Case Studies

Current Engagements

Just a few of the organizations we have worked with to grow business through better decisions.

CPG Use Case

Opportunity identification.


Company X wanted a viewpoint on category trends over the next 2 years. Using a combination of company sales and KPI data – along with market, demographic, climate and census data from the last 5 years – we ran our engine to determine the best predictive forecast per category.


We then back-tested the top models to see how closely the models would have predicted events over the last 5 years. This included testing against major holidays and events to understand how behavior changed.


With 2020 and 2021 markets predicted, we can now understand key behaviors, clustered geographies, and buying patterns by category. Using this forecast, we segmented the buyer types and determined how to influence them based on the trends.

Retailer Use Case

Head-to-head demand forecasting.


CW wanted to predict the impact of planning and forecasting decisions within the vitamin category to see if there was enough financial impact in changing their current approach. Leveraging product sales, allocations, and attribute data – along with demographic, climate and census data – we forecasted the optimal SKU/store/inventory combination.


Over a 4-week period, we then went head-to-head with the existing method of forecasting. We were measured based on our weighted daily average distance between our forecast and the actual results. ​​​


We were able to prove the accuracy of our engine, beating the existing process of prediction by 58%. Through this, we were able to identify a significant, multi-million dollar impact through changing this process, without even altering the upstream decisions (i.e., assortment, pricing, promo). Insite AI did all of this with only 6 days of AI modeling, and the expected accuracy will continue to improve over time.

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