From Insights to Shelf Space – Using Retail Data to Accelerate CPG Innovation

Ready to turn insights into revenue? This post shows how CPG brands use Bedrock Analytics to uncover white space, track competitors, and build retailer-ready strategies that win shelf space – and drive sales growth faster. Bedrock isn’t just for reporting what already happened, it’s also a powerful tool for planning & creating innovation in CPG. Here’s how:

1. Identifying White Space & Category Gaps

Bedrock harmonizes NielsenIQ, SPINS, Circana, and retailer portal data into a unified view. By slicing this across subcategories, pack sizes, and claim attributes (organic, plant-based, functional, etc.), brands can spot:

• Under-penetrated consumer segments (e.g., “plant-based snacking is 8% of total snack sales, but only 2% of our portfolio”).
• Emerging attributes trending faster than the category.
• Retailer voids where competitors have presence but your brand doesn’t.

This becomes the foundation for deciding where to innovate (e.g., new flavor extensions, new pack formats, functional benefits).

2. Benchmarking Competitor Innovations

Using Bedrock’s dashboards, a CPG team can track how new item launches from competitors perform:

• Distribution build-out (how fast they win new doors).
• Velocity benchmarks (are consumers actually picking them up?).
• Price positioning relative to the category.

This allows innovation teams to see what’s working and what’s failing in near-real time, derisking their own pipeline.

3. Building the Business Case for Innovation

Bedrock automatically creates retailer-ready PowerPoint decks that show:

• Market opportunity sizing.
• Trend growth rates.
• Consumer demand drivers.
• Incrementality potential (how much new sales an item will add vs. cannibalize).

This makes it easier for brand managers to secure internal buy-in and for sales teams to pitch innovation to buyers.

4. Testing & Iterating Pre-Launch

With harmonized POS + retail portal data, Bedrock can help brands run “test and learn” pilots:

• Launch a few SKUs in select retailers.
• Track performance in Bedrock dashboards (velocity, repeat, household penetration).
• Compare to category benchmarks and adjust formulas, pack sizes, or pricing before scaling nationally.

5. AI-Driven Insights for Faster Innovation

Bedrock’s AI insights layer automatically flags patterns like:

• “Low-sugar beverages grew +28% YoY, outpacing category growth by 3x.”
• “4-packs are declining, while 8-packs are gaining share in club channels.”
• “New distribution in Publix drove +$2.4M incremental sales for competitors in your segment.”

Instead of combing through data manually, innovation teams can let AI surface the opportunities.

Takeaway: Bedrock turns raw retail data into actionable innovation roadmaps – from spotting consumer demand shifts, to validating white space, to building buyer decks that secure shelf space. It shortens the cycle between insight → idea → launch → proof of success.