How to find & fix duplicate listings in Poshmark
If you’re a clothing reseller who’s anything like me, you have hundreds or thousands of active listings in Poshmark. With that kind of activity, and especially if you’re using an extension so crosspost and re-list stale listings, it’s all too easy to accidentally create duplicate listings. There’s also nothing worse than having duplicate listings live, selling one item and delisting it, then having the duplicate you missed sell and then being forced to cancel the sale (to the ire of your potential customer!) because you don’t have the item.
Poshmark, unfortunately, doesn’t have any tools that can help you identify duplicates. Worse, you can’t even sort items in your closet alphabetically, so trying to find duplicates manually in a large closet is an exercise in futility. In this article, I’ll outline how you can use only free tools to set up a system that makes it really easy to identify duplicates (and export your listing data to CSV, Excel, and other formats for easier analysis).
Note: This is a highly technical article that requires more advanced tech skills. If this is beyond your comfort level, consider using a paid cross-listing app with inventory management features or duplication finder capabilities, like Crosslist.
Exporting Poshmark Data with a Web Scraper
Because Poshmark doesn’t offer any listing export options or an API, it’s difficult to get your data into a usable format for analysis. I use a very basic web scraping extension for Chrome that allows me to extract data that loads in my web browser and reformat it into something I can use in other applications. You will need the Chrome browser for this process, and then the “Web Scraper” extension, which you can download and activate here.
Once that’s done, visit your Poshmark closet page. From that view, I like to filter by available items only (look for the Availability tag in the filters section on the left side of the page), then I sort by “Just In”. As a result, here’s a sample of the URL that I might use for this analysis:
Once that page is loaded, go to the Chrome menu and choose View > Developer > Developer Tools. This should show a new section at the bottom of your browser window with code, like the example below. If it’s not at the bottom, you can use the icon with the three dots to display a menu that allows you to choose where to place the tools. Choose the bottom.
Once that’s set up, you will see a number of tabs in that new section. Look for one called Web Scraper and click it. It will be mostly empty your first time using it. Look for the Create new sitemap menu, then click it and choose Create Sitemap.
Name the sitemap (e.g. “poshmark-export”), then paste your URL into the Start URL 1 field., like the URL in my example above. Click Create Sitemap to start setting it up.
Now we need “selectors”, which are basically the types of data we want to collect from the Poshmark closet page. For this example, I’ll keep it simple and just retrieve each item’s title and price, but you could easily include data like size and brand as well. To add a selector, click Add new selector.
Enter a label for the ID. I’ll start with the container element for all of the listings, so I’ll just use “container” as my first ID. Type should be Element (scroll). For the Selector, go to the text field to the right of Data preview and enter “div.tiles_container” without the quotation marks. Check Multiple and Scroll, so your section looks like this:
Click Save selector to save your changes.
Next we want to add child selectors inside that container selector, so we’ll click on the selector row. Click anywhere inside it to go into it. You should see breadcrumb links for _root / container right above that, so you’ll know you’re in the right location.
Click Add new selector to set up the data for the listings that you want to extract from inside the container. I’ll start with the listing title, so I’ll use an ID of “title”, then for selector you can use this: “a.tile__title”. You can also click the Select button to choose it visually; just select multiple titles from the page above so it looks like this, then click Done selecting:
Check Multiple, leave the parent selector unchanged (it should be “container”, or whatever parent you set up), then click Save selector. It should look something like this:
Add another selector by clicking Add new selector. For the next one I’ll capture price, so I’ll set the ID to “price” and the Selector to “span.p–t–1”. Choose Multiple and the same parent. It should look like this:
Save the new selector. You will be prompted to group selectors, which you should do. Click Group selectors on the right.
The hard work is done; now we just need to run the web scraper to extract the data for all of our listings. To do that, go to your sitemap in the menu and choose Scrape, like this:
Leave the defaults of 2000 for both fields, then click Start scraping. The extension will open a new window and get data from all of your listings.
Depending on how many listings you have, the process may take several minutes. Let it run on your computer, even if it pauses and scrolls up and down multiple times. Wait until it has closed the pop-up window.
When it does, click the Refresh Data button. You should hopefully have data now for all of your listings in your browser. Assuming you do, click the menu for your sitemap again, then choose Export data. Choose your preferred data format (I’ll use CSV for the example) and click the button to download the file it generates. Your listing data can now be analyzed in Google Sheets, Excel, or whichever tool you choose.
Find Poshmark Duplicates in Google Sheets
I’ll use Google Sheets for my example because it’s a free product, but if you prefer Excel, Numbers, or another tool, it’s fine to use an alternative.
To get started, open Google Sheets and create a new spreadsheet. Then choose File > Import. In the Upload tab, choose the file you exported above and click the button to complete the import.
Once imported, name your spreadsheet at the top of the page. You can rename it by clicking on the title and entering something new.
You will have an unformatted spreadsheet with four columns; the first two aren’t relevant to our analysis, but for consistency, I’ll leave them in the spreadsheet. It’s the Title and Price that we care about.
If you just want to analyze things quickly and manually, you could highlight the entire sheet, then choose Data > Create a filter. You could then potentially click into the Title column (in column C) and choose the option to Sort A to Z. That can help to go through your listings quickly to see if any names match.
Of course, we want duplicates to be obvious, so as long as you’re comfortable working with formulas, we’ll create a new title for column E. In cell E1, type in “Duplicate?” or whatever label you prefer. Then in cell E2, copy and paste this formula:
=AND( C2<>””, COUNTIF( $C$2:$C$10000, C2 )>1 )
This assumes that column C has your title data and column D has your price data. Once entered, you should see TRUE in E2 if the title is a duplicate, and FALSE if it isn’t. Now select cell E2 and drag it down to the bottom of your data range so the duplicate check is applied to all records. If you want to make your search for “TRUE” entries as easy as possible, add a filter to the top of column E so it only outputs True records.
That’s it! You now have a clear picture of your duplicates in Poshmark so you can search for them and make changes as needed. You can also run any other analysis you might need on your Poshmark listings, and any time in future you can scrape the data again to analyze your live listings.
Conclusion
This process to find Poshmark duplicates in this article is certainly complex, but once it’s set up, you can run it any time again in future. And until Poshmark adds their own tool that makes finding duplicates easier, this is the best way to avoid problems related to double listings in your closet. Once you have the data, it also provides an easy way to perform other analysis related to your listing prices, sizes, brands, colors, and other data you might want.
Happy thrifting!
