How a Digital Shelf Analytics Firm Cut Weekly Data Collection Time by Outsourcing Web Scraping
A retail analytics firm builds digital shelf reports for CPG brand manufacturers, tracking pricing, availability, and shelf position. Its 12-person data team benchmarks 150+ SKUs across 25+ grocery and marketplace sites every week, all copied by hand until now.
From four analyst-days to under four hours per weekly cycle
Down from one week
Full transition completed within one quarter of kickoff
Client Snapshot
A retail analytics firm builds digital shelf reports for CPG brand manufacturers, tracking pricing, availability, and shelf position. Its 12-person data team benchmarks 150+ SKUs across 25+ grocery and marketplace sites every week, all copied by hand until now.
The Challenge
Analysts manually opened each grocery and marketplace site, screenshotting shelf position and typing prices, stock status, and ratings into tracking sheets for 150+ SKUs across 25+ sites. A weekly report took four analysts most of a week to compile, and competitor prices had often shifted by the time a client saw it.
An in-house scraper built two years earlier broke constantly against JavaScript-rendered shelves and rotating IP blocks, and a freelance scraping contractor could not keep pace once the SKU list grew past 100 products.
The Solution
APISCRAPY now covers all 150+ tracked SKUs across the full 25+ site list, pulling price, stock status, shelf rank, and ratings from each page. Top retailers refresh daily and smaller sites refresh weekly. Every record is deduplicated and split into sale versus list price, with JavaScript-rendered shelves and anti-bot defenses handled on APISCRAPY's side.
Data lands on a shared dashboard and through an API feed wired into the firm's existing reporting stack. First usable data arrived within 10 business days of kickoff, with no engineering hire needed.
The firm chose APISCRAPY over a raw scraping tool because the account came with a data operations team handling cleaning and normalization, not just collection. Setup meant a discovery call and a sample-data review before go-live, and that team absorbed every shelf layout change afterward.
The Results
Manual shelf checks across all 25+ sites are gone, cutting data collection time from four analyst-days to under four hours per weekly cycle. Report turnaround for brand clients fell from a week to next-day delivery. The firm added two new brand accounts in the following two quarters without adding analyst headcount, and shelf reports now reflect same-day pricing instead of week-old snapshots.
We used to spend four days a week chasing shelf data. Now our analysts spend that time explaining what the shelf data means for our clients.
Tell us your sources and schema. We scope a pilot in days with a data sample you can evaluate before committing.