Yext: Machine Learning in Ecommerce Site Research

Predicting the future can be tricky, but that doesn’t mean businesses can’t identify and prepare for changing trends. Spotting and leveraging them can help your business improve your products and increase your customer base. With machine learning, you can analyze current data and extract insights into the future.

Machine learning in e-commerce site research

Machine learning is a term that refers to the ability of a computer or program to learn itself based on experience instead of being programmed by someone. It uses artificial intelligence to recognize patterns in data and improve its own capabilities through trial and error.

However, artificial intelligence is not necessarily the same thing as machine learning. Artificial intelligence is any type of automated behavior that mimics human behavior in some way. Motion-activated cameras are a type of artificial intelligence because they can detect motion. machine learningis a subset of artificial intelligence that looks specifically at how machines process data and make predictions about the future based on their experiences.

The best part about machine learning is that it doesn’t require human intervention. Your business can save countless hours and overhead by relying on machine learning instead of needing programmers to make every change manually. machine learningworks very well in the e-commerce space by leveraging customer data, such as their purchase history and habits.
From these many data points, machine learning can make predictions about what they will need and when they will need it. However, this can only take your website so far; Once customers get to your website, they need to be able to find their products without wasting time untangling complex site navigation.

Driving traffic to your website means nothing if people can’t find what they’re looking for in a timely manner. Your conversion rate depends on having an accessible website that makes it easy for customers to browse your products and find what they need. This is where the second part of machine learning comes in. With machine learning, your website can change messaging and internal search results based on user intent in real time.

Improve relevance

One of the ways machine learning is used for site searches is to improve the relevance of results. Typically, customers who start searching for products on your website are already ready to buy them. Their goal is to see if you offer the products, included features, and your prices.

If customers are faced with results pages that give them no results, or hundreds of results that have nothing to do with what they searched for, they are very likely to leave your website unsatisfied and do business elsewhere. Machine learning helps your search return relevant results for customers who don’t have time to waste.

Related search results

Machine learning doesn’t just help customers by filling in product names, accounting, or misspellings; it may also display similar or related products to entice customers to buy more than they originally intended. Showing accessories for products can be a great way to entice customers to sell during the buying process.

Machine learning incorporates past purchase history, browsing history, and connects products in new ways based on the experiences of other customers. It can also take into account what other customers have clicked on or added to their cart after searching for a term or set of keywords, learning from their connections.

For example, if you have an account with Amazon, you’ll probably notice that every time you log in, before you even click on the search bar, Amazon presents you with items similar to everything you last bought. or the previous time. Amazon often features items based on the last two or three items you purchased.

Error tolerance

Your search site should tolerate misspellings. Focusing on keywords alone won’t help when many customers are in a rush and spell words incorrectly or don’t know how to spell your smart brand names. If you use machine learning to account for these errors and provide autocomplete names, you can help your customers find what they’re looking for more easily.

This is a good thing because most customers will leave your website after a few minutes if they can’t find what they need.

natural language processing

When customers search for things, they’re more likely to type their requests the way they would tell their friends, using natural language. Guessing the right combination of keywords to get the right results is a tedious waste of time for everyone, and most customers don’t have the patience to play this game.

Site search tools like Yex Answerscan help you enable your search site to process natural language and return relevant results no matter how your customers ask their questions. This tool also lists all search queries, so you can see what people are looking for and if you have any gaps in your content.

Predictive analytics

Machine learning can also extract insights into customer behaviors that allow your site to predict the future behavior of other customers by knowing what is happening in their lives and what drives their purchasing choices. Based on what customers choose to buy, machine learning can extrapolate major life events that might make other items attractive to them in the future.

For example, if a customer buys cat food, this should prompt your website to predict that the customer owns a cat and will need other cat supplies. They may see advertisements for cat litter, cat toys, harnesses, or costumes. If they are registered on your website, you should activate the coupons or discount codes for cat-related items to entice them back to your site.

However, these predictive analytics can also work on a much larger scale. By analyzing buying trends, you stay informed about the market and what people will want in the near future. This can influence your marketing strategies, as well as how you stock your items so you don’t run out when people start buying.

Agreement the context of customer researchis essential, both to anticipate what they need now and what they will need in the future. Machine learning can also learn to incorporate the time between consumable purchases. Using the example above, your site search can learn that after purchasing one bag of cat food, consumers typically purchase a second bag three weeks later.

It learns this fact by seeing repeat customers and finding patterns or overlaps, and comparing the time between purchases for an average. Your website can then send personalized notifications or discount codes gently reminding customers that they might soon run out of cat food and should buy more, so their cat won’t go hungry.

Improve ranking

Another way machine learning can benefit site searches is through rankings. When a customer searches for cat food and you sell multiple products with that tag, your search engine needs a way to determine the order in which the cat food products are listed on the results page. of research.

Some e-commerce websites like Amazon allow customers to choose filters that automatically sort their results by price or average star rating. You too can enable Yext to learn what items the customer is looking for based on previous search histories, shopping behaviors, what they typed in the text box, and what other people like them. have purchased previously.

With machine learning, search on your site can analyze all of this data and sort the items into a reasonable ranking system that lists the items the customer is most likely to buy at the top, with the likelihood of purchase decreasing to as the results page continues down.

Chatbots

Customers aren’t always looking for products on your website. Many customers are looking for information about what you offer, tutorials on setting up or using the products, or more information on product features. For questions like these, having an automated chatbot is a great way to provide answers without involving customer service reps.

Many customers prefer to avoid waiting for an email response. Instead, a chatbot provides instant access to a knowledgeable expert who is always online. Plus, it saves your business time and money as the bot answers questions and decreases the number of customers who need human assistance.

In conclusion

The benefit of machine learning is that your site research will become smarter and more informative with each shopper, whether or not they buy your products. Your website analyzes data from your customers and users to see how they organize products and which ones relate to each other to deliver better and more relevant results.

contact usfor more information on integrating machine learning into search on your business site and increasing your conversion rate.

Sources:

Machine learning improves search on e-commerce sites Learn more | Events

How Machine Learning Improves E-Commerce Site Search | Loop 54

Machine learning for e-commerce: how does it work? | Big Trade

Sherry J. Basler