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Optimizing online customer experience using AI for a top US home improvement retailer

Consumers struggle to find the products they want quickly

The online customer experience is always important, but it has become especially crucial now that customers are beginning to move their purchasing power to online shopping and avoid retail locations. Consumer expectations have increased along with the online retail market share: customers now expect to locate the products they want quickly and easily with minimal search attempts. 

However, many retailers, even the most prominent ones, have failed to keep up with this trend. Their online product content is often incomplete, unintuitive, and full of gaps where customers want specific information. This leads to frustration when potential buyers find themselves unable to locate products or unable to access the product information that would make them feel confident in a purchase. 

A top home improvement retailer decided to try AI

Even if a company wants to optimize its online product content, the process can seem insurmountably time-consuming and expensive. Re-doing product naming taxonomy, adding extensive detailed product information, and testing for the effects of improvements manually requires huge numbers of either in-house or outsourced employees for data entry and validation. 

To avoid a cost-prohibitive and potentially never-ending project, one top home improvement retailer decided to look into AI solutions with CrowdANALYTIX. By using machine learning and automation instead of painstaking man-hours, the business could make their online customer experience smoother and more efficient, leading to better conversion rates and higher profits. The company recognized that making their online experience excellent was especially important in the face of a massive move away from in-person retail transactions. 

Our approach

CrowdANALYTIX leveraged product data and public search data to produce algorithms that revealed vastly improved taxonomies for product naming and for additional product content. This led to the production of AI-optimized product naming formulas as well as identification and subsequent improvement in attribute population and strategy gaps. 

An example of the process can be seen with the company’s naming and content conventions for ceiling fans, a popular home improvement purchase. Customers were struggling with the online experience of finding the fan they sought, because the taxonomy did not include nearly enough information to make consumers confident in their purchase decisions. They were expected to navigate to a general “Ceiling Fans” category, and from that vast array of products, make a selection. Customers were forced to spend more time than they were willing to spend looking through pages of products, in this case more than 4,000 individual ceiling fan options. CrowdANALYTIX validated an improved taxonomy that took customers from “Ceiling Fans” to options with or without lights, and from there to types of bulb. Customers might also now search by color, number of blades, or product width. With the CrowdANALYTIX solution applied, potential buyers were offered fewer and more appealing choices more quickly.


CrowdANALYTIX projected that existing data could be enriched by 93% with the application of the customized AI solutions developed for the company. Since CrowdANALYTIX used actual search and product data to make their taxonomic recommendations, the application of these changes was projected to significantly improve the customer experience, leading to reduced search time and higher conversion rates. 

Data used: Public data, Search data

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