Review descriptive metrics from your uploaded sales data and separate them from AI-generated suggestions.
Last updated: September 2026
You've got sales data. Maybe a lot of it. But you're staring at rows and columns hoping a pattern jumps out. It doesn't.
Seller IQ summarizes mapped transaction lines. The results depend on upload coverage, currency, mapping and the completeness of costs and refunds—not access to your entire business.
Code computes signed line totals from mapped uploads, preserving explicit zero profit. Review coverage and reconciliation warnings; quantity does not multiply financial amounts.
Explore reorder hypotheses informed by supplied sales data. Transaction history alone may not establish inventory availability or sell-through rates.
Review possible markdown strategies as generated hypotheses. Timing and price suggestions are not a forecast or a guarantee of sales.
Use observed upload patterns to frame questions about products, categories and pricing. Recommendations are generated hypotheses to test.
Descriptive comparisons within the uploaded period, subject to data coverage. Past changes do not predict future shifts.
Plain-English suggestions with assumptions and limitations. Review them against business context before making inventory or financial decisions.
Upload a supported CSV and review its column mapping. Remove unnecessary personal information and secrets before uploading; use a single reporting currency.
Review computed totals, coverage and discrepancies. Missing fees or costs, signed refunds and incomplete periods can materially change interpretation.
Separate user-uploaded observations from assumed inputs and generated hypotheses. Test recommendations and record field evidence before refining a company version.
E-commerce sellers, Amazon FBA operators, DTC brands — anyone with sales data who wants to make smarter inventory and pricing decisions without hiring an analyst.
Upload a CSV to review descriptive metrics and proposed next steps. Processing time varies, and generated recommendations are not empirically validated predictions.
Upload Your Sales Data →