RetSKU is a proprietary, real-time data aggregator, integrator &
insight provider of CPG data. Our data/platform is used to get a good
understanding of a category, research on who the winners/losers are in
a category, identify M&A targets, sell/short a stock, as well as understand why sales are going up / down.

For the entire category, we track and provided the following
proprietary data for both online and brick-and-mortar / in-store:
- Assortment (share of shelf, new SKUs added/removed)
- Distribution (how many stores SKU sold at each retailer), what % of
coverage does a brand have vs another
- Pricing (daily changes, differentiated pricing for Brand / SKU
across retailers)
- Promotions (who’s promoting more - weeks, % off - to gain sales),
including in-store temporary price cuts
- Online reviews

We typically partner with Nielsen, IRI or NPD to get in-store retail
sales for competitors and integrate that data with the above
proprietary data that we provide.

Our data can thus abl...
RetSKU is a proprietary, real-time data aggregator, integrator &
insight provider of CPG data. Our data/platform is used to get a good
understanding of a category, research on who the winners/losers are in
a category, identify M&A targets, sell/short a stock, as well as understand why sales are going up / down.

For the entire category, we track and provided the following
proprietary data for both online and brick-and-mortar / in-store:
- Assortment (share of shelf, new SKUs added/removed)
- Distribution (how many stores SKU sold at each retailer), what % of
coverage does a brand have vs another
- Pricing (daily changes, differentiated pricing for Brand / SKU
across retailers)
- Promotions (who’s promoting more - weeks, % off - to gain sales),
including in-store temporary price cuts
- Online reviews

We typically partner with Nielsen, IRI or NPD to get in-store retail
sales for competitors and integrate that data with the above
proprietary data that we provide.

Our data can thus able to provide actionable insights like:
- Projected revenue for each brand based on increase/decrease in
assortment and distribution across retailers
- Projected revenue based on user sentiment derived from online
reviews / comments and ratings
- Projected margin based on change in promotional cadence, depth of
discount and duration
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