GMC Price Competitiveness Import
Import a CSV export from Google Merchant Center / BigQuery (manual) and compare your price vs benchmark/competitor price: gap% + traffic light (≤0 / 0–3% / >3%) — incl. export of a repricing candidate list.
Note: results are not made indexable via URL parameters. Canonical: https://tools.snapsoft.de/en/tools/gmc-price-competitiveness
Who is this for?
- Pricing/repricing teams who want a quick candidate list from GMC data
- Ops/category managers prioritizing products priced above benchmark (yellow/red)
- Teams working manually with CSV/copy-paste — without API setup
Price competitiveness: quickly see where you’re priced above the market
The price competitiveness export from Google Merchant Center provides a benchmark/competitor price per product. This tool imports the CSV manually (upload or copy/paste) and computes a per-product price gap (gap%) and a simple traffic light.
No API calls and no storage: everything runs locally in your browser. Optionally filter by country and export a repricing candidate list.
Calculator
Max 6 inputs, clear outputs. Everything runs locally in your browser.
Inputs
Everything runs locally (no API calls, no storage).
Upload or copy/paste. Everything runs locally in your browser.
Advanced options
Optional: pick a file — we’ll copy its content into the text area.
Leave empty = all countries.
Column mapping
Mapping appears after importing the CSV.
Result
How it works
From the CSV we read productId, your price (ownPrice) and benchmark/competitor price per row.
Gap% = (ownPrice − benchmarkPrice) / benchmarkPrice. Green if gap% ≤ 0; yellow if 0 < gap% ≤ 3%; red if gap% > 3%.
The 0–100 score is derived from the green/yellow/red share: green counts full, yellow half. We also derive an “overall signal” from it.
The repricing candidate list includes products priced above benchmark; the target price is computed as benchmarkPrice × (1 − underbid%).
Quick conclusion
- Gap% + traffic light make GMC export deviations easy to prioritize.
- Focus: red (>3%) as “poor” — typical repricing candidates.
- Next step: export the candidate list and feed it into your repricing workflow.
Sources & notes
Disclaimer: assumptions, fees and policies can vary and change. Always verify critical values in official sources (marketplace, supplier, payment provider).
FAQ
Which columns are required in the CSV?
At minimum: productId/offer id, your price, and benchmark/competitor price. If column names differ, you can map columns manually in the tool.
What does “poor competitiveness” mean here?
In this tool “poor” = red, i.e. gap% > 3% (your price is clearly above benchmark/competitor).
Does the tool make API calls or store data?
No. Everything runs locally in your browser without storage.
Why are rows skipped?
Common reasons: missing/empty productId, non-numeric prices (e.g. text), or benchmarkPrice is 0/empty. You’ll see skipped counts in the KPI cards/notes.
Do you support *_micros columns?
Yes. If a price column contains “micros” in its name, we divide by 1,000,000 (common for BigQuery exports).
Turn it into a repricing rule in SnapTrade
If you want to turn benchmarks into automated repricing rules and guardrails (instead of manual CSV workflows): SnapTrade can help.