Predictive search: how it works and why you need to use it

November 12, 2022
Search predicting what user might want

If you’re into science fiction, you know that stories set in the far-flung future often feature machines that can communicate with people simply by reading their thoughts, without any physical form of communication being necessary. 

While we’re not quite there yet, we’ve definitely come a long way when it comes to simplifying how people interact with computers and programs, primarily through various applications of Artificial Intelligence (AI). One application of AI that has percolated into our everyday lives is something called ‘predictive search’ (known by several other names as well, including ‘autocomplete’ and ‘autosuggest’).

Predictive search is something you’ve almost certainly encountered and benefited from many times already. Whenever you go to some kind of search bar (e.g. on Google, in online stores or in your browser) and start typing something in, it’s likely that a dropdown menu will appear with a list of suggestions. This is predictive search working its magic: each of those suggestions is an attempt to predict what you might be looking for.

If you’re an online business owner, incorporating predictive site search into your website is vital. Here are two key reasons why:

Let’s look at this useful functionality in more detail: let’s understand how it works and explore the best ways online business owners can make use of it.

The nuts and bolts of predictive search

Like search engines in general, predictive search or autocomplete also relies on complex algorithms. As hinted at above, these algorithms often involve the use of AI. In addition, such algorithms may also depend on various techniques drawn from the domains of Natural Language Processing (NLP) and Machine Learning (ML). NLP techniques aim to enable computers to understand naturally phrased human language, while ML techniques aim to allow computers to get better at a particular task by analyzing large amounts of relevant data.

What kinds of factors do predictive search algorithms take into account to produce their output? Some such factors are:

The importance of implementing predictive search

Implementing predictive search or autocomplete comes with an array of benefits for online business owners. Some of the most important ones are:

1. Increased time spent on site

By ensuring a better search experience for your potential customers, predictive search gives them more of an incentive to stay on your site and look for the products or content that they’re interested in.

2. A higher conversion rate

The more time visitors spend on your site, the more likely they are to find something they like and convert (i.e. buy a product or view a piece of content).

3. Lower likelihood of ‘No Search Results’

Typos and searches for items that your site doesn’t have can lead customers to the dreaded ‘No Search Results’ page, which is an annoyance. By providing automatic suggestions, predictive search can maximize the chances of your visitors searching for something that will actually produce useful results.

4. Better content/product discovery

Lastly, predictive search can also serve as a gateway to initiate your visitors into the kinds of products or content that your site provides.

Best practices for an impactful predictive search experience

Not all site search engines come equipped with predictive search capabilities. Thus, online business owners who wish to provide predictive search must first find and integrate a site search engine that does provide this functionality. Moreover, most such engines allow you to configure predictive search to suit your business needs.

Here are some best practices to keep in mind when creating a predictive search experience for your site visitors.

1. Optimize search suggestions based on user signals

Personalizing search suggestions is also very important these days, as site visitors have come to expect it thanks to their experience with popular search engines and platforms. Various user signals, such as location, search history, age, gender, past purchases, etc. can be used effectively to offer highly relevant search suggestions, especially if a site search engine uses AI and ML behind the scenes.

2. Display related content and products as well

Online business owners can leverage predictive search for boosting their content or products as well (referred to as ‘merchandising’ in an ecommerce context). In other words, in addition to simply text-based search query suggestions, the dropdown menu that appears can also include a small section that shows a featured product or piece of content. This can help draw the attention of site visitors to particular items that are known to be good revenue generators, thus improving your bottom line.

3. Ensure a good mobile experience

Given that mobile usage and mobile search is booming, online business owners today know that optimizing for mobiles is critical.

When using predictive search on a mobile, the suggestions dropdown menu can easily take up a significant chunk of screen real estate, with the keyboard taking up another major chunk. Thus, good UI and UX design is required to ensure that mobile autocomplete is useful rather than being an annoyance (these points also apply to desktops): 

Predict your way to a thriving business

To sum up, predictive search brings with it several benefits, chief among which is an enhanced customer experience. This, in turn, can drive up the conversion rate of your online business website. In addition, if a site search engine uses ML behind the scenes, then its predictive search capabilities can automatically get better over time. 

If you’re looking for an easy-to-integrate site search engine with robust predictive search functionality, you might want to consider using Zevi. By using AI and NLP behind the scenes, Zevi ensures a smooth and intuitive search experience for your site visitors, while also providing several business-oriented tools that can help you boost your revenue. Book a demo today!