When I built my dining room table (a bit of backstory on that in my dining room tour here) I ended up with the challenge of trying to find chairs that matched. I built the table myself because I couldn’t afford to buy a full dining room set. I knew I was going to need to find chairs secondhand, because dining chairs are expensive AF. I think the materials for the table cost about $200. If I were buying chairs new, I could easily spend that much money on one chair, and I needed at least six. We lived with a few random folding chairs around the table while I searched Craigslist and Facebook marketplace for a permanent option. Some time during this search, John and Sherry at Young House Love mentioned using the Facebook marketplace algorithm to their advantage on their podcast.
The concept is pretty straightforward. The Facebook Marketplace algorithm is designed to try to predict what users are looking for and most likely to buy. You can train it to show you more of what you want by what you click on. In my case, I was looking for dining chairs. I clicked on lots of postings for dining chairs, even if they weren’t exactly the kind I wanted. Conversely, I avoided clicking on things that caught my eye but weren’t dining chairs. Over time, the algorithm showed me fewer things that weren’t dining chairs. Then I found the perfect set of chairs for my table. In the end, my full dining set cost around $350 total.
This idea of training the algorithm applies in a lot of different scenarios. Take social media ads for example. Amanda and I have a friend who got an ad for engagement rings that was advertising conflict-free diamonds. She clicked on it because she was curious about the conflict-free diamonds, and now her feed has been full of engagement rings for months. Social media platforms’ advertising algorithms are going to show you more of what you engage with. In the case of our friend and the engagement rings, that ended up being annoying for her. On the flip side, I’ve used this to my advantage. I often get ads for jewelry companies (not engagement rings!) that I think are interesting. I don’t want to deal with the clutter of signing up for their email lists. To make sure they stay on my radar, I click on one of their ads. This helps ensure I keep seeing their ads so I don’t forget about them. It also often means I end up in their retargeting pools, so if they’re running sales I get ads for those as well.
A brief explanation of retargeting: if you accept cookies when you go to a site, your browser is cookied. Over time, this creates a data pool the site can then plug into biddable advertising channels to use for targeting ads. If you don’t want a site to cookie your browser, you can either deny cookies, clear your cookies, or visit the site in an incognito window. Amanda and I both work in marketing in our day jobs, so we spend a lot of time thinking about retargeting and algorithms. As an aside, I can assure you the marketers who are retargeting web users don’t know any personal details. We just get random pools of ID numbers that are assigned by the data management platform tracking the cookies.
But back to the topic of this post: algorithms, and how to train them. Most things online are running some kind of an algorithm. While these are the “secret sauce” of the web platforms, a bit of common sense can usually discern some of the elements of an algorithm. Sites are going to favor actions that help their business grow. Social media sites reward engagement, search engines want to help users find information quickly and accurately, and e-commerce sites want customers to find the products they’re looking for and make a purchase. When you start thinking about what a site will favor in its algorithm, you can start learning how to train it to help you out. If Facebook Marketplace wants you to find dining chairs you like, and you want to find dining chairs you like, think about the ways you can tell it that you’re looking for dining chairs and not bookshelves, or a car, or refurbished electronics. When you get what you want, everyone wins.
I hope this is helpful. We’d love to hear about your marketplace wins, your retargeting woes, and just generally what kind of content you like to read. Please connect with us on social media, leave us a comment below, and check out our email newsletter for updates when we post new content.