Home Data-Driven Thinking AI In Q4: What Worked, What Didn’t And What’s Next

AI In Q4: What Worked, What Didn’t And What’s Next

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Chris O’Neill, CEO, GrowthLoop

AI-driven content and personalization are no longer just an advantage; they’re a necessity. 

According to a recent Bain survey, top retailers achieved a 10% to 25% lift in return on ad spend through AI-powered, targeted campaigns during this past holiday shopping season. And AI’s rate of progress, particularly among industry giants like Google and Amazon, is nothing short of astonishing.

But not every retailer has a solid handle on this emerging tech. While some thrived, others stumbled – sometimes spectacularly. 

The lesson? Success comes not just from adopting AI but from doing so with strategy, transparency and a human-centered approach.

The good: AI success stories

Through a data partnership with Adobe, Ulta Beauty created a real-time personalization engine that integrates in-store and online experiences seamlessly. This approach helped grow its loyalty program, UB Rewards, while driving deeper engagement and increased spend among customers.

The key to Ulta’s success wasn’t just the technology but its thoughtful data strategy. Personalization wasn’t forced; it was rooted in customer insights and designed to deliver meaningful, relevant experiences. AI works best when it’s a tool for amplifying what retailers already do well, not a shortcut for creativity or connection.

The bad: AI missteps

Spotify’s 2024 “Wrapped” campaign, meanwhile, became a cautionary tale. By going all in on AI-generated features and stripping away fan favorites like top genres, Spotify alienated its core audience. What should’ve been a celebration of personalized music listening felt impersonal and overly engineered, leading to widespread backlash.

Don’t use AI just because you can. Consumers value authenticity and relevance over novelty. When AI feels disconnected from the brand or the audience, it risks becoming a liability instead of an asset.

The ugly: ethical and operational challenges

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AI’s potential to enhance brand storytelling came under scrutiny with Coca-Cola’s attempt at an AI-generated holiday ad. Instead of delighting audiences, the campaign was deemed “soulless” and lacking the warmth that has defined Coca-Cola’s most iconic campaigns. 

The backlash highlighted a deeper issue: brands using AI without “permission.”

Permission, in this context, isn’t just about data usage; it’s about the implicit agreement between a brand and its audience. Customers grant permission to personalize their experience, to innovate and even to experiment, but only within the boundaries of trust and respect.  

Coca-Cola’s misstep wasn’t just an issue of creative execution; it was a breach of the unspoken contract it had created with generations of consumers who expect authentic emotional connection and adherence to tradition from the brand.

This trust-permission dynamic extends far beyond brand identity. AI systems rely heavily on customer data. But data alone is insufficient for achieving effective results. 

Transparency is also critical. Consumers must understand how their data is collected, used and protected. Without clear communication and well-defined boundaries, even the most sophisticated AI-driven campaigns risk alienating the very audiences they aim to serve.

Balancing innovation and permission isn’t just about avoiding backlash; it’s about building lasting relationships. Brands that stray outside of what customers expect risk undermining that trust, which takes years to establish and moments to lose.

Tips for using AI in 2025 and beyond

How can brands avoid these pitfalls while unlocking AI’s potential? Here are three strategies:

Keep humans in the loop: AI isn’t a substitute for human oversight. Creative teams should review and refine AI-generated outputs to ensure they align with brand values and resonate with consumers.

Embrace holistic, compounding data strategies: Success in AI isn’t just about more data; it’s about the right data and continuous learning. Retailers need a complete view of the customer journey, from email engagement to in-store purchases. They must use AI that optimizes each campaign, learning from past wins to make smarter, more personalized recommendations. This compounding intelligence not only enhances customer experiences but also drives efficient, scalable ROI for retail brands.

Earn and respect permission: AI-driven campaigns must start by understanding the permission consumers grant to brands. Innovation should respect these boundaries, building trust by offering value and relevance without overstepping or feeling intrusive.

Retailers must balance innovation with authenticity and intentionality if they are going to win in the AI-powered future.

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Follow GrowthLoop and AdExchanger on LinkedIn. 

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