If you have ever searched for something on Google, you may have noticed just how relevant the results tend to be. You rarely have to go to the second page or even scroll to the bottom of the first page to get what you want. The answer you seek is usually behind the first two or three links.
Yet when you search for stuff on certain e-commerce stores, the results tend to be very random and sometimes borderline useless. You may be a man searching for pants and when you do, they show you high-waisted women’s jeans. Google would never do that to you.
How does Google do it and can you replicate it?
Google’s algorithm is complex and the company hasn’t revealed the exact way it works but it mostly relies on backlinking. Let’s say, for example, you search for the term “Joe Biden.” Biden is the president of the United States and there are millions of websites and blogs on the internet that mention his name.
There could be a news story from ten years ago about Biden throwing the opening pitch at a Little League match. There may also be a Facebook rant from a guy who thinks Biden is secretly a lizard in human skin. But you probably won’t see these on the first page of search results.
What you’ll see first is his Wikipedia page and then a series of news stories about what Biden has been doing recently, formatted by order of importance. There could also be an interview from three years ago on the front page.
How does Google sift through the millions of Biden mentions on the internet to find the ones you would be most interested in? This is where backlinks come in.
A guy on Quora or Reddit asks what Biden’s favorite meal is and someone answers that it’s chicken, linking back to a magazine interview where Biden said chicken was his favorite food. Other people link to the same interview for other things like how Biden likes trains or how many kids he has. Other articles link to his Wikipedia page or some other press story.
When you go and type “Joe Biden” into Google, Google finds all pages that mention Joe Biden on the internet. Then it counts the number of links to each mention. Generally, the more a page is linked back to by other pages, the higher it ranks.
So, the Wikipedia page and the interview, which have thousands of pages linking back to them, rank very high up on page one of the search results while the Facebook rant about Biden the lizard man, which only has two blogs linking back to it, gets buried on page 3,000 of the search results where no human will ever see it.
Other factors affect Google rankings but backlinks are an integral part of the process. Backlinking allows Google to deliver results that are both very relevant and very trustworthy.
How to implement Google’s search methods in your store
While reproducing Google’s search algorithm for your store would be a tremendous technical challenge, you can try something a lot less involved but nearly as good. You can use context clues just like Google does to refine your search results. If you search the term “Who is the president?” on Google, you will get very different results based on the country you are in.
You can do the same for your store. If a customer searches for the term “pants” in your store, you shouldn’t return results containing every last pair of pants you have, especially not on the first page. There will be men’s pants, women’s, pants, children’s pants, hot pants, and the like.
It’s very unlikely that any one customer would be interested in all these types of pants. If the customer is a man, then it’s very likely that he’s only interested in men’s pants. If he was browsing the children’s section, then maybe he’s interested in children’s pants.
This is how you make your search results more relevant without needing to hire an entire army of software engineers. Use context clues like customer demographics, products in the cart, browsing history, and purchase history to filter the search results before even showing them to the customer.
You can also rank the already filtered results based on customer reviews so you can put your best products at the top. Just be careful with your review weighting. A product with a rating of 4.7 stars from 1,000 reviews is probably superior to one with a perfect 5-star rating from only two reviews.