Decide Whether to Resell an eBay Item

Research an eBay item's demand, competition, and margin before you buy.

Introduction

30 Second Summary

Fees can turn a bargain into a poor resale purchase. Weak demand can leave that item sitting unsold.

In this project, you will investigate one item with eBay's free resale research tools. You'll collect live competition with Apify's E-commerce Scraping Tool before calculating the most you can pay.

What You'll Build

Your finished margin sheet shows whether a possible purchase price stays under the maximum you can pay.

By the end of this project, you'll have:

A sell-through rate that shows how strongly your chosen item is selling. A 90-day sold price band that gives you a realistic resale target.
A weekly competition tracker that refreshes your sortable live listings table.
A margin sheet that shows your maximum buy price after fees, shipping costs, and your target margin.
Secret Mission: An optional challenge to push your resale research skills further.

Do I Need Any Accounts?

You'll need a free eBay account with Seller Hub access. You'll also need a free Apify account.

Before We Start

A resale decision becomes unreliable when each search describes a different item. One precise keyword set keeps every later comparison focused on the same product.

You also need access to eBay Seller Hub and Product Research before the research begins. A web browser gives you access to both.

A spreadsheet tool will hold your later margin calculation. An email address lets you create an Apify account when the scraping stage begins.

In this step, get ready to:

Choose one resale item with a reusable set of search keywords.
Confirm access to eBay Seller Hub and Product Research.
Prepare the supporting tools needed for later research.

Choose one resale item

Broad keywords can mix different models or conditions into one result set. A focused phrase gives you comparable listings throughout the project.

Choose one item you could realistically buy for resale.
Refine the phrase until every word describes the exact item.
Record that phrase here: your resale item keywords.

Confirm your research toolkit

Seller Hub supplies the Product Research data used in the next stage. Your spreadsheet tool later turns that research into a maximum buy price.

Account setup can feel fiddly because Seller Hub access varies by eBay account. You are only confirming access in this step.

Use a web browser to go to eBay.
Create a free eBay account if you do not already have one.
Sign in to eBay with that account.
Open Seller Hub from eBay.
Open Product Research inside Seller Hub.
Confirm your spreadsheet tool opens to a blank sheet.
Confirm you can receive messages at the email address you plan to use for Apify.

You should see Product Research ready for an item search. You should also see a blank spreadsheet ready for later calculations.

Can't Access Product Research?

Product Research is available through Seller Hub. Your eBay account may need seller access before the page becomes available.

Complete the seller access setup that eBay presents inside Seller Hub.
Return to Product Research after Seller Hub access becomes active.

Help me resolve my access problem.

Verify your starting point

Before you check, do you expect Product Research to open with your current eBay access?

Return to Product Research in Seller Hub.
Confirm the page loads without starting a search.
Check that your resale item keywords still name the exact item you chose.

You will see Product Research ready for your first search. Your recorded keywords name the same item you will use throughout the project.

That preparation gives every later comparison a reliable starting point. Next up, you'll compare sold listings with live listings to measure demand.

Measure Sell-Through Demand

A promising purchase can still sit unsold among hundreds of similar listings. Demand evidence gives you a firmer starting point before you think about price.

eBay lets you compare current supply with sold results. In this step, you will turn those two counts into a sell-through rate for your chosen item.

What is sell-through rate?

Sell-through rate compares sold listings with current live listings from the same search. Calculate it as (sold listing count / live listing count) * 100.

The percentage shows how many sold listings you found relative to current supply.

In this step, get ready to:

Search eBay for your chosen item.
Capture both eBay result counts.
Calculate the item's sell-through rate.

Search eBay for live listings

Your first result count represents current supply for the keywords you chose. You need this live count before looking at sold results.

Signing in uses your usual eBay account details. Your credentials stay on eBay's sign-in page throughout this project.

Visit the eBay homepage in your web browser.
Select Sign in near the top of the page.
Complete the sign-in prompts with your eBay account details.

You're signed in when eBay returns you to a page showing your account identity. That access unlocks the sold-listing view needed for this comparison.

Select the main search field.
Enter your item keywords.
Press Enter to submit the search.

You'll see a results page for the exact item keywords you entered.

Read the total result count near the top of the results page.
Record the live result count here: your live listing count.

