case study

Hyper-local, Shareable Data to
Inform Price Changes

The Client

Leading American Multinational Producer
of Breakfast Cereals

The Situation

Cereal is an $8.5B category in the US and managing product-level price advances across the retail partner landscape has become one of the most important ways for manufacturers to combat pandemic profit challenges. Taking a price increase on brands that generate 100s of millions of dollars with retailers who are also managing through a 40-year high inflationary period with their consumers, isn’t an easy job.

Market Conditions

Food manufacturers are facing a combination of challenges including rising energy costs, commodity price increases, supply chain, and labor shortages. These headwinds, left unchecked, would force large manufacturers to absorb the impacts and suffer erosion across the business.

Key Challenge

In a highly competitive shopper climate, many retailers take a “wait and see” approach to everyday price changes. They rely heavily on intel gathered from their field teams and traditional syndicated, POS data. Delays in the adoption of prices has previously caused key retail partners to revert to original pricing, erasing any planned gains.

Solution

Having implemented a market-wide price change on the entire portfolio of cereals in Jan 2022, this manufacturer identified a singularly critical element of executing that increase. They focused on monitoring a critical price threshold on high turning brands in an important size portfolio across the most competitive retailers in Grocery. The goal was to validate if any of those retailers had decided to pass that price increase through to their shopper base.

AHA! Insight

Datasembly’s real-time hyper-local data allowed the large cereal manufacturer to validate within weeks that key items were getting significant pricing moves across a broad-base of stores and geographies/ markets, and more importantly, could share this information with other key retailers in the US. The ability to share real-time information across retailers validated that the market had moved and provided the confidence needed to ensure their partners that the new prices would hold. These changes allowed retailers to move faster, resulting in +500k in total sales gains in the first 10 weeks from key retailers with projected sales gain of $2.7M for just the 2 retailers who moved on price 8-10 weeks faster then rest of market.

Datasembly app image showcasing retail data collection