Shopify Ecosystem

What Merchandisers Should Know About Ecommerce Search Algorithms

what-merchandisers-should-know-about-ecommerce-search-algorithms

Is the ecommerce search algorithm on your store a mystery to you? It shouldn’t be. You may not realize it, but search algorithms have a direct impact on your online shopping experience, as well as your bottom line. Online retailers need to understand how and why certain products show up in search results to ensure shoppers can find exactly what they’re looking for. Read on for a quick-and-easy guide to everything you need to know.

What is an ecommerce search algorithm?

For most of us, the concept of algorithms first surfaced with the advent of Google and its ability to turn search queries into a carefully sequenced list of the most relevant results. Fast forward to today and algorithms have not only firmly entered the public consciousness, they have become the subject of much greater scrutiny as we question how and why we are served certain content online. 

We may be increasingly aware of the role that algorithms play in our online experiences, but it’s easy to overlook how they factor into ecommerce. And yet, ecommerce product search algorithms have a significant influence on your store. 

Without getting too technical, an ecommerce search algorithm can be defined as the process by which results are retrieved and displayed in response to a search query. From a user perspective, algorithms essentially dictate how easily a shopper finds accurate results, or whether they find relevant results at all. 

If this sounds like a concerning level of power wielded by an inscrutable technology, fear not. With the right search solution, you can optimize and control your ecommerce search algorithm with minimal technical skills. Below are the questions you need to ask of your search solution as an ecommerce manager or merchandiser.

Does your ecommerce search algorithm understand semantic search?

An algorithm that responds to the intent behind various types of search queries is essential. Your search bar should understand that a user searching for a “red Nike shoe” wants a shoe, while a user searching for “red Nike shoe laces” wants an accessory for Nike shoes. For each search, the shopper should be presented with a specific set of relevant products, instead of a broad collection of all “Nike” results that are only loosely related to the search query. 

Semantic search (sometimes also referred to as natural language processing) means your search bar can assess the subtleties in a search term to identify which words are product categories, and which are attributes. 

Search Results: Red Nike Running Shoes - Attributes, category, product type

What’s more, an intelligent search algorithm will automatically account for things like spelling errors, plural and singular search terms, and special characters such as measurements.

Bonus tip: Remember, an ecommerce product search algorithm is only ever as good as the data it has to work with. No matter the query, the quality of your results will ultimately be determined by the cleanliness and standardization of your product data.

Does your ecommerce search algorithm learn from user behavior? 

An ecommerce search algorithm that can discern between product types, categories, and attributes is fundamental, but an intelligent search solution doesn’t stop there. Your algorithm should be capable of machine learning, so your search results become more relevant over time. The more shoppers interact with your search, the more your algorithm should learn about your customer behavior, allowing it to elevate the best performing products.

While this optimization will happen automatically with an intelligent search tool, this is also where the merchandiser’s intervention can come into play. As your search solution gathers intel on shoppers, you should gain the ability to instruct the algorithm on what to do with that data, as covered in the next section. 

Can you override the algorithm when you need to? 

Occasionally, you may want to strategically manipulate search results to meet certain objectives. Perhaps you want to boost on-sale products to the top of search results for a certain period of time. Or, maybe you want to implement a rule that your house brand always appears first. Without the ability to override your default ecommerce search algorithm, these types of adjustments aren’t always possible – at least, not without the assistance of your IT team. 

As an ecommerce merchandiser, search intelligence and automation eliminates a lot of manual, time-consuming work. Yes, it’s convenient to let automation take over, and yes, an intelligent solution will do most of the heavy lifting with minimal intervention. But, the ability to leverage human knowledge about your store, your brand, and your customers when you need to is invaluable. 

Take control of your ecommerce product search algorithm

When implementing site search, it can be tempting to leave the ecommerce search algorithm to its own devices. For the most part, with a solution that features semantic search and machine learning, you can trust it to perform. However, it’s always worth retaining control over search results so you can make calculated alterations on the fly, without enlisting the help of a developer. Interested in learning more? Check out Searchspring’s intelligent site search.

Special thanks to our friends at Searchspring for their insights on this topic.
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