How Smart CPG Leaders Are Mastering AI Consumer Intelligence to Drive Growth

EXECUTIVE SUMMARY: Consumer relevance begins with superior listening. The evidence shows that success belongs to those who can hear consumer needs before consumers fully voice them, precisely the capability that separates market leaders from market followers in every category.

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Consumer behavior now shifts faster than quarterly reports can capture it, leaving CPG executives facing an uncomfortable truth.

Traditional market research methods are failing to keep pace with the speed of consumer evolution. Recent Bain surveys reveal a striking disparity: 84% of executives in other non-tech industries count generative AI among their top five priorities, while only 37% of CPG executives share this conviction.

This hesitation emerges at a critical moment when the primary challenges for 2025 include increased competition for shoppers, decreased consumer spending, and intensified pressure from retailers.

The companies that are listening smarter through AI aren’t just gaining operational efficiencies — they’re rebuilding the fundamental connection between brand and consumer that drives sustainable relevance.

Having been a beta tester for ChatGPT and now working daily with AI-powered solutions across my consulting practice, I’ve witnessed firsthand the evolution from experimental novelty to essential consumer intelligence capability.

The companies I advise that have embraced sophisticated AI-enabled listening are consistently outperforming those still relying on conventional research methods to understand their rapidly changing consumers.

The Relevance Crisis: When Consumer Insights Lag Behind Consumer Reality

The data reveals a sobering disconnect between CPG brands and their consumers. Only 7% of US online shoppers are members of a CPG brand’s loyalty program, compared to the vast majority enrolled in retailer programs. This gap signals more than a marketing challenge—it represents a fundamental breakdown in consumer understanding and connection.

Consider the stark reality facing today’s CPG leaders: consumers have definitively rejected the price-increase playbook that sustained growth through 2023.

As Bain & Company’s research demonstrates, consumers are now switching to private-label brands, waiting for promotions, or simply buying less when faced with price hikes that offer no additional value.

Conventional consumer research, with its quarterly cycles and retrospective analysis, cannot capture these sentiment shifts quickly enough to inform real-time strategy adjustments.

Meanwhile, consumer behavior complexity has reached unprecedented levels. McKinsey’s analysis shows notable disparities between income segments, with older, high-income consumers driving discretionary spending while price-sensitive segments increasingly scrutinize every purchase decision.

The traditional demographic and psychographic segmentation models that guided CPG strategy for decades now feel woefully inadequate.

The AI Listening Revolution: From Data Collection to Consumer Understanding

The most sophisticated CPG companies are discovering that AI’s true power lies not in automating existing research processes, but in fundamentally reimagining how brands listen to and understand consumers.

Procter & Gamble’s groundbreaking collaboration with Harvard Business School provides compelling evidence of this transformation.

In their comprehensive study involving 776 employees across commercial and R&D functions, P&G found that teams leveraging AI-powered consumer insight generation worked 12% faster than traditional research teams.

More significantly, these AI-augmented teams developed more balanced solutions that better reflected diverse consumer needs, regardless

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Why Smart CPG Leaders Are Rethinking Their AI Strategy to Maximise Consumer Insight Value

Have you noticed how every technology vendor, consultant, and industry publication is telling you that your AI Strategy is the solution to all your business challenges?


The pressure to invest heavily in AI capabilities has never been greater for CPG executives.

Yet many leadership teams ask a fundamental question: How do we separate genuine opportunities from expensive distractions?

This question becomes particularly challenging when it comes to customer understanding.

While an effective AI strategy promises unprecedented insights into consumer behaviour, the path from investment to measurable business impact remains unclear for many leadership teams.

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The Reality of AI Strategy Investment in CPG Today

Let’s start with some sobering numbers.
According to McKinsey’s recent analysis, while 70% of CPG companies are implementing some form of AI initiative, only 22% report significant business impact from these investments.
The disconnect between implementation and value creation isn’t surprising when you consider that many companies approach AI as a technology solution rather than a business transformation.

The executives I work with often share a common frustration: they’ve invested millions in AI platforms and data lakes, yet still struggle to generate actionable customer insights that drive revenue growth.
One global beverage company CIO recently confided,

”We have more data than ever, but less clarity on what our customers actually want.”

This disconnect exists because technology alone can’t create customer understanding.
The most sophisticated AI systems are only as valuable as the business questions they’re designed to answer and the actions they enable.

Building a Strategic Framework for AI Investment

When working with CPG leadership teams, I’ve found that successful AI strategies share a common foundation: they start with strategic business objectives rather than technological capabilities.

Rather than asking “How can we implement AI?” successful executives ask:

  1. Which customer-related business challenges, if solved, would create substantial value?
  2. Where are our current gaps in customer understanding creating barriers to growth?
  3. How might AI-generated insights enable better strategic decision-making?

This approach shifts the focus from technological implementation to business transformation. This is a subtle but critical distinction that separates high-ROI investments from expensive experiments.

Consider how Miyoko’s Creamery approached this challenge.
As a pioneer in plant-based dairy alternatives, they faced the dual challenge of understanding both their core vegan consumers and the much larger segment of flexitarians they needed to attract for mainstream growth.
Rather than broadly implementing AI across their organization, they identified specific high-value decision points where enhanced customer understanding would drive measurable business outcomes.

They focused initially on product formulation and messaging optimization, using AI to analyze consumer sentiment around taste, texture, and functionality in both their owned channels and broader food conversations.
Their system identified that “performance” messaging (how the product melts, stretches, etc.) resonated more strongly with flexitarians than sustainability or ethical messaging.

According to Miyoko’s Series C funding announcement, this targeted approach helped them reformulate their flagship products and reframe their marketing to emphasize culinary performance. This delivered a 40% increase in repeat purchase rates among … Click to continue reading

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