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A study highlighted by eConsultancy showed that a comprehensive search could improve conversions by 4.63% compared to the websites’ average conversion rate, which is just 2.77%.
It shows customers convert 1.8 times more effectively when websites use the intelligent search functionality.
We want to focus on predictive search, one of the most effective search techniques of all the ways that search is utilized.
Predictive search has shown a 20% increase in customer engagement—also, an 11% increase in customer interactivity when implemented on eCommerce sites.
Predictive search is nothing but providing auto-suggestions or eCommerce search autocomplete based on the customer’s input. These suggestions are based on the product database and the customer’s browsing history.
The eCommerce search autocomplete 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 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 “black 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 eCommerce websites leads to poor customer loyalty and conversions.
So, a simple search feature alone is insufficient to improve your website’s conversion rate.
Instead, predictive search technology that uses data intelligently is mandatory to enhance product discovery and customer engagement.
In reality, a great search starts with the search box placement and includes intelligent functionality.
The search box position varies with each eCommerce site, so we’ll only discuss the vital functionality to understand which works best for your product and eCommerce store, and some predictive search examples.
Predictive Search Best Practices:
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 quickly help customers shortlist the products of their choice.
This drastically reduces product discovery time, as customers can easily navigate to the desired product.
Including images inside the search result is another excellent way to help customers visually relate to the product.
Let’s look at the below search result for ‘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, 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 navigate you to the place of interest easily.
This dramatically 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 to the most popular product.
Adopting the correct predictive search functionality can significantly improve your customer engagement rate and product visibility.
Why should you use predictive search in your eCommerce store?
Customers enter your website with a spree to shop. Do you know that around 64% of shoppers use the search option to acknowledge their “I want to buy” moment.
When if they don’t find the right product before their enthusiasm dies, you lose a sale. The best way to solve this problem is using predictive search. It optimizes and reduces the search time.
Shoppers may not know what words to use in the search bar to find the product. By displaying popular search terms, you can help them understand the site better and show them relevant results.
Remember, 39% of buyers are motivated by relevant searches.
Excellent user experience creates more sales and happy customers. But when it is difficult to find the products, customers get frustrated. This pulls down your user experience score.
Statistics state that the site search conversion rates can be up to 50% more than the average, but more than 12% of shoppers bounce to competitor sites after an unsatisfactory search.
The predictive search feature can help you out from this. It offers accurate suggestions for shoppers, helping them find the product in minimal time.
You can use predictive search to show products on promotion and sales automatically. By this, you show the relevant results and promote specific products. It highlights the products you want to sell instantly, draws more traffic, and offers an enhanced shopping experience.
When the predictive search is used effectively, you can ensure shoppers are directed to available products. You can reduce the display of no results found or out-of-stock pages. This way, you never disappoint your customers.
You can achieve this by integrating predictive search with your inventory.
The predictive search uses customers’ data to suggest the right products and services.
This includes their past search history, search terms, purchases, and more. Thus, the predictive search displays results around the shopper’s current search intent.
This way, each user gets optimized results based on their interests.
Want to know how to implement predictive search? Or need help help improving your customer decision process? Contact our team today!