One of the most essential factors for any E-Commerce store is the search feature. It is estimated that about 30% of customers will go strictly to the search box to find what they are looking for. That means that about one-third of the visitors to your site will ignore every other feature on the front page in order to use the search box and find exactly what they are looking for. For us, this means that the search box needs to be the most important feature of our site. Let us look at some ways that we can optimize our search capabilities.
We can utilize Natural Language Processing
NLP is a search algorithm that works under the assumption that human beings make mistakes. For example, if a customer using the search box to search for a mobile phone instead enters the term “mobile phone” their search result may not have much success. As a result, they will not find what they are looking for and may choose to shop elsewhere. With natural language processing, “mobile phone” would instead return results for mobile phones and give customers the product they are looking for instead of an error code. The alternative to NLP, that is, text-based searches and keyword matching algorithms do not have the same capacity to detect the human error. Hence they are left matching exact syntax and lining up keywords.
Differentiating Syntax and Semantics
Online searches boil down to two things, that is syntax vs semantics. Syntax-based searches are powered by exact keywords, brand names and other singular names. Here, the search engine returns results that have syntactically matched with the entered terms. Semantic search is more attune to the way people speak naturally and connects searches to concepts rather than keywords. As such, someone searching for “shoe and socks combo” will get a result that reflects what they want despite there being no applicable keyword in their search term. This type is search is powered by natural language processing.
Making Search central to our Site
It is easy for any E-Commerce store to grab customers attention when they are on the site and show them things they may like. But unless we lead customers to what they need, the sale will almost always be lost. The search function of our website can be considered the best salesman we have. Just as a salesman in a brick and mortar store would take a customer to a product, the site search must offer relevant results to a query. One of the biggest criticisms for an online store vs. a brick and mortar store is the lack of face to face interaction. How do we get the help we need with anyone to deliver it, and what if we need to find a specific product and need to describe it to a salesperson? Once upon a time, they may have been valid criticisms, with outdated search engines and keyword search algorithms. But thanks to the innovations set out by natural language processing, these criticisms are no longer valid.
Avoid missing out on conversions because of textual search
According to E-Commerce industry giants such as BigCommerce and Magento, the average conversion rate across all online store is only three to five percent, and getting your E-Commerce stores conversion rate to the average rate is a difficult task in itself for most stores. While many online retailers will keep pushing with new marketing campaigns and investing in gimmicks that push sales, the smart E-Commerce operators will look towards more sustainable, passive ways to boost conversion rates, i.e. Semantic Search. In order to generate better conversions through our on-site search, we must move away from standard text and keyword-based algorithms that do more harm than good for our website. If you are one of the many online retailers using platforms such as Magento, much of the E-Commerce interface is already provided, but the supplied search functionality may leave you wanting more. Replacing the stock search engine with semantic search will give you the ability to tap into potential conversions.
Learning about the Customer
Online retailers are always looking to learn more about their customers. This involves gathering enormous amounts of data regarding each customer and interpreting the data. Here, a search engine based on natural language processing comes in handy as a tool to learn even more about our customers. Some would argue on what the most important piece of information that we can learn about a customer is. An e-mail address would allow us to keep in contact with the customer, while demographic details may help us fine tune our recommendations. But what is even better is to understand what exactly the customer wants. The above-mentioned details will not be of any use if the customer is looking for something specific from our store. By using the data from our search engine, we are able to successfully predict our customer's needs. If your site is not using natural language processing, you may be missing out on more sales than you think. Whether those lost sales are worth the effort for you to upgrade your search engine is only for you to decide.