This count is your live-listing baseline.

Can't find the live result count?

Confirm that you submitted the search from eBay's main search field.
Keep Sold Items disabled for this first count.
Use a clear model name or item description if the search has no matching results.

Help me locate the live result count on my eBay search page.

Filter for Sold Items

The Sold Items filter can be fiddly because its position changes with the page width. The same query keeps your two counts comparable.

Confirm that the search field still displays your item keywords.
Locate Sold Items among the result filters.
Enable Sold Items.

eBay refreshes the page. You'll see a new result count while Sold Items remains enabled.

Read the result count for the sold listings.
Record the sold result count here: your sold listing count.

Can't find Sold Items?

Look through the filters beside the search results.
Use the page's filter menu on a narrow browser window.
Confirm that you are still signed in to eBay.

Help me find the Sold Items filter on my eBay results page.

Calculate the sell-through rate

Your two counts now describe live supply and sold activity for the same keywords. The formula turns that comparison into one percentage.

Open a blank sheet in your spreadsheet tool.
Enter your sold listing count in cell A1.

You'll see the sold count ready as the first part of your calculation.

Enter your live listing count in cell B1.

Your sold count and live count now sit side by side. Before you calculate the rate, do you expect those two numbers to be close or far apart? Hold that prediction in mind.

Enter =(A1/B1)*100 in cell C1.
Press Enter to calculate the rate.

You'll see one number in cell C1. That number is your sell-through percentage.

Record the value from cell C1 with a percent sign here: your sell-through rate.

Spreadsheet won't calculate the rate?

Confirm that cell A1 contains only the sold-listing number.
Confirm that cell B1 contains only the live-listing number.
Re-enter =(A1/B1)*100 in cell C1.

Help me troubleshoot my sell-through rate calculation.

Good work on turning two result counts into a measurable demand signal. Next, you'll compare sold prices to find the price range buyers are paying.

Research Sold Price History

Your sell-through rate now shows how often listings for your item sell on eBay. Sold prices answer the next question: what buyers actually paid.

In this step, you will use Product Research in Seller Hub to examine the last 90 days of sales. The resulting price band gives your resale target a market anchor.

In this step, get ready to:

Open Product Research in Seller Hub.
Search your item across the last 90 days.
Turn the observed sold-price band into a target resale range.

Open Product Research

Product Research collects completed eBay sales into a searchable view. It turns individual sales into a price history you can compare.

Switch back to the eBay tab from your demand research.
Select Seller Hub from the eBay navigation.
Select Research at the top of Seller Hub.
Select Product Research from the Research menu.

You should see the Product Research workspace with a keyword field plus date controls.

Product Research Missing?

Confirm that you are still signed in to the same eBay account.
Check that your eBay account can access Seller Hub.

If the selling tools are still unavailable, help me work out why Product Research is missing.

Search the last 90 days

Using identical keywords keeps your demand research comparable with your price research. The 90-day window gives you a broader view of completed sales.

Enter the same item keywords from your demand research into the Product Research search field.
Set the date range to cover the last 90 days.
Select the search control beside the keyword field.

You should see sold-listing results for your item within the selected period.

No Sold Results?

Compare the keywords with your original eBay search.
Confirm that the date range still covers the last 90 days.

If the results remain empty, help me troubleshoot my Product Research search.

Review the sold price range shown in the results.
Record the lower endpoint as your low sold price.
Record the upper endpoint as your high sold price.

Set your target resale range

Your first target range can use the observed sold-price band directly. This keeps your resale target tied to completed purchases from the selected period.

Return to the notes where you recorded your live count.
Add a sold-price section beside your sell-through rate.
Write your low sold price in that section.
Write your high sold price in that section.
Record the complete low-to-high band as your target resale price range.

Before you compare the entries, do you expect your target range to line up with the observed low-to-high sold-price band?

Check the date range shown in Product Research.
Compare your recorded lower endpoint with the low sold price.
Compare your recorded upper endpoint with the high sold price.

You should see a Product Research query covering 90 days. Your notes should show the low sold price from that query.

They should also show the high sold price from that query. The target resale range should span those two endpoints.

That is your pricing anchor locked in. Next, you will bring live competing listings into a table you can sort.

