How Reynolds Lifted Its Innovation Pipeline 40% in 8 Weeks

Reynolds had years of consumer research in scattered studies and reports. An AI research system read 174,000 reviews against it, surfacing four new growth territories and 11+ product concepts.

40%

Lifted the innovation pipeline

4–8 weeks

Implementation Time

$250K – $500K

Project Cost
the challenge
Reynolds Consumer Products wanted a stronger pipeline of meaningful, consumer-led innovation, but its research was fragmented across consumer studies, market reports, product reviews, social conversations, sales data and internal strategic priorities. The problem was not a shortage of information. It was knowing which signals mattered, how they connected, and where Reynolds had credible room to grow beyond its familiar product categories as consumers' cooking and household habits changed.
what they built
Starday used its proprietary AI-enabled research and decision system to combine Reynolds' internal research and performance data with about 174,000 product reviews, more than 50,000 social posts, consumer segmentation, category research and competitive intelligence. Its team organized the evidence around the needs, frustrations and behaviors shaping how people cook, prepare meals, store food and manage their homes, and used it to answer a sequence of business questions. The output was four opportunity territories across the cooking journey and 11+ product concepts, each with consumer evidence, competitive context, strategic rationale and product requirements.
Reynolds Consumer Products wanted more consumer-led innovation, but its evidence was spread across consumer studies, market reports, product reviews, social conversation, sales data and internal strategy documents. Starday combined that internal knowledge with a large body of external evidence, about 174,000 product reviews and more than 50,000 social posts plus segmentation, category research and competitive intelligence, and used its proprietary AI system to ingest, organize and analyze it. Instead of producing a long list of ideas, the team worked through a fixed sequence of questions: where consumer behavior was changing, which needs were meaningful but poorly served, where Reynolds had the credibility to compete, which openings could support large and differentiated products, and what Reynolds would need to build to win. That work produced four opportunity territories spanning the whole cooking journey rather than only Reynolds' existing categories, and 11+ product concepts, each carrying its consumer evidence, competitive context, strategic rationale and product requirements. The deliverable was a growth strategy and a concept pipeline rather than a tool. Reynolds' CEO took up the broader territory, which helped shape an "Own the Kitchen" strategic direction.
best fit for
Large consumer-products companies with substantial consumer, market and internal data but no consistent way to connect those inputs to innovation decisions. Particularly relevant for teams that need to identify new growth spaces, fill long-term pipeline gaps, or evaluate where to place high-cost product bets.
Ai ROLE
Starday's proprietary technology ingested, organized and analyzed large volumes of consumer, market, competitive and internal business data. Innovation experts then interpreted the evidence, identified growth opportunities and translated them into product concepts.
impact

45% of pipeline ideas came from this work

Only 10 to 15% overlap with concepts from another strategy partner

40% expansion of the innovation pipeline

More ideas in Reynolds' pipeline, and a more differentiated set to advance

A broader strategic growth platform

The CEO took up the full cooking journey as territory, helping shape an "Own the Kitchen" direction
implementation complexity
Medium, editorial call: the AI system is Starday's existing platform, so no custom build for Reynolds, but the work fused large internal and external data sets and ran on an eight-week strategy timeline with leadership involvement.

Chaz Flexman

CEO & Co-Founder @ Starday
Starday Foods
CEO and Co-Founder of Starday, whose AI-enabled research and decision system helps consumer-products companies find evidence-backed growth opportunities and product concepts.
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Talk to this team
industry
Consumer Goods & CPG
business organization
Executive & Strategy
Product & Engineering
Marketing
AI TYpe
Data Synthesis & Reporting
Natural Language Processing
Decision Support & Scoring
value type
Revenue Growth
frequently asked questions
How did Reynolds grow its innovation pipeline 40% with AI-driven consumer research?
Reynolds Consumer Products combined its internal research and performance data with about 174,000 product reviews and more than 50,000 social posts, analyzed with an AI research system. The experts used the evidence to find four new growth territories and 11+ product concepts, which expanded the company's innovation pipeline by 40% in eight weeks.
What AI tools and approach were used?
A proprietary AI-enabled research and decision system that ingests, organizes and analyzes consumer, market, competitive and internal business data. Innovation specialists then interpreted the evidence and turned it into commercially viable product concepts.
What results did Reynolds achieve?
A 40% larger innovation pipeline, four evidence-backed growth territories, and 11+ product concepts. 45% of the ideas in the combined pipeline came from this work, with only 10 to 15% overlap with another strategy partner, and the broader territory helped shape an "Own the Kitchen" strategic direction.
How long did the engagement take?
About eight weeks.
Who is this AI consumer research approach best for?
Large consumer-products companies with plenty of consumer, market and internal data but no consistent way to connect it to innovation decisions, especially teams filling long-term pipeline gaps or weighing high-cost product bets.

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