Fuzzy matching (also known as approximate string matching) is an effective technique that allows you to match near-identical sets of data. For its application in SEO, this data can be anything from URL slugs to page titles or H1s. This guide walks you through the process of using our fuzzy matching script, Fuzzzy, in Google Sheets.
How to use Fuzzzy
By following these steps, you’ll be able to leverage fuzzy matching for your marketing needs, whether that’s for redirects during website migrations, or finding similar pages for internal linking opportunities.
- Make a copy of our Fuzzzy Google Sheets Script
- You will only need two columns of data to add to the ‘Input’ sheet
- The idea is to have two datasets you want to find pairs between
- Please note: they don’t have to be exactly the same length, and any non-matches from the first column will be highlighted in the Sheet called ‘No matches’
- Once your data is ready, click Fuzzy Match in the menu bar. This will populate the Matches and No Matches tabs. The script will return the matching value with the highest matching confidence score, even if there are multiple.
We’ve used the FuseJS library in this Google Sheet tool. If you’d like to learn more about the scoring concepts of this library, you can read them here: https://www.fusejs.io/concepts/scoring-theory.html
- For URLs, we recommend that you remove the domain names and only use the URL slugs to avoid false positives.
- The script removes symbol characters when matching, so don’t worry about formatting or removing any hyphens or slashes.
- Make sure your data is clean and consistent before running the fuzzy matching script for accurate results.
Benefits of using Fuzzzy for SEO tasks
The main function of this tool is to help SEOs with their optimisation tasks in the following ways:
- Redirect maps
Redirect maps can be challenging for larger sites, but with a fuzzy matching tool, the time taken to find matches would be drastically reduced.
We faced this challenge with a client that needed redirect maps for 4 different languages. Despite the language barrier, fuzzy matching helped significantly, as we were able to match approximately 50% of the URLs with match scores of 75% and above. This saved us hours of time.
- Internal linking
There are a variety of ways to find internal linking opportunities but some of the easiest is pages with similar titles or URLs, and that’s where fuzzy matching comes in handy. Taking a list of pages with low URL Rank and comparing them to the rest of a site’s URLs can show opportunities where similar pages aren’t linked. You can also do this with titles/H1s and this works especially well with sites that have uniform titles or headings.
Let us know your feedback 📣
Have you got a question about using Fuzzzy? Or would you like to send us some feedback and feature requests? Let us know by getting in touch or via Twitter.