For all the talk of AI and its opportunities and challenges for marketers, let’s look at it from a different starting point.
AI is an existential threat to brands
Why? Because AI's superpower is to raise the floor of quality across every dimension, which means that brands will become less different from each other. And meaningful difference is what brand-building is all about. Difference is being perceived as different from others in your category, and substitutable for other, lesser brands. Meaning ensures your brand meets functional and emotional needs. And to grow, brands need to be meaningfully different to more people.
Our Blueprint for Brand Growth shows that brands that are perceived to be meaningfully different have a 5x higher chance of penetration growth today and double their chances of growth in the next few years.
However, these measures are relative to what other brands are doing; marketers need to make sure their brands remain meaningful and different. But with Gen AI, everyone can move at pace to compete. What if your brand’s relative difference is countered at lightning speed by competitors using Gen AI? Or they fine-tune their and emotional resonance on the fly, to appeal to more people?
Moving towards parity is already an issue for brands. It is the inevitable result of category maturity. As one brand finds the optimal way to do something, all brands will do the same (because it's optimal), thereby making all brands sloosh around in a sea of sameness. Our colleague J. Walker Smith recently wrote about a similar topic, the paradox of quality, here.
So what can AI do?
AI could take the guesswork out of difference, pointing all brands in the same direction. Using AI to develop your brand strategy, in the absence of very specific brand and category data, will result in a sea of sameness.
As brands and businesses use AI to synthesize large datasets, without brand-specific data, AI will distil all learning and point directly to consensus knowledge about the best thing to do. But with the right brand-focused data, it can deliver reliable and sustainable insights to create and deliver meaning and difference.
One pre-requisite for marketers is better knowledge. But that's not necessarily enough. It's an easy competitive gap to close (hire better researchers; buy better databases).
Another answer is speed of differentiation. But too much variability and updating of difference, using trained AI models, could prove confusing and detrimental to brand perceptions and the well-known and well-proven desirability of consistency.
The better answer lies in rebalancing brand propositions. Meaningful Difference is, essentially, a brand's proposition – two components that come together, and drive a brand’s pricing power. As AI puts the squeeze on difference, meaning becomes more important.
Gen AI is the missing ingredient for the long-pursued ambition of true personalization to amplify meaning and difference. The main barrier has always been aggregating, calculating and configuring personalization, or even customization in a truly personal way, and in real-time. AI can aggregate, calculate and configure like nobody's business – for example, reformulating existing products or services to better align with consumer demands and expectations.
Becoming a brand grandmaster
So instead of worrying about the threat, brand marketers need to behave like a chess grandmaster, constantly thinking ahead.
- Thinking three moves ahead: successful brands invest in AI tools to predict consumer behavior, identify emerging trends, and understand new opportunities. They ask themselves, "How can AI support me in better understanding my audience and predisposing more people to my brand?"
- Playing Their Own Game: Brands that thrive are those that understand their meaningful difference and leverage AI to consistently reinforce this unique positioning. These brands continuously refine their own unique data, their messaging and delivery. “How can AI help me to conceive of fresh yet familiar brand exposures and experiences that keep my consumers engaged and loyal?”
- Embracing Agility: the fast-paced marketing environment requires quick thinking and adaptability, while remaining true to the brand. “How can we use AI to make data-driven decisions swiftly, respond proactively to market changes, and seize emerging opportunities with confidence?”
Of course, once a brand’s strategy for being meaningfully different to more people is understood and tracked, marketers also need to activate well using AI. We’ll cover that in future pieces.
Conclusion
Successful brands are using the power of AI across the marketing cycle by thinking several steps ahead, staying true to their meaningful difference and remaining agile, ensuring that the potential threat of AI turns into an opportunity.
Find out more about Kantar’s Meaningful Different and Salient (MDS) framework and how brands can use MDS to connect more in a meaningful way with customers and create value for their brands and businesses. Learn more here.