Autocomplete search is a crucial and fundamental part of any eCommerce experience. In order for it to be optimized, it should overcome two challenges: speed and ranking. When done well, it will increase conversion rates, boost customer satisfaction and keep shoppers coming back for more. Let’s take a look at some best practices to achieve this.
What Is Autocomplete Search?
Autocomplete search is a feature that suggests and predicts keywords or phrases that users may be searching for when they start typing into the search box. It works in real-time, using machine learning based on initial characters typed. It’s an efficient and intuitive system that saves users time and effort. Without having to type the whole word in, users can find their desired result.
The Difference Between Autocomplete & Autosuggest
Autosuggest, or suggestive search may suggest words or phrases for you to choose from. Autocomplete will complete the entry for you without you having to finish typing. It will predict what you are looking for, as soon as it knows you want to start looking.
Best Practices
In order to have an optimized autocomplete search, consider the following best practices:
Ranking System
Autocomplete suggestions can be displayed according to a ranking decision that you decide upon. Suggestions can be displayed based on a series of different ranking strategies such as:
- Their relevance to the users search query
- Popularity of the products being searched
- Previous user behavior
- Store rules and ecommerce merchandising rules
Choosing in what order your shoppers will see the autocomplete results can have a big effect on your business. The sooner shoppers see products, the more likely they are to buy. Having a ranking strategy is therefore definitely a good idea.
Effective UX Design
The way your autocomplete looks needs to be optimized for your business in order to make it more user friendly. It should be clear, readable and simple. Don’t overcomplicate things, the more intuitive the system is, the better. It should also be easy to find and accessible to all users. The point is to speed things up, not overcomplicate things.
Keep it clear, with clear labeling and instructions. Refrain from using industry jargon that might be confusing for regular shoppers. Make sure that the autocomplete terminology will be understandable for anyone.
Omnichannel Focused
We all know the importance of omnichannel eCommerce. Since more users than ever are using their mobile devices to shop, your autocomplete must be optimized for the phone. It also should be optimized for mobile apps, or for any other way that people will access the search. If the autocomplete only works on your web store, this won’t produce the best results.
Visual Depth
With the advances in technology, there is the option to add interesting visual depth to your autocomplete. Take advantage of these and add optimized features. This could be adding a drop down menu with high quality images. You could also include promo tiles in your dropdown search. Or you could use other borders and icons. As long as it doesn’t compromise the accessibility and usability, it’s a great idea to be creative.
Using Analytics
Having an optimized autocomplete search is great for improving your customers’ shopping experience. However it can also be greatly beneficial for you in terms of understanding your shoppers’ needs better. You can use analytics to monitor product performance, and see what people are searching for. This data can help you make better decisions in the future.
By examining factors such as conversion rate, bounce rate, click through rates, you can gather valuable insights. These can be used to continue to optimize your autocomplete search. They also can help to boost sales.
Powered By Artificial Intelligence
There are more and more AI systems that can help ensure your autocomplete search is to a high standard. Natural Language Processing (NLP) means that shoppers can search in language that makes sense to them, and they will still see the results they want. This also means that no queries will be lost as a result of spelling mistakes or typos. Synonym and antonym search can also be incorporated.
Machine learning can also help to understand user behavior to help predict their search. This can help to create personalized results improving customer satisfaction.
Conclusion
Autocomplete search is a great addition to any eCommerce store. When these best practices are followed, you will be able to see improved results in different areas. Customers will be saved time and effort, and you will see more products being sold.