Ashley HomeStore Experiences a 28%
Revenue Increase with Unbxd Site Search


Ashley Homestore has a large and loyal customer base. However, Ashley found that their online sales were declining while their in-store business was thriving. Probing further into the issue, Ashley found that their site search usage was high but so were their search exit rates and bounce rates.

The search results page took a long time to load and often returned irrelevant or no results at all. Often, shoppers could not find what they were looking for, and this lead to low conversion rates, adversely affecting customer retention and the online Ashley brand.


Ashley HomeStore is America’s largest furniture retailer. A household name in the US for over two decades, it sells top quality furniture online, and at over 450 stores in the US and over 600 locations worldwide.

Ashley HomeStore’s parent, Ashley Furniture Industries is the world’s largest furniture manufacturer.

Unbxd understands our shoppers well, and helps us provide 
the great customer experience that we are known for.”

Jeff Melton,
Director of eCommerce

Ashley HomeStore partnered with Unbxd to deliver a high-quality, 
personalized online shopper experience through Unbxd’s self-learning 
site search solution.

Achieving high relevancy with unstructured product catalog

Ashley’s product catalog was largely free-text and unstructured. Unbxd’s machine learning algorithms semantically parsed the catalog to extract relevant product information from the metadata and converted it to a searchable product database.
Unbxd Site Search identifies shopper intent and matches it with the right products in the product catalog to provide highly relevant search results. Aided by natural language processing, the solution is tolerant to common errors. It provides highly relevant results even when shoppers make spelling mistakes or use synonyms in search queries.


Adapting to shopper behavior with self-learning machine algorithms

Unbxd’s machine learning algorithms learn from user behavior patterns to become better at understanding the nuances of shopper

For instance, based on shoppers’ behavior patterns on the site, the solution learns over time that “contemporary leather sofa” is similar to “modern leather sofa.” This eliminates manual intervention in not only building synonyms but also adapting to differences in shopper behavior.

Catering to unique shopping needs with targeted segmentation

Ashley has a unique challenge of having multiple zones across the US, each having its own local fulfillment strategies. Unbxd’s solution replicates this geographical segmentation online in site search results, without the need for separate microsites for each geographical location.

Shortening path-to-purchase with predictive visual guidance

Unbxd’s Visual Autosuggest offers visual product suggestions to shopper search queries. It enables shoppers to visually identify their choices and significantly reduces shopper effort by helping them reach the desired product in as few clicks as possible.


Unbxd’s AI-powered, self-learning site search solution drives 
Ashley HomeStore’s search revenue with a personalized shopper 
experience and an intuitive search UI.