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:
- Visitors who use site search are nearly twice as likely to lead to conversions compared to those who do not. Thus, online business owners need to be mindful of catering to visitors who are likely to use site search. The more accurate and feature-packed the site search engine is, the better.
- Predictive search improves sales by around 24%. This is mainly because in general, a longer search query is more specific, and such queries lead to greater engagement and better conversion rates. By giving you the option of searching for a relatively long query without having to type it in, predictive search makes queries longer than they would otherwise have been.
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:
- Trending search queries
- A given individual’s search history
- The “search intent” behind a query (this is where NLP takes center stage)
- How often certain search suggestions get clicked on (i.e. their ‘click-through rate’)
- What happens after a suggestion gets clicked on (does the user navigate away from the site immediately, do they spend a lot of time on that site, do they end up making a purchase on that site, etc.)
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):
- Query suggestions should be legible and highlighted to make it stand out.
- The list of suggestions should be of manageable size.
- The search suggestions box should be clean, uncluttered and visually appealing.
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. Start free trial today!