The ecommerce industry has seen tremendous growth in the past few years. This is largely due to the convenience and ease of use that online shopping provides to consumers. With a few clicks, shoppers can find and purchase the items they need without having to leave the comfort of their homes.
Predictive searches can be very accurate, which is why they are becoming increasingly popular with businesses. Ecommerce businesses can use predictive searches to their advantage by optimizing their website for these types of searches.
According to Forbes, ecommerce will account for 20.4% of global retail by the end of 2022, up from only 10% five years ago. This rapid growth is expected to continue as more and more consumers turn to online shopping.
With the ecommerce space becoming more crowded, it is important for businesses to ensure their website appears high in search engine results. One way to do this is by optimizing for predictive searches.
Predictive searches are based on algorithms that try to guess what a user is going to search for next. These algorithms take into account a variety of factors, such as the user’s location, search history, and time of day.
Are Predictive Searches More Accurate?
There is no definitive answer to this question. The accuracy of predictive searches depends on a variety of factors, such as the type of data the algorithm is using and the quality of the data.
Some experts believe that predictive searches are more accurate than traditional search engine algorithms. This is because predictive searches take into account a wider range of factors that can help to predict better what a user is looking for.
Other experts believe that predictive searches are no more accurate than traditional search engine algorithms. They argue that the increased accuracy is offset by the fact that predictive searches return a smaller number of results. The accuracy of predictive searches is likely to improve over time as the algorithms become more sophisticated.
In spite of these differing opinions, there is no doubt that predictive searches are becoming more popular. This is because they offer a number of advantages over traditional search engine algorithms.
What Is Predictive Search All About?
Predictive search is a type of search engine that suggests query terms as the user is typing. This is different from traditional search engines, which only return results after the user has entered a query.
Predictive search engines use algorithms to try to guess what the user is looking for. These algorithms take into account a variety of factors, such as the user’s location, search history, and time of day. They quicken online searches by presenting related search term suggestions that the user is searching for. Primarily, these predictions are based on similarity and popularity.
The biggest advantage of predictive search is that it’s a lot faster and easier for a user to read than type. Instead of having to type the entire search query, the user can simply read through the search predictions and select an item.
For an ecommerce website, predictive search has more advantages than simply saving time. There are times when customers may not be able to enter the full description of the products they are looking for.
Sites built with platforms like WordPress, Shopify, or Magento can easily incorporate predictive search functionality by using 3rd party apps. They can locate the correct description and spelling of products their customers are looking for.
How to Increase the Accuracy of Predictive Search for Ecommerce Sites?
There are a number of ways to increase the accuracy of the predictive search for ecommerce sites:
1. Include all relevant product information in the search index.
2. Use synonyms and related terms to help the algorithm understand the meaning of the product.
3. Use misspellings and common typos to help the algorithm understand the customer’s search query.
4. Use customer reviews and ratings to help the algorithm understand the quality of the product.
By taking these steps, ecommerce site owners can ensure that their predictive search functionality is as accurate as possible.
Predictive Search Use Cases for Ecommerce Sites
Ecommerce sites can use google predictive search to suggest products, categories, and brand names. Product suggestions can be based on the user’s location, search history, and time of day.
Here’s how some of the top ecommerce businesses have leveraged predictive search to improve their customer experience:
1. Manageable List (Amazon)
Ecommerce giant, Amazon, uses predictive search to manage a huge product catalog and still offers relevant results to their users. The search suggestions are based on the user’s location, search history, and time of day.
Moreover, the search predictions are different on the desktop site and the mobile site. This is because the mobile site is limited to 5 or 6 predictions, while the desktop site can have up to 9 or 10.
2. Highlight Active Search Prediction (Etsy)
This is one of the most common features that ecommerce businesses can find in predictive search results.
Etsy highlights active search predictions with a gray shade to let users know which prediction they intend to select. This is a very simple design feature, but it’s very effective in helping users find what they’re looking for.
To incorporate this on your eCommerce site, make sure that you highlight the active search prediction just like Etsy.
3. Use Related Terms (Walmart)
Walmart uses related terms in their predictive search to help users find the products they’re looking for.
For example, if a user searches for “baby clothes”, Walmart will also suggest related terms such as “baby girl clothes” and “baby boy clothes”.
This is a very useful feature, especially for ecommerce businesses with a large product catalog. It helps users narrow down their search and find the products they’re looking for.
4. Featured Image (Costco)
Using feature images in your predictive search results is a great way to increase conversion rates, especially if you are selling electronics on your ecommerce store.