The search function is a crucial component of your website that directly influences your sales numbers and significantly impacts the buyer’s journey. Unfortunately, many search boxes fall short of providing the top-notch user experience that modern consumers expect. But fear not. There are ways to refine your search bar and achieve better results, and one of these ways is through autocomplete.
Today, we’ll explore how you can leverage this search feature to your advantage, along with some best practices for implementing it effectively.
Before we delve into e-commerce autocomplete best practices, let’s clarify what this feature is. You may have heard it referred to as predictive search, type-ahead, search-as-you-type, or auto-suggest. You’ve likely encountered this tool when using search engines like Google.
When you begin typing in the search bar, autocomplete springs into action, offering multiple potential search queries based on what you’ve entered. For instance, if you type “sp,” you’ll see suggestions like “sports,” “space,” “spa,” and so on. Moreover, autocomplete can extend beyond individual words; it can suggest categories. For example, if you type “men’s shoes,” it can provide categories like “trainers,” “boots,” “sneakers,” and “running shoes.”
Why e-commerce sites should embrace autocomplete
Autocomplete isn’t merely a gimmick; it’s directly linked to the overall success of your e-commerce store. Here are some compelling reasons to implement autocomplete effectively:
Power of suggestion
Autocomplete taps into the power of autosuggestion, offering relevant and tailored suggestions based on various factors. We have prepared a separate page on the search box autocomplete suggestions for more information.
Eliminates "No results" pages
Autocomplete reduces the frustration of "no results" pages, which can deter users and erode their confidence in your website. Instead, it directs them to accurate search suggestions, ensuring they find what they're looking for.
Autocomplete can increase e-commerce sales by a staggering 24%. Longer, more specific search queries tend to convert better than short keywords. Autocomplete helps users find the precise products they're seeking, catering to those with a clear purchase intent.
It reduces search time by an average of 25%. Users looking for products can quickly find what they need, saving them valuable time.
7 Autocomplete best practices for e-commerce
Now that we’ve explored the benefits, let’s delve into the best practices for optimizing your autocomplete feature:
- Create a quick autocomplete feature – Speed is of the essence. Ensure your autocomplete function is lightning-fast, as modern users expect instant results. Slow autocomplete can be as detrimental as not having it at all.
- Add personalization elements – Tailor autocomplete suggestions to individual users by considering their search history, preferred language, and location. Personalization enhances the user experience.
- Correct typos – Implement typo correction tools to help users find what they’re looking for, even if they make spelling errors. This not only improves autocomplete performance but also enhances the overall search experience.
- Offer autocomplete for various query types – Don’t limit autocomplete to product-related queries. Cover all relevant user inquiries, including return policies, shipping options, payment methods, and more, to build trust with potential buyers.
- Create a usable autocomplete list – Maintain a balance between providing sufficient suggestions and overwhelming users. Avoid lengthy lists that require scrolling, especially on mobile devices. Ensure the autocomplete list is easily clickable.
- Add visual elements – Use visual cues to distinguish autocomplete suggestions from user-entered text. Bold styling, categorization, and product image thumbnails can improve the user experience.
- Implement merchandising suggestions – Highlight specific merchandise, such as products on sale or those with higher margins, in autocomplete suggestions. Ensure these suggestions are relevant to users’ searches.
Each popular query on your e-commerce site represents an opportunity to boost conversions. To harness this potential, gather data about your website visitors, tracking their behavior, interests, actions, and location. With this valuable information, you can tailor your autocomplete feature in your website search box to offer contextually relevant suggestions, saving users’ time and ultimately refining the search experience on your site.
Frequently asked questions
What is autocomplete and how does it benefit e-commerce websites?
Autocomplete, predictive search, or search-as-you-type is one of the advanced features that utilizes artificial intelligence algorithms and machine learning techniques to predict and suggest search queries in real time. For e-commerce sites, it boosts sales by providing specific product suggestions, speeding up search time, reducing frustration, and increasing the likelihood of conversions.
How does an autocomplete contribute to increased sales on e-commerce platforms?
Autocomplete increases sales by 24% on average. Suggesting relevant products based on user input caters to specific purchase intent, guiding users directly to the products they’re interested in. This personalized approach significantly enhances the chances of conversion.
What are some best practices for optimizing the autocomplete feature on e-commerce websites?
Optimizing autocomplete involves creating a quick and responsive function, personalizing suggestions, correcting typos, offering diverse query types, maintaining a usable suggestion list without overwhelming users, incorporating visual elements, and implementing merchandising suggestions. These practices ensure a seamless and effective autocomplete experience, enhancing user engagement and driving conversions.
How can e-commerce businesses utilize data to enhance their autocomplete feature?
E-commerce businesses can gather visitor behavior, interests, actions, and location data. By analyzing this data, businesses can tailor their autocomplete feature to offer contextually relevant suggestions. Utilizing data-driven insights ensures that the autocomplete function is finely tuned to user preferences, refining the search experience and ultimately driving long-term sales growth.