How Do You Track Competitor Prices Every Day? Hand the Phone Patrol to a Computer

People who do competitor analysis know what to look at. The hard part is looking every day.

Looking once is easy. A week is still possible. By three months, days start getting skipped. By six months it has mostly gone quiet. Something more urgent always crowds out the repeated job. The value is in looking without a break, so this daily work fits a computer. What you save is labour.

Which fields to watch

If the fields are not settled, the automation can finish and still be useless.

Price is the most direct. Compare the price the buyer actually pays, with discounts, coupons, and member prices included. After that calculation, it often fails to match the sticker price.

New listings are what the competitor has put up lately: which new products, which models, which styles. This field fits a weekly look.

Changes to the hero image and the copy need a continuous look. When a competitor changes the hero image, they are often running an A/B test, or the old image was not working. A few looks in a row show which direction they are trying.

Sales and review counts are about the slope. One reading explains little. 1,200 reviews today and 1,180 yesterday means roughly 20 orders yesterday.

The first three show what they did. The fourth shows whether it worked afterward. You need all four to judge.

Why the phone is harder to watch

If all of this lived on the web, it would be much simpler. A lot of the information exists only in the app. The web has ready-made ways to collect it. The phone side has none.

Inside an app you move one screen at a time. A web page can load dozens of rows at once. In the app you scroll. Fifty SKUs means a dozen or more screens.

The login session drops. Leave the account alone for a while and it asks you to sign in again. A script stops at that step.

Popups are frequent. Open the app and an event is pushed. Enter a page and a coupon is pushed. Go back and it is pushed again. A script that only follows fixed steps either misses these or gets stuck.

Commerce apps also change often. A patrol script with coordinates written in usually does not last two months.

Once the upkeep cost is high, the team drops phone-side patrol and goes back to doing it by hand.

Describe the daily routine in a conversation

iEasyRun is free and runs on your own computer. Describe the routine you already do by hand, and let it run every day. A description looks roughly like this:

Open the competitor list on platform A and find these three stores. Go into each store, screenshot the first screen of the home page, and note the price of every item on sale. If an event popup appears, close it and continue. When finished, save the screenshots to a folder called competitor patrol on the desktop, named by date.

That paragraph has to say three things: what to look at, what to step around, and where the results go. How to find the buttons stays out of it.

Compared with writing a script, a layout change needs no new setup, because it finds things by the text. A popup needs one rule. That one rule covers the popups. If the login session drops, add one line: if it asks you to sign in, run the login flow.

That last point is the practical one. A script usually has a hard time with an expired login, and the login flow itself can change. In a description, it is one more sentence.

When it runs, and how to store the results

Run it before the working day starts. The first thing you do when you sit down is read the result, and you can use it in the morning meeting. “Two of the three competitors changed price yesterday” is more useful than “I had a look recently.”

For categories where prices move a lot, add an evening pass. Comparing morning and evening shows whether there was a same-day price change. That is what you want while a promotion is on.

Change new listings and review trends to once a week. A daily look gets buried in noise.

Line the patrol up with the time you make the decision. If the day’s ad plan is set at 10, the patrol should finish before 9. If nobody reads it afterward, the run never reaches the decision.

Keep both screenshots and a spreadsheet. Screenshots are for looking back at the page as it was. When you want to check “is that how they wrote it then,” the screenshot is the fastest place. The spreadsheet is for the trend. It needs at least four columns: date, competitor, field, value. Drop one column and three months of data still cannot be analysed.

You can have the patrol write straight into one fixed spreadsheet, appending a row each time. After three months you can pull the trend directly, without digging numbers out of a pile of screenshots.

The first run is three stores and two fields, price and hero image, for a week, so you can see whether the result is what you wanted. Ten competitors and eight fields is too wide for that first week. Once there are too many dimensions, every row looks worth chasing, and you finish none of them.

What you are looking at is public information. The normal way is to browse someone else’s public pages the way a person would. Leave alone anything that requires a login to see, and anything the platform explicitly restricts. Keep the frequency ordinary too, at the pace a person would browse.

Wait until you have two weeks before you draw a conclusion. One pass only tells you what they are at now. Two weeks of continuous data shows which direction they are moving.

After a run, open execution history and read each record. A store that stopped halfway, a field that was not captured: both are in the record. For related patrols, see what to do when a phone keeps going offline and daily operations in the Amazon seller app.