Why Semantic eCommerce Search is not really necessary

| Elza Joseph

What is the first thing a customer does after landing on an eCommerce website? They browse or search! Most of the time, customers know what they want. They type in the eCommerce search box and press “Enter.”

This simple feature of “search” can make all the difference. It can help you become a success or cause low eCommerce search conversions. So if you want to have a competitive advantage and succeed despite so many eCommerce stores on the digital map, you need to ensure that your search feature works perfectly.

Today there is a lot of buzz about “semantic search” in the eCommerce arena. What is it? Do you need it? Is it just an unnecessary hype? Read on to know more.

eCommerce search

What is Semantic Site Search?

Semantic search is an AI-powered search that also has natural language processing features. It shows relevant results through correcting typos, showing similar products, finding synonyms, etc. It also helps in understanding the meaning of the search carried out by the customers by attempting to interpret the intent.

Google, a contextual-based search engine, uses semantic search, but how useful is it for an eCommerce store? It might not be at all. Especially if you are a small or mid-sized eCommerce business.

Why You Don’t Need eCommerce Semantic Search

1. Disappointing Data

Less than 0.07% of eCommerce searches are semantic searches. This means that out of every 1000 searches, only 7 are semantic.

If you focus on making your eCommerce site search semantic, you are only catering to 0.07% of your customers, which means you will get a low return on your investment and a high search bounce rate. There might be other search features that may cater to 70% of your customers and bring in significant revenue.

2. Not What Customers Want

Customers are more likely to click on predictive suggestions than type a semantic query, as shown in the picture below.

amazon search

Image Source: amazon.com

Your customers prefer a smart, predictive search. They also prefer typing in short queries versus full semantic queries. With smart search and short queries, the intent is pretty evident, and there is no need for an interpretation through semantic search.

Another challenge that doesn’t work in favor of a semantic eCommerce search is the vocabulary incapabilities your customers might have. Your eCommerce store might be in English, but your customers may not be native English speakers. So they might not type in exactly what they want, and a semantic interpretation of their query might lead to irrelevant results. This leads to low eCommerce site search accuracy as searches that are semantic in nature are often not precise.

3. Not Ideal For a Product-Based Database

Google, which is a contextual database fed search engine, can benefit from semantic search, but eCommerce is about products that have graphics and videos at their core.  It’s more about how a product looks than about the study of the words typed in and linking it to relevant results.  Most visitors know exactly what product they want, so incorporating semantic search serves only some of your customers, not all. It’s irrelevant.

4. Sub-Optimal Utilization of Resources

Like we read before, not even 1% of product searches are semantic. To get NLP-based semantic capabilities, you need a system that processes results in less than 50 milliseconds. Otherwise, it slows down your search, leading to a high search bounce rate.

To get these capabilities, you need to invest a large amount of capital. This heavy investment will not be offset by the revenue as semantic search serves some versus all. This affects the broader picture. A focus on semantic search might derail investment in other important must-have eCommerce elements.

low search conversion

5. Affects Personalization Efforts

Your customers want personalized results. A semantic query is complex, and because of this, it may lead to inaccurate personalization for eCommerce. This doesn’t align with tailored advertising/marketing strategies and won’t help you get more conversions.

Choose Relevant, Data-Driven Search Instead

Google search

We have seen why investing in semantic search is a waste of time and resources. It isn’t one of the eCommerce site search best practices.

Instead, having a data-driven search solution, like the one offered by Tagalys, that uses the power of human + machine intelligence to optimize conversions, can work wonders.

Tagalys‘s site search services offer intelligent, accurate, and merchandisable search results. Pin searches, display popular searches, get intuitive suggestions, and much more. You can offer trending searches by location too! Contact us now to empower your eCommerce site search.

References:

  1. https://www.tagalys.com/blog/semantic-search-for-ecommerce-site-search/
  2. https://www.freepik.com/free-vector/search-engine-concept-illustration_5357330.htm#page=1&query=search&position=4
  3. https://www.researchgate.net/figure/Advantages-and-disadvantages-of-the-main-semantic-QE-approaches_tbl1_330605622
  4. https://www.bypeople.com/semantic-web-pros-and-cons/
  5. https://www.freepik.com/free-vector/magnifying-glass-with-searcher-flat-style_2034687.htm#page=1&query=search&position=3
  6. https://www.freepik.com/free-vector/bankruptcy-concept-illustration_7321329.htm#page=1&query=loss&position=2