The Role of Autocomplete Suggestions in User Experience
One feature that has proven to enhance user experience is autocomplete suggestions, also known as predictive search. This tool is powerful. It speeds up searches and improves the user experience by making navigation easier and more intuitive. We’ve all seen it, we’ve all used it and according to google, their own implementation of autocomplete “predictions” saves users 200 years of typing time… a day.
We’ve been working with Decksaver to improve their UX and simplify their customers’ journeys from first visit to purchase. Refining the search experience has played an important part in this.
The Power of Autocomplete
Autocomplete suggestions work by predicting a user's search query as they type. They offer completions to their input based on search history, popular trends, contextual data, and available product or content catalogues. This feature is particularly useful in e-commerce, where a vast array of products can make finding a specific item challenging. By predicting what a user is looking for, autocomplete can streamline the search process, making it quicker and more efficient.
Users no longer need to type out their entire query, saving valuable time. It reduces the likelihood of misspellings, leading to more accurate search results and it can expose users to products they might not have found otherwise. It’s no surprise that, according to a study by Baymard Institute, 80% of ecommerce sites provide this feature. However, while autocomplete is a powerful tool, its effectiveness depends on its implementation.
Best Practices for Implementing Autocomplete
When looking to introduce or improve autocomplete suggestions, here are some things to consider:
- Number of suggestions: Keep the autocomplete list short. Too many suggestions can overwhelm users and be counterproductive. Aim for a balance between providing enough options and maintaining usability and consider tailoring the amount of results based on screen size.
- Highlighting Active Suggestion: Use typography and colour to help users see the part of their query that was auto-completed. It makes the query more readable and efficient.
- Interaction Methods: Desktop users typically use a mouse and keyboard, so ensure keyboard navigation is possible. For mobile or tablet users, ensure the touch targets are large enough to select.
- Differentiate between result types: If different types of data are suggested in the search response, make that clear to the user. For example, style product category suggestions differently from product suggestions. This helps users distinguish between the two and assists with their decision process.
With the right approach autocomplete suggestions significantly enhance user experience by offering useful results to users, especially in e-commerce. We’ve seen positive results with Decksaver’s site search and are continuing to explore further ways to refine it to improve their customer journey.