Get set up in four steps

Go from an empty workspace to your first pricing recommendation in about fifteen minutes — no retailers, no products, and no runs until you add them.

What you get

• A live comparison of your prices against retailers you choose to watch
• One place to trigger a check on demand or leave it to a schedule
• Recommendations that explain what changed and why, before you decide anything

1. Connect the retailers you compete with

Price Checker only compares you against retailers you tell it to watch. Head to Settings → Retailers and add the competitors you want tracked. Add them one at a time, or use the bulk import if you already have a list.

2. Import what you sell

Tell Price Checker which of your own products to track. Add them manually, or bring in a bulk list via Settings → Catalog → Import, which includes a downloadable sample CSV so you can match the expected columns.

3. Run your first check

With at least one retailer and one product in place, go to Overview and select Run now. This kicks off a price check across your connected retailers. Checks consume research units against your plan's cap, so it's a deliberate action — set up a schedule later if you'd rather it happen automatically.

4. Read your first recommendation

Once the run finishes, results land in the Action Center as pricing recommendations — one per product where something's worth reviewing. Each recommendation explains what changed and why, and you decide whether to accept or dismiss it.

Tips

• Load the sample dataset from Settings first if you want to see a populated workspace before connecting anything real.
• A run that produces zero recommendations is a normal result — it means your prices are already in line with what you've configured.

Go further

• See what needs attention — work the Action Center day to day.
• Get alerts when prices move — stop checking manually for changes.
• Put checks on a schedule — keep results current without triggering runs yourself.
• Sample data vs your data — if you loaded the demo dataset, read this before you run for real.