Own catalogue and competitors' prices in one view
Pricing and assortment decisions were being made from a spreadsheet that was out of date the moment it was finished. The commercial team now acts on the data instead of assembling it.
- Sector
- E-commerce retail, Europe
- Service
- Data & Market Intelligence
- Delivered as
- Dashboard and API into the pricing workflow
- Status
- Monitored and running
An online retailer competing on price and assortment in a market where competitors change both without notice. Getting either wrong shows up in margin within days.
The competitive picture was assembled by hand. Someone checked competitor sites and marketplace listings, copied prices into a spreadsheet, and circulated it. By the time the file was complete it described a market that had already moved, and nobody could answer a simple question like what a given competitor changed that week.
The deeper issue was matching. Comparing a competitor's listing to your own product is not a lookup — titles differ, pack sizes differ, the same item appears under several names. Without reliable matching, a price comparison is a guess presented as a number.
A monitored pipeline over competitor storefronts and marketplace listings, matched product by product against the client's own catalogue.
Price, availability, assortment and reviews across competitor storefronts and marketplace listings, on a defined refresh cadence.
Listings matched to the client's own catalogue despite different titles, pack sizes and descriptions — the part that makes the comparison trustworthy.
Movements surfaced rather than buried in a table, so the team sees what changed since the last check instead of rereading everything.
A dashboard for the commercial team and an API into the pricing process, so the data is used where decisions are actually made.
Scope, sources and method are documented, and collection stays inside what the client is permitted to gather and use. Competitive intelligence that cannot be explained to your own legal team is not an asset.
The commercial team stopped assembling data and started acting on it
The work that had gone into building the spreadsheet was skilled work applied to copying. Removing it returned that time to the decisions the data was collected for.
The second change matters more over time: because the pipeline is monitored rather than delivered once, the picture stays current when sources move and pages change.
Tell us the spreadsheet somebody rebuilds every week.
A discovery session is a working conversation, not a demo. We will tell you whether the data is gettable and what keeping it current costs.