What is Predictive Search and How it Works

Predictive search has become a staple feature in e-commerce, with customers automatically expecting that an e-shop simply has it. Today, 80% of e-commerce sites use predictive search to help users find what they need more quickly.

But not all predictive search solutions have UX tweaked to perfection.

In this article, we’ll cover what predictive search is, how it works, its differences from autocomplete, and, most importantly, how it should function for an optimal user experience.

How is it different from autocomplete

Predictive search, autocomplete, autosuggest, autofill, and search-as-you-type are all terms that are used interchangeably. You can find various definitions explaining subtle differences between these concepts, but in broader sense, they all serve the same purpose—to predict what the users are looking for and come up with relevant product suggestions that will allow clients to find what they need in just a few seconds.

How it all works

While the predictive search process might seem simple at first glance, a lot is happening in the background to make the suggestions possible.

Predictive search systems learn from search patterns to suggest the most relevant phrases based on what others are searching for. The whole process involves steps like:

1. Tracking popular phrases

Predictive search keeps track of frequently searched terms. If thousands of people search for “running shoes” every day, it knows this is a popular phrase. So, when you type “sho…,” “running shoes” might appear as a top suggestion, as it’s likely relevant to what you’re looking for.

2. Recognizing context

Predictive search also considers common contexts. For example:

• If many users look for “comfortable shoe brands” or “durable shoe brands,” starting with “shoe br…” may bring up “shoe brands” or specific brands like “Nike” or “Adidas.”
• Seasonality matters too. In winter, “snow boots” might rank higher, while “sandals” might appear in summer.

3. Learning from search refinements:

Predictive search also learns how users refine searches. For instance, if people often search “shoe” and then add “size chart,” it might suggest “shoe size chart” when someone starts with “shoe s…,” helping users get there faster.

Predictive search learns from users by noting which phrases are frequently searched, which get clicked most, and how users adjust their searches, creating a helpful, context-aware experience.

How predictive search helps modern e-shops

Predictive search is now a must-have feature for all e-shops. Its goals are:

1. Search effectively: Display exact products when users search by product name or code, ensuring they quickly find what they need.
2. Direct users to category pages: Quickly guide visitors straight to the relevant category, even at deeper levels of the site.
3. Complete partial queries: Show relevant categories and brands when users only know part of a product name, helping them find the right product.
4. Minimize typing: Especially on mobile, predictive search saves time by reducing the need for full typing.
5. Provide instant feedback: Help users confirm the store has the products they want by displaying helpful suggestions as they type and quickly allow to reformulate their search if not.

There are numerous benefits for an e-commerce business if the predictive search is able to deliver.

1. Improved user experience

Offering a better search experience results in an improved user experience. Visitors who can use the responsive search bar and find what they’re looking for quickly and easily instantly become happy customers. Therefore, a quality predictive search function can improve the user experience and motivate your customers to return.

2. Higher conversion rate

By ensuring your visitors can find what they need, you’re automatically increasing the conversion rate of your business. As a result, customers won’t leave your website frustrated. Instead, they’ll place an order and will probably come back again if they’re satisfied with the products and service, which leads to a higher conversion rate.

3. Better customer service

Providing relevant queries in the search form and ensuring the visitors are satisfied with the search option leads to better customer service. Not only does good customer service support the buyers, but it also helps e-commerce businesses gain a better understanding of the customers. Staying in touch with your target audience has genuinely never been easier.

4. Greater competitive advantage

With an improved user experience, higher conversion rate, and better customer service, an e-commerce business can quickly secure a competitive advantage over other companies in the same industry. Not all modern e-shops are equipped with a faceted search feature, so this is a perfect opportunity for companies to implement something that’ll make them stand out.

Useful tips and best practices for predictive search

Leading e-shop boast of autocomplete with several features you didn’t even think of. Here are some tips, best practices and functionalities your e-shop shouldn’t miss as well.

1. Make your search bar visible

If your site visitors know exactly what they’re searching for, they will likely use the search function to find the products quickly. Therefore, your search bar needs to be visible and easily accessible to everyone.

Some e-commerce businesses include only the search icon, which isn’t the best idea. Not only is it less visible than a search bar, but it also requires visitors to click on it if they want to use it. Remember to include the entire search box and make it easily accessible from every page on your website for the best results.

