Monetizing Customer Insights: Turning Data into Dollars

There are two things every business knows are important; 1) knowing that your customer is king, and 2) knowing your customer—but knowing is only just step one. The real magic happens when you act on that knowledge. In a digital-first Foodservice landscape, manufacturers and distributors alike sit on a goldmine of customer insights. The challenge is in figuring out how to actually turn that information into revenue.

The good news is that customer insights can be monetized collaboratively. When manufacturers and distributors use their data to serve the end buyer better, everyone wins. Here’s how.

1. Let the Data Guide Your Product Strategy

Customer insights don’t just tell you what was sold. They tell you what’s missing. When distributors track frequent search terms with no results, or manufacturers notice repeated requests for product variations, that’s real-world demand knocking. For instance, Distributors can spot trends across accounts, like rising demand for plant-based or allergen-free products. Sharing that info upstream can spark new SKUs from manufacturers—and generate more sales for both parties.

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How Frito-Lay (Lay’s) leverages customer data to launch new snack products

Lay’s relies heavily on data analytics—tracking sales, engagement, and digital behavior—to uncover evolving consumer preferences. They interpret these numbers through a cultural lens, ensuring insights aren’t just quantitative but contextually rich. Their global culinary teams combine this analytics approach with on‑the‑ground insights, capturing trends like flavor preferences, texture cravings, and local dining habits. This enables targeted development of flavors (e.g. cucumber & seaweed in China, Magic Masala regional variants in India/Pakistan) tailored to local tastes.

Lay’s embraces digital tools—social listening, AI, and interactive apps—to refine product development and promotional strategies. They use social media monitoring to capture emerging preferences and cultural moments, and AI‑powered tools help “decode” these insights for new launches. Their loyalty‑program app incorporates quizzes and games to collect first‑party data, letting them offer personalized upsells and refine product offerings based on behavior.

On‑ground activation is another key strategy. Lay’s “Do Us a Flavor” crowdsources local flavor ideas, turning customer suggestions into products (like Wasabi Ginger in Japan) and generating engagement. They also roll out limited‑edition, occasion‑based or regionally inspired products—such as “@ Home” family‑size packs during lockdowns in India, and wafer‑style chips for South Indian meals—grounded in consumer context data. Campaigns link data collection, product innovation, and cultural resonance seamlessly.

Key ways Lay’s uses customer data to launch new products:

• Trend identification: Regional sales and engagement analytics drive flavor and format decisions (e.g. local spices, textures).

• Social listening & AI: Real-time insights from social platforms guide limited‑edition launches and marketing hooks.

• Loyalty app & quizzes: First‑party data enables personalized product assortments and targeted promotions.

• Crowdsourced innovation: Consumer‑driven campaigns generate product ideas and strong brand affiliation.

• Occasion‑based adaptation: Data on usage moments (e.g. at‑home snacking) informs pack sizing and positioning.

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2. Use Insights to Segment (and Serve) Better

Not every customer is created equal—and data can help you tailor your approach accordingly.

Manufacturers and distributors can use purchase history, order frequency, and even cart abandonment patterns to segment customers. For example, operators that consistently buy premium ingredients may be more interested in upsells, chef demos, or recipe bundles. On the other side, price-sensitive buyers might engage more with promotions, discounts or bulk deals.

Sysco, the largest foodservice distributor in North America, is a prime example. Sysco segments its customers on geographical, industry, size, purchasing behaviour and demographic data. This allows them to run tailored programmes like ‘Culinary Connect’, targeting their customers who are chefs and culinary professionals. Their use of customer segmentation has enabled them to offer tailored promotions and suggest complementary products, driving larger order sizes and increased loyalty.

For manufacturers, knowing which segment each distributor is serving allows for co-branded campaigns, personalized marketing, and product development that actually resonates.

3. Power Up Your Promotions

Customer insights can take the guesswork out of marketing—and help you stop wasting time and budget on what doesn’t work.

Distributors, for example, can analyze order cycles to time promotions more effectively. If data shows that independent restaurants stock up on condiments every six weeks, manufacturers can align their promo calendars to offer discounts or incentives just ahead of that cycle.

It’s not just timing, either—it’s targeting. Kraft Heinz used e-commerce data and AI to optimize their promotions in the retail space, boosting their ROI significantly. The same logic applies in B2B. Use data to tailor promotions by region, cuisine type, or purchasing behavior, and your conversion rates will thank you.

4. Inform Smarter Sales Conversations

Sales teams—on both the distributor and manufacturer side—are most powerful when armed with insight. Imagine a rep walking into a customer meeting already knowing:

• What the customer orders regularly (and what they stopped ordering)

• How often they buy (and when they’re due to reorder)

• What similar customers are buying that they’re not

That’s not sales anymore—that’s consulting.

PepsiCo, the food and beverage giant (who also owns Frito-Lays), has been using AI-powered sales tools that recommend specific products to sales reps based on outlet type and local demand patterns. It’s a model that can easily apply to Foodservice distribution, enabling smarter pitches that drive revenue and strengthen relationships.

5. Enable Predictive Inventory and Smarter Merchandising

If you know what customers will buy, you can stock smarter—and sell faster.

By analyzing customer data, distributors can reduce waste, avoid out-of-stocks, and better forecast seasonal spikes. For example, if taco-related SKUs always spike in the first week of May (hello, Cinco de Mayo), you can plan ahead. But it goes deeper—predictive insights can also inform which products to feature on your homepage, bundle together, or push through a limited-time offer.

Some B2B platforms now offer AI-driven product recommendations based on purchasing trends, helping both sides optimize merchandising. 

Final Thoughts

Insights are a shared asset. Too often, customer data stays siloed—trapped in individual CRMs or locked behind separate platforms. But monetizing insights doesn’t have to mean guarding them. In fact, there’s more to gain by pooling knowledge. Distributors have the frontline visibility. Manufacturers have the R&D and product development muscle. Together, they can act on what customers want faster and more effectively.

Start small: share anonymized trend data, coordinate on joint promotions, or co-invest in tools that surface the right insights at the right time. Because when you put customer insights to work—not just for one part of the chain, but across it—you don’t just sell more. You sell smarter.