Taking a Bite Out of Promotions in Biscuits

At Middlegame, we support Revenue Growth Management using a proven process—designed by marketing science pioneers and driven by proprietary algorithms.

We identify the products shoppers WANT, the merchandising interrupts that stimulate INTEREST and the prices shoppers are willing to PAY. We help you:

Rationalize products—What items are best to drop and add to generate the most incrementality?
Reallocate merchandising—What support produces the greatest portfolio lift?
Adjust pricing—Which decreases or increases offer the best win-win plan to take to retailers?

Our platform handles both direct price change or indirect price change, based on downsizing or special packs.

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WE EXPAND YOUR TESTING CAPABILITIES

Our goal is to help you "do better things" through Revenue Growth Management and not just "do things better."

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The Middlegame platform can evaluate hypotheses in all areas, including:

Shifting (doing something you currently do differently)
Imitating
Line-filling
Innovating

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WE TAKE PROVEN METHODOLOGY

AND MAKE IT PRACTICAL TO YOUR SITUATION

We use a modified version of the "multinomial logit" model originally developed for household panel analytics.

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But we closely tie it to the statistical engine behind conjoint analysis. The same math that predicts respondent choices of “no” or “yes” can predict market shares between 0% and 100%.

For a detailed paper on our exact methodology, download our whitepaper.

Download Our Whitepaper

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WE TAP INTO IMMEDIATELY AVAILABLE DATA

FOR FAST RESULTS

Instead of fielding a survey, you can immediately begin to see potential solutions as we apply the Middlegame platform to any sales data.

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The process is proven for both audit and scanning channels, as well as internal shipments.
The core data requirements are product-level volume sales, distribution, price and potential merchandising conditions as well as the product characteristics or attributes.
Our ETL procedures can integrate additional information into the analysis, including:

- SKU margins or other financial information
- Competitive media activity
- Survey research with shopper opinions and attitudes
- Environmental factors