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Segment
Manufacturing
Timeline
90 days
Modules used
AI Operations · AI Logistics · AI Insights

How a food manufacturer found their real market.

A South African food brand replaced quarterly panel research with daily sell-through data — and discovered demand patterns no research firm had ever surfaced.

Warehouse operations team handling inventory on a working floor
The Challenge

What wasn't working.

The manufacturer produced 18 SKUs across breakfast and snack categories, distributed through wholesalers, formal retail, and informal channels. Their sell-through visibility ended at the wholesaler dock door. They paid a research firm $180,000 a year for quarterly panel estimates that were 10 weeks delayed and only covered formal retail.

  • No visibility into informal retail sell-through — over 60% of their volume
  • Pricing decisions made on dated estimates, leaving margin on the table
  • New product launches measured on shipments, not actual consumer adoption
  • Promotional spend allocated by gut, with no measurement of ROI
The Solution

How Lumanw changed it.

The manufacturer subscribed to AI Insights and integrated their product catalogue. Within six weeks, they were receiving daily sell-through data from 3,800 retailers across the Lumanw network — formal and informal — broken down by SKU, region, and time of day.

  • Live SKU-level sell-through, refreshed daily
  • Geographic heatmaps showing where demand was unmet
  • Price elasticity analysis across regions and channels
  • Promotional ROI measured against actual sell-through, not shipments
Results

What changed.

15×
Faster insight cycles
+12%
Margin expansion
6w
To first insight
−$180K
Annual research cost
The Impact

The manufacturer used the new data to reformulate one underperforming SKU, kill another, and reposition pricing in two key regions. Within a year, they had grown category share by 3.2 percentage points — the first share gain in seven years.

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