Scrape Live eBay Listings

Your 90-day sold-price range shows what buyers paid for the item. A resale decision also needs today's competition on eBay.

In this step, you will use Apify's E-commerce Scraping Tool to turn the same live search into a dataset. The Actor collects one row for each retrieved listing.

What is an Actor?

An Actor is a cloud program that performs a task using the input you provide. E-commerce Scraping Tool uses your eBay search URL to collect publicly available listing data.

In this step, get ready to:

Create a free Apify account.
Configure E-commerce Scraping Tool with your live eBay search URL.
Run the Actor to produce a dataset of live competing listings.

Create your Apify account

A free Apify account gives you access to the console that runs the Actor. You can manage the scraper input from the same console.

Open the official E-commerce Scraping Tool page.
Follow the account prompts to create a free account with your preferred sign-in method.
Complete any account verification Apify requests.
Return to the E-commerce Scraping Tool page after signing in.

You should see the E-commerce Scraping Tool input screen in the Apify Console. Your account is ready to configure the Actor.

Having trouble reaching the Actor input?

Use the same sign-in method you selected during registration.
Refresh the official Actor page after completing any account verification.

Help me reach the E-commerce Scraping Tool input screen.

Copy the live eBay search URL

The search address captures your exact item keywords plus the current filters. The Actor uses this address to identify your live competitors.

Return to the eBay search results from your earlier demand research.
Clear the Sold Items filter in the search filters.
Confirm that the search box contains the same item keywords used in Product Research.
Click the browser address bar.
Press Cmd+C (macOS) or Ctrl+C (Windows) to copy the URL.
Switch back to the E-commerce Scraping Tool input screen.
Find the URL input described as accepting category or listing pages.
Paste the copied eBay search URL into that input.

The Actor input now points to the public live listings for the same item you researched in Seller Hub.

Generate the live listings dataset

Each Actor run processes its saved input to create a default dataset. Starting the run uses Apify usage credits.

Before you start the run, do you expect the output to stay as an eBay page or become structured rows?

Click Start to run the Actor.

The run can take a few minutes while the Actor visits listings. A short wait here is expected.

Wait for the run to finish.
Open Output or Storage in the finished run.
Switch the dataset to table view.
Inspect the first few listing rows.

You should see one row per retrieved live listing with its title. Prices appear where eBay makes them available.

No listing rows?

Confirm that the copied URL opens a public eBay search page.
Replace any Seller Hub Product Research URL with the live search URL.
Run the Actor again after correcting the URL.

Help me troubleshoot an empty Apify dataset.

You have captured the live market in a dataset of competing eBay listings. Next, you will export these rows to calculate your maximum buy price.

Calculate Your Maximum Buy Price

Your completed E-commerce Scraping Tool dataset in Apify shows live eBay competition. Asking prices alone cannot tell you whether a purchase leaves enough profit.

This step converts that evidence into a margin sheet. The result is the highest purchase price that preserves your target profit.

In this step, get ready to:

Export the completed dataset as a CSV file.
Add columns for your selling price assumptions and costs.
Calculate the maximum price you can pay for the item.

Export the live listings as a CSV

A CSV stores each listing as a row with each field in its own column. That structure lets your spreadsheet keep the scraped evidence in a sortable table.

In the completed dataset from earlier, click Export above the table.
Select CSV as the export format.
Click Download.
Open your browser's downloads panel.
Show the downloaded file in Finder on macOS or File Explorer on Windows.
Rename the downloaded file to live-listings.csv.
Open live-listings.csv in your spreadsheet app.

You should see the imported column headers with one live competing listing on each row. That export gives you a reusable snapshot of the market you researched.

Downloaded file looks empty?

Return to the completed run from earlier to confirm that its default dataset still contains listing rows.
Export the default dataset again after the rows are visible.

If the file still has no listing rows, help me troubleshoot an empty Apify dataset export.

Add the margin columns

Your downloaded file is the untouched evidence from Apify. Saving a spreadsheet copy protects that original export while you add your own assumptions.

Save a copy of live-listings.csv in your spreadsheet app's native file format.
Insert five blank columns before column A.
Enter Selling Price in cell A1.
Enter eBay Fee Amount in cell B1.
Enter Shipping Cost in cell C1.
Enter Target Margin in cell D1.
Enter Maximum Buy Price in cell E1.