2. Offer relevant suggestions

The more detailed your product suggestions are, the better. Since the purpose of the predictive search is to offer customers products, they might be interested in; the recommendations should include the product’s name, brand, product category, thumbnail, and any other details you might find crucial.

Having all this information available at their fingertips makes visitors more likely to check out the recommended products and even purchase them.

3. Include the autocomplete feature

Autocomplete is another helpful feature that’ll make a difference for your clients. The purpose of autocomplete is to provide automatic query suggestions as soon as the user starts typing. By following autocomplete best practices, you can ensure these suggestions are relevant and helpful. Autocomplete cuts the time required for a search query and speeds up the whole process since clients don’t have to finish their queries manually before getting what they came for.

It’s important to say the autocomplete feature is almost everywhere nowadays. However, with that said, modern e-shops are often expected to have autocomplete feature as part of their search process, so not having it could be a huge disappointment for contemporary online shoppers.

4. Use artificial intelligence for query understanding

The power of artificial intelligence is everywhere around us. All newer technologies and solutions heavily rely on AI, and predictive search for e-commerce businesses isn’t an exception. When your site visitors enter a search term, you want to make sure they get exactly what they’re looking for, even in the case of long-tail keywords.

Basic systems might fail to understand more complex queries, but that’s what AI is for. AI and ML can understand even the most complicated queries and provide customers with instant search results. With such solutions by your side, increasing the conversion rate is a piece of cake.

5. Add synonyms and slang to the database

How many times did you search for a particular product only to find out it was listed under a different name? A high-quality predictive search tool can recognize various terms as synonyms or slang for certain products and thus help customers find what they need, even if they use an entirely different term.

Let’s say you’re looking to purchase a new sofa. You enter the term into the search box, but nothing comes back. Naturally, you’ll leave the site thinking the brand doesn’t sell any sofas. However, adding synonyms and slang to the database can result in a completely different experience. So, whether you use the term sofa, couch, loveseat, divan, or any other related word, you’ll find what you’re looking for.

6. Count on typos in the search input

Did you ever miss out on a good product just because of the simplest typo? We already mentioned that people use the search box to find a specific product quickly. That means they’re often in a hurry, and typos aren’t uncommon in such instances. Nevertheless, e-commerce businesses probably double-checked how they named their products before launching them, and they shouldn’t contain any typos.

Fortunately, the predictive search can spot typos and recommend products closest to the inserted keyword. This feature is a nice touch for every e-commerce website and will motivate more customers to continue shopping on your website.

7. Pay attention to product relevance and ranking

If you have a lot of items in your assortment, using a single keyword can result in thousands of product matches. If that happens, how can you ensure the customers find what they want, considering they probably won’t be going through all of the suggested products?

Product relevance and ranking are here to sort all of the matches accordingly. Most e-commerce brands sort their products by popularity, so all of their best-sellers are on top. That way, they offer their best products immediately and increase the chance of a customer going through with the purchase.

8. Don’t compromise the search speed

Having a wide array of products certainly has its pros and cons. One of the significant disadvantages is the decreased search speed when clients are looking for a specific product. Naturally, the more products you have, the longer the system will take to go through them all and select only the relevant ones.

However, that doesn’t have to be the case. Many modern solutions offer impressively fast predictive search solutions that don’t require e-commerce brands to sacrifice their search and render speed to provide relevant product suggestions.

Predictive search examples

The e-commerce space is full of great examples of predictive search widgets that are superquick and offer top-notch user experience.

11teamsports

11teamsports uses predictive search with a trademark Luigi’s Box design. This autocomplete includes years of our dedicated research and tons of work of our developers and UX designers.

Muziker

Predictive search on Muziker website offers popular result, direct link to categories, brands, and most popular results with just a half of the query typed in.

Pilulka

Pilulka is an online pharmacy popular in Central Europe. Their autocomplete includes a rich array of information. Popular queries, products, brands, and categories are dynamically accompanied by articles or product lines. Notice how they also offer Add to Cart button, making it easy for customers to quickly shop for popular products.

Conclusion

Predictive search is making its way as one of the crucial additions for every modern e-commerce business. As the ultimate way to help potential and existing customers find what they want to purchase quickly and easily, solutions offering this feature are certainly in high demand right now.

If you’re running an online shop, predictive search is exactly what you need for your business. Besides improving the user experience, it’ll also improve your conversion rate and increase sales.

Frequently asked questions