Related Products and Searches is a product that recommends popular search pairs. The insight it provides is incredibly valuable as it’s based directly on user data and tells you exactly what your webshop’s visitors want to see and how they think.
Related Products usually appear on 0-result pages so users can easily navigate to other products that fit their needs, but can also be configured to appear when results for a query are found.
Related Searches encompasses both search suggestions and product suggestions and can be displayed on search result pages (SERP) and 0-result search pages. When a user searches for a product and results are found, Related Searches places smart keywords above and below the results. For difficult, long tail searches when the search engine cannot display results, Related Searches places keywords and product suggestions (with images) on the 0-results page to help users find products that match their initial intent.
Related Searches mines and refreshes content based on user behavior; since it is continually learning, recommendations are always up to date and improve over time. For example, in the summer, it would learn that “air conditioner” is becoming a more popular search and start to recommend it. In the fall, as searches for “air conditioner” decrease, it would no longer be a recommended search or product.
These product and keyword suggestions help users easily navigate to other products, serve as an effective way to disambiguate user intent, refine searches, and recommend related products.
If you are not ready to replace your entire search engine just yet, this is an easy improvement that yields quick conversion gains and saves shoppers from a bad search experience.
0-Result Pages are one of the worst experiences users can have on your site, especially when you sell the product they are looking for.
Typically, web stores have a 30% 0-Result Rate, which is high. And we mean really high - 1 in 3 searches won’t display a result at this rate and this often causes customers to leave the site, resulting in missed business opportunities.
When no results are found, Related Searches suggests keywords and products to users so they can refine/reformulate their query in order to find the initial product or another that suits their needs.
The suggested keywords are reformulations of the initial search, which serve as an alternate way to express user intent in case the product users are searching for is listed under a different name or the initial query contained a typo.
Related products are displayed if the search engine fails to find results when attempting to match the query text to product details. The main search engine tries to match queries exactly to products, while related products broaden the search in order to recommend products the user may have intended to search for. For example, if someone searches for “10GB USB stick”, which the shop doesn’t carry, there would be 0 results, but the reformulation would provide alternatives like 5GB USB
Related keywords on the Search Engine Results Page (SERP) help users refine searches and discover more products related to their initial query. For example, if someone searches for “door”, Related Searches may recommend “front door, wooden door, sliding door, door handles, door paint” as keywords and products. For example, if a user visits www.auchan.hu (a grocery store), searches for “tomato”, and adds that to their cart directly from the SERP, Related Searches will suggest similar keywords, such as potato or pepper, so the user can quickly navigate to other products. This increases the average cart value by directing users to more products; it appears even when a user’s original search yields results.
The keyword boxes on the SERP help users reformulate their initial query. Since the software learns from user behavior (based on click through rates) the most relevant results are displayed first. Without these suggestions, users have to manually type in a new search, sort through attribute filters in order to find a more specific product, or page through seemingly endless results to find what they’re looking for. This isn’t very effective because people give up looking for a specific product if they don’t see it on the first page - ideally as one of the top results - they will look elsewhere. SERP keyword boxes help users reformulate their search with just one click.
It is a good practice to put these navigation boxes both at the top and at the bottom of the SERP. We recommend only placing a few suggestions (4-5) at the top of the SERP and many at the bottom since this is where the user will end if they don’t find what they’re searching for and this gives them another chance to find a product that fits their search.
Lists of related keywords and products are generated daily based on user behavior. If a user searches for X, but doesn’t click on a product and then searches for Y, X and Y are then considered related or tagged as synonymous.
If someone clicks on a related search suggestion, that product/keyword’s relevancy would be boosted (by an amount you set) and would therefore be more likely to appear as a synonym for the original search. You can set how often those 2 terms search pattern must occur before it appears as a related keyword/product.
Unlike our other products, the more recent actions are not weighted more heavily than those occurring farther in the past.
Simply because one person executes a search pair does not mean it’s automatically added to the related searches list. You can set the number of times a sequence must be searched before it appears as a related keyword/product.
Our Related Search boxes can be placed at the top, bottom, or to the side of the SERP. You can opt to have all these boxes, 2, or just 1 and can set these preferences in the portal.
When determining which product/keyword to display first on the list of related searches, the frequency of the search pairs comes into play.
If people search for “computer” then “laptop” as well as “computer” then “Macbook”, and the “computer-laptop” sequence is more frequent, then the list of related searches for “computer” would be “laptop” then “Macbook”.
Related Products pulls data from keywords and clicks when determining suggestions. Keywords that lead to 0-results are automatically not included.
If someone searches for “computer” then “laptop” and clicks on a specific “Macbook” product, that “Macbook” would linked to the search term “computer” and would appear as a recommendation on subsequent “computer” searches.
Keyword suggestions are based simply on searches, while product suggestions are calculated by searches and product clicks.
If a certain query frequently leads shoppers to a 0-results page, you can find out what users search for next and rename products accordingly, so they appear for the first query shoppers usually type – this will help drastically reduce your 0-result page display rates.
When implementing Related Searches on your mobile site, we recommend displaying fewer related products and searches than you do on your desktop site. For example, desktop sites usually have 7 keywords on the top and 11 at the bottom of the SERP, but on a mobile site you should only have 4 at the top and 7 at the bottom.