What Is Autocomplete in E-Commerce Search? A Complete Guide

What is autocomplete in ecommerce search

Here’s a staggering fact: Did you know that ecommerce sites with effective autocomplete functionality see a 25% increase in conversion rates compared to those without?

Well, these stats describe the obvious plus points of implementing autocomplete to enhance user experience and offer a range of valuable features that make site search functionality better, which ultimately increases the conversion rate.

Autocomplete provides real-time suggestions, it not only provides faster results but also reduces spelling errors and gives valuable analysis of popular search terms.

This blog post will dig deep into what, why, and how of autocomplete in ecommerce search. So, merchants can discover the full potential of this feature to take their sales to a new height.

So, let’s get the ball rolling.

What is autocomplete in ecommerce search?

Autocomplete is a feature in ecommerce search that provides real-time suggestions as they type in the search bar. It works quickly to offer contextual suggestions and help users avoid typing long, complex queries and typos. It is also known as search suggestions or predictive search.

For example, after typing the letter “m” in the search bar, it will show similar results in the drop-down like “Macbook” or “mobile”.

Most Popular ecommerce platforms such as Shopify, eBay, and Amazon have implemented autocomplete into their site search to improve the user experience.

Let’s talk again, what stats say:

According to a study by Econsultancy, sites with predictive search have a 9.01% conversion rate compared to sites without it, which have a 2.77% conversion rate.”

Why autocomplete is important in ecommerce search?

It’s a common sense thing that long-tail keywords have more conversion than short ones. It goes the same on Google and e-commerce store searches. Conversion increased by 15% with the addition of every single word. It’s because the shoppers who are entering long-term search(with deep details) queries are most purposeful in buying the product.

So, there’s a direct relation between integrated autocomplete and increasing sales. This was proved by a recent case study by Sypfu.

How you can implement autocomplete?

How you can implement autocomplete? Best practices

Add Personalization elements

Autocomplete suggestions should not be the same for everyone. To get more advantages from this feature, you should tailor it according to the user’s personal choices.

Did you know that 63% of consumers expect personalization as a standard of service from retailers?

Here are a few best strategies to implement autocomplete personalization ecommerce stores:

  • Utilize purchase history
  • Segment your audience
  • Incorporate location-based personalization
  • Dynamic personalization
  • Combine personalization with trend analysis

Brand Success stories based on personalization in search:

Which brands have completely benefited from personalization in search, let’s have a few examples:

Amazon: Amazon’s recommendation engine, powered by sophisticated personalization algorithms, drives 35% of its total revenue.

Netflix:  Similarly, Netflix’s personalized recommendations account for 80% of the content watched on the platform.

Add merchandising autocomplete suggestions

There are some strategic ways to showcase top-selling products and promotions on your ecommerce store and autocomplete suggestions are one of them. With merchandising autocomplete, merchants can categorize their products in the best way to elevate user experience.

Following are a few best ways to implement autocomplete suggestions on your ecommerce store:

  • Promote top-selling products
  • Highlight seasonal or trending items
  • Cross-sell and up-selling opportunities
  • Showcase promotions and discounts
  • Personalize recommendation

Real-life examples:

Target: The largest store in the US, uses strategic ways to display seasonal and trending products in its autocomplete suggestions.

Sephora: Sephora uses autocomplete to promote featured products, exclusive offers, and personalized recommendations to make the shopping experience smoother.

Add the right visual to improve the experience

The search on any ecommerce store is primarily about keywords or text, but focusing on visual elements doesn’t hurt the user experience. Using correct visual elements to guide visitors is the right direction. It also leads to a smooth user experience.

To do it right, the predictive section of your suggestion should stand out from the rest of the design. The easiest way to do it with the below points:

  • Use bold style for the suggested search
  • Add different sections by the suggestion type
  • Divide suggestions by page
  • Divide suggestions by categories and products

Many e-commerce stores depend only on visual imagery to make their purchases sell. It includes display product image thumbnails so the users can easily see the product they are looking for. They might also see different products that they like and make a purchase.

Offer autocomplete options for search queries outside of products

Many ecommerce stores focus only on the search box and the dropdown suggestions when working on their search engine. This is common because every store’s ultimate goal is to boost its sales.

However, it would be helpful to consider that your store’s visitors are not only interested in your products, but they can also go on the “about us” page to see the story of your brand. Or they can go to the blog page to find the latest information about new products or any other page to look for information outside of your currently available items.

For instance, some visitors want to learn about shipping options, contact details, return policies, special deals, and discounts on your business.

Make sure to make every search query covered with a relative suggestion list. No doubt, that’s your ideal goal, but it requires a lot of work and time. Learning more about your store, conditions, prices, and offers can only gain visitor’s trust and convert them into paying customers.

Technical overview of implementing autocomplete

There are several ways to anticipate users’ needs in an ecommerce store and implementing autocomplete in search engines is one of them. But how exactly do you implement this robust feature on your ecommerce store?

First things first, let’s delve into the technical nitty-gritty of implementing autocomplete. In convertopia, the initial steps involve choosing a search template. Make sure the template aligns well with the brand guidelines.

After choosing the search template, a few key elements should be considered:

  • Main theme
  • Last modified date
  • Status indicator
  • Actionable buttons

With convertopia, choosing the search template is the first step, the further steps are below:

  • Customize style
  • Publish
  • Preview
  • Installation instruction

The autocomplete implementation process by convertopia is as easy as seems in the steps above.

autocomplete implementation process by convertopia

Now let’s talk about a few best practices for implementing the autocomplete:

  • Optimize search index
  • Optimize query performance to ensure accurate search result
  • Properly structure & index your product data
  • Optimize search algorithm to handle complex queries efficiently

Wrapping it UP!

From personalization to merchandising autocomplete suggestions, the above best practices help you optimize autocomplete functionality and meet the unique needs of your target audience.

By implementing the autocomplete best practices in this guide, merchants can create a more engaging shopping experience for their customers. With autocompletes, ecommerce business owners can connect with audiences in meaningful ways and drive business growth. Whether it’s highlighting top-selling products, offering personalized recommendations, or showcasing promotions autocomplete empowers ecommerce businesses in every possible way.

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