What do these columns capture?

Selling Price holds the price you expect a buyer to pay.
eBay Fee Amount holds the estimated total selling fee for that sale.
Shipping Cost holds the amount you expect to spend on delivery.
Target Margin stores your desired profit as a currency amount.
Maximum Buy Price shows the most you can spend while keeping that profit.

Save your spreadsheet copy.
Check cells A1:E1 to confirm that all five headers sit beside the imported listing data.

You should now see your live market data beside a dedicated margin calculator.

Calculate the maximum buy price

The maximum buy price starts with your target selling price. Every expected cost plus your desired profit reduces what you can safely pay.

Enter the value from your recorded 90-day sold-price range that matches the item's expected condition in cell A2.
Enter the expected total eBay fee amount for that selling price in cell B2.
Enter your expected shipping cost in cell C2.
Enter your desired profit amount in cell D2.
Apply your spreadsheet's currency format to cells A2:E2.

Before you calculate it, do you think these costs leave enough room for the price you expect to pay?

Calculate the maximum buy price in cell E2 by entering this formula:

=A2-B2-C2-D2

What does this formula do?

Cell A2 supplies your target selling price.
Cell B2 removes the expected eBay fee amount.
Cell C2 removes the expected shipping cost.
Cell D2 protects your desired profit.
The value left in E2 is your buying ceiling.

Press Enter to calculate the result.
Save your spreadsheet.
Compare the value in E2 with the price you would need to pay for the item.

You should see a currency value in E2. That value is the maximum price you can pay after accounting for fees, shipping, and your target profit.

That is the decision point done: your sheet now shows the most you can pay without giving up your planned profit.

Formula shows text or an unexpected result?

Change cell E2 from a text format to a number format if the formula appears unchanged.
Check that every value in cells A2:D2 contains only a number or currency value.
Review your costs if the result is negative because the planned sale does not cover them.

If the result still looks wrong, help me troubleshoot my maximum buy price formula.

Your margin sheet now turns market prices into a clear buying ceiling. Next, you'll schedule the Actor to refresh your live listing data each week.

Schedule Weekly Price Tracking

Your Resale Margin Sheet now turns today's listings into a maximum buy price. That decision gets stale when competing listings change.

A weekly schedule in Apify keeps the research moving after today's session. In this step, you will schedule the E-commerce Scraping Tool to repeat the same eBay search every week.

In this step, get ready to:

Save the successful scraping input as a reusable task.
Enable weekly tracking that produces a fresh dataset.

Save the successful input as a task

A saved Actor task preserves the input from a successful run. The weekly schedule can reuse that exact eBay search without rebuilding the form.

Return to the completed E-commerce Scraping Tool run in the Apify Console from earlier.
Select the Input tab on the completed run.
Click Save input to a new task.

You'll see the new task page with the same eBay search in its input. This proves the reusable configuration carries your tested search forward.

Create the weekly schedule

A schedule adds timing to the saved task. Weekly tracking creates dated market snapshots without requiring another manual search.

Open the three-dot menu at the top right of the task page.
Select Schedule.
Select Weekly.
Click Create.

You'll see the detail page for the new schedule. Its action uses the saved E-commerce Scraping Tool task.

Click the schedule name at the top of the detail page.
Enter Weekly eBay Price Tracking as the schedule name.
Select Schedules in the Apify Console navigation menu.
Open the newly named schedule from the schedules list.

Before you expand the timing details, when do you expect the next repeat to appear?

Click Show more in the Next runs section.

You'll see upcoming runs spaced one week apart. These dates confirm that the schedule uses a weekly cadence.

Check the status shown on the schedule detail page.

✔️ The schedule is enabled

The weekly trigger is active. Its next run remains listed on the schedule detail page.

ⓧ The schedule is disabled

Click Enable on the schedule detail page.

You'll see the status change to enabled. The schedule can now start the saved task at its next weekly time.

You've turned a one-time scrape into an enabled weekly tracker. The Apify Console now shows when the next market snapshot runs.

Schedule missing the saved task?

Return to the saved task page if the schedule shows no task action.
Use the three-dot menu to create the weekly schedule again.

Help me fix an Apify schedule that does not show my saved E-commerce Scraping Tool task.

