Poor eCommerce Product Discovery Experiences Cost Ecommerce retailers £8m per Year

March 10, 2021 | 2 minutes read

According to research conducted by Klevu, there are usability and accessibility issues with the search experience on 80% of UK ecommerce websites .

The majority of ecommerce sites are ineffective in delivering results when processing complex search queries, which account for 17% of all searches, leading to poor ecommerce product discovery, costing retailers £8 million every year. 

Poor-Product-Discovery-Experiences-Cost-Ecommerce-retailers-£8m-per-Year

Image credits: Klevu ecommerce discovery report UK

These issues naturally lead to low conversion rates and a large amount of revenue lost. The most common reason for this problem is the inability of search engines to handle complex natural language queries, such as the ones that involve product features or price ranges. 

Furthermore, it was also found that in the most critical cases, 26% of ecommerce websites are unable to generate relevant results even if the search queries include minor spelling errors, whereas 30% of the websites generate no results at all for search queries like ‘men’s jacket under £100’.

This clearly indicates that majority of the online ecommerce stores are not yet prepared to make the best use of future technologies for product discovery tools such as bots, voice recognition and other zero interface interactions 

Filling in the gaps

The research has also provided measures that can help improve user experience and ecommerce product discovery.

The right way to attract more users to your website and increase conversions is to optimize your on-site search experience. This would not only help increase conversion rate but also provide access to the most valuable and sustainable data – shopper intent. 

Moreover, the on-site search engines should able to process natural language and provide users with relevant search results for their queries, regardless of the search method they are using.

Data collected can further be used to understand consumer buying behavior which can help retailers to use effective filters on product listing pages and optimize their product recommendations blocks in a better way. 

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