Marketplace analytics: every store at a glance
Ready by morning: what to order, what to ship, why sales changed
Sample data
Problem
Data on stock, orders, prices and reviews is scattered across marketplace seller accounts and manual exports. Decisions on "how much to order from the supplier and when to ship" were made on gut feel.
What we built
A tool that collects the data from all the stores by itself every night and by morning turns it into decisions: how much to order and when, what to ship to the marketplace warehouse, why sales changed, where the reviews show a problem building. All the stores on both marketplaces run in one system—a new store just plugs in, with no new development.
How it works
Nightly collection
Every store on both marketplaces: orders, stock, prices, reviews, the sales funnel—straight from the marketplaces' own systems, with no manual exports.
Recalculation
For each item: sales rate adjusted for seasonality, and how many days of stock are left.
Recommendations
How much to order and what to ship—before an item runs out. The shared stock is split between the stores by sales rate, so two stores never lay claim to the same units.
Root causes
Sales changed—a breakdown across eight factors at once: price, promotions, availability, reviews, season, the funnel, competitors' moves. Not "sales are down", but "a competitor cut its price three days ago—here is the chart".
Review signals
Negative reviews add up and get grouped by topic—a signal of a systemic problem, not a one-off complaint.
Summary
In the morning the owner sees what matters: what needs a decision.
Once a week the tool works out the store's share of its product niche—a metric the marketplaces do not hand over through their API.
It exists only in manual exports from the seller account. The tool parses those exports itself and turns them into a finished figure—for every narrow subcategory, not an average across the store.
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