Run a fresh price check

The first automatic run waits for its next weekly slot. A manual run now checks that the saved input still produces a fresh dataset.

The published 40-listing example finished in under two minutes. A larger result set can take longer.

Return to the saved E-commerce Scraping Tool task page from earlier.

Before you click Start, do you expect Apify to replace the first dataset or create a separate snapshot?

Click Start at the top right of the task page.
Wait until the follow-up run finishes successfully.
Open the default dataset attached to the completed follow-up run.
Review the listing titles in the new dataset.
Review the listing prices in the new dataset.

You'll see a separate completed run with its own new dataset. The rows form a fresh snapshot of your live competition.

Follow-up run did not complete?

Confirm that the task's Input still contains the eBay search from the completed run.
Review the latest run details for the stage that stopped.

Help me diagnose an E-commerce Scraping Tool task that did not produce a new dataset.

That's the tracking loop complete. Your research kit now holds an enabled weekly schedule plus a second market snapshot.

Secret mission

Add a Live-Market Safety Check

Turn the newest live listings into a safety check for your maximum buy price. You will compare three close competitors before choosing a sourcing ceiling that reflects the latest market.

Clean Up Your Resources

Your weekly Apify schedule keeps running after the project. Each run uses account credits. Choose whether to keep tracking prices, pause the schedule for later, or remove the project resources entirely.

Cost warning

An enabled weekly schedule continues consuming Apify credits whenever it starts the E-commerce Scraping Tool. Pausing or deleting the schedule prevents further automatic runs.

Resources you used:

Your enabled weekly Apify schedule for the learner-selected eBay item.
The two completed Apify run datasets containing live competing listings.
The live-listings.csv export containing the original live listing table.
Your Resale Margin Sheet containing the maximum buy price calculation.

Keep everything running

No action is needed. Choose this if you are still tracking the item or plan to compare another purchase soon.

Keep the weekly schedule enabled so the E-commerce Scraping Tool continues collecting fresh listing data.
Keep both completed datasets so you can compare the original listings with the follow-up run.
Keep live-listings.csv as a snapshot of the original competition.
Keep the Resale Margin Sheet as a reusable template for your next item.

Pause - I'll come back to this later

Stop future runs to preserve credits while keeping your research outputs ready for later.

Return to the weekly schedule that is already visible in the Apify Console.
Use the schedule's status control to disable future runs.
Confirm that the schedule now shows a disabled state.
Keep both completed datasets available for comparison.
Keep live-listings.csv in its current saved location.
Keep the Resale Margin Sheet as your template for future resale decisions.

Delete - I don't want to use this again

Remove every project resource when you no longer need this tracker. This stops future runs and clears the saved research outputs.

Return to the weekly schedule that is already visible in the Apify Console.
Use the deletion control for that schedule.
Confirm that the weekly schedule no longer appears in your schedules list.
Return to the two completed E-commerce Scraping Tool runs from earlier.
Select the dataset attached to the first completed run for deletion.
Use that dataset's deletion control.
Repeat the dataset deletion for the second completed run.
Confirm that neither dataset remains available from the two run records.
Use Finder on macOS or File Explorer on Windows to search for live-listings.csv.
Delete the matching live-listings.csv file.
Confirm that your file search no longer returns live-listings.csv.
Return to the spreadsheet app that contains the Resale Margin Sheet.
Use the spreadsheet app's file deletion option to remove the Resale Margin Sheet.
Confirm that the Resale Margin Sheet no longer appears in the app's file list.

Nice Work!

You did it! You now have a resale research kit that turns one possible purchase into a decision backed by demand, sold prices, live competition, and profit calculations.

Your weekly Apify schedule keeps that research current. Your margin sheet shows the highest price you can pay while protecting your target profit.

You've learned how to:

Measure buyer demand by comparing sold listings with live listings on eBay. Use the 90-day sold-price range to choose a realistic target resale price.
Research live competition with the Apify E-commerce Scraping Tool. Export the retrieved listings to live-listings.csv for sorting and comparison.
Calculate a maximum buy price after eBay fees, shipping costs, and target profit. Track the market with a weekly Actor schedule that produces fresh datasets.
Secret Mission: Complete an optional challenge to push your resale research skills further.

Ready to quiz yourself?