October 26, 2016
A study highlighted by eConsultancy showed that a comprehensive search can improve conversions by 4.63% when compared to the websites’ average conversion rate, which is just 2.77%. This shows customers convert 1.8 times more effectively when websites use intelligent search functionality.
Of all the ways that search can be utilized,we want to focus on predictive search, one of the most effective search techniques.Predictive search has shown a 20% increase in customer engagement and 11% increase in customer interactivity when implemented on eCommerce sites.
Predictive search is nothing but providing auto suggestions based on the customer’s input. These suggestions are based on the product database, as well as the customer’s browsing history.
The auto-complete feature was initially started by Google in 2008 and started getting popular amongst eCommerce websites in 2012.
Almost 80% of eCommerce websites have an auto-complete feature in their search option, but they fail to provide the necessary customer experience needed to fully impact the customer’s buying decision.
For example, imagine that a customer wants to search for the item ‘Black Tunic’:
Site #1 returns the result:
If they don’t notice the error in spelling, the customer exits immediately. Even if they find the mistake, the customer gets frustrated as they need to re-enter the search term.
In another scenario, a customer searches the term “blck tunic” in site #2 which returns the following result:
The customer continues hunting for their favorite black tunic without any search hurdle or delay in looking for products.
Sadly, there are many scenarios where even when the user searches for ‘black tunic’ the result that is returned is either ‘No result found’ or irrelevant products. This leads to customers leaving the website without making a transaction.
This lack of user engagement in such eCommerce websites leads to poor customer loyalty and conversions. So, to improve your website’s conversion rate, a simple search feature alone is not sufficient. Rather, predictive search technology that makes intelligent use of data is mandatory to improve product discovery, as well as customer engagement.
In reality, great search starts with the search box placement and includes the intelligent functionality. The position of search box varies with each eCommerce site, so we’ll only discuss the important functionality to understand which works best for your product and eCommerce store.
Imagine that your eCommerce store has plenty of categories with similar products listed in them. A customer searching for’blue jeans’ could be looking for any gender and when the search returns a combined result, it could be a confusing ordeal for customers.
Instead, a predictive search box that recommends the suggested products,along with specified categories and brands, will easily help customers to shortlist the products of their choice. This reduces the product discovery time drastically, as customers can easily navigate to the desired product effortlessly.
Including images inside the search result is another great way to help customers visually relate to the product. Let’s look at the below search result of ‘white bed frame.’ By just keying in the keyword, customers can visually decide which products they like and go ahead with their choice.
The major drawback is that it is not possible for all kinds of eCommerce websites. If you have too many similar products, then you might miss out on showcasing other products of interest to customers. So carefully evaluate if your eCommerce store needs images displayed in the search result.
Improve visibility of your best performing products by pre-populating keywords in the search box field. By just clicking on the search box you get a list of pre-populated keywords to easily navigate you to the place of interest. This greatly improves customer engagement within your eCommerce website.
This works best for huge eCommerce stores with thousands of products on display. Customers can shortlist their search based on their budget, size, color, needs, etc. These narrowed down results help customers make a quick purchase decision by decreasing the product discovery time.
You can start cross-selling from within your eCommerce search engine. Engage customers better by recommending popular products when they start searching for the products of their choice. This helps you improve conversions, as customers are attracted towards the most popular product.
Adopting the right predictive search functionality can greatly improve your customer engagement rate and product visibility. Need help improving your customer decision process and your eCommerce conversion rate? Then check out our CRO Calculator and contact our team today!