: unlocking smarter intelligence with AI

AI’s effectiveness depends on the data it’s trained on – and while quality is critical, so is quantity. AI models reliant on ID-based data alone are inherently limited, as this data type is both narrow and increasingly unreliable. More powerful is AI trained on all the valuable data signal brands can access in a privacy-safe manner. Beyond identity and consumer data, this could mean business, campaign, supply chain, retail sales and web engagement signals – even if not matchable to an ID. All these data points hold value and will deliver more intelligent AI models than models limited to customer records with matching IDs. We can use all the data available between parties to train models and apply all that intelligence to all inventory. This means reclaiming reach, much of it uncontested for brands as it makes available valuable inventory not visible to ID solutions, and increasing effectiveness as identity signals erode.

Why could this make such an impact on legacy brands like brand icons? They sit on decades worth of data, most of which might not have been actionable before these new approaches became viable. They are in the position to invest in the long-term future of their companies and build their own data ecosystems that can enrich AI models to deliver better campaigns. By embracing AI and building intelligence beyond IDs, legacy brands can future-proof their strategies and cement their iconic status in the next era of marketing.

How brands can take action today

So, how can brands begin rethinking their data strategies? Here’s are 3 ways to get started:

Connect

Start by prioritising control over your data. As regulations grow stricter, sharing data with third parties introduces unnecessary risks. No single party will be able to centralise all the valuable data in one place. Instead, leverage privacy-first solutions like WPP’s InfoSum, which allow you to connect your data with other data owners in a secure, privacy-compliant way – creating uncommon collaborations that yield unique, ownable insights.

Collaborate

Once you have established connections to access the most valuable data signals to meet your goals, apply AI data techniques to maximise the intelligence that can be derived from across these signals. Techniques like federated learning, which learn and build knowledge by training models across a decentralised network of multiple sources without exchanging raw data, allow us to find connections that fuel growth opportunities that no single database could see – all whilst further enhancing data privacy and security.

Validate

Finally – test the AI-powered data strategies created on your campaigns. Anchor tests in key business performance outcomes, not just vanity ‘media metrics’ that could appear skewed given the different inputs into these strategies. Unlike identity solutions, which rely on batched data appends that can slow the speed to insight, AI data models are dynamic and continuously updated. This means, that as more data is fed in, the foundational model will learn what generates your desired campaign outcome and improve over time, delivering better results.