Online shopping: Search abandonment still vexes Indian retailers-the problem and how to fix it

Despite the continued rise in online shopping, many shoppers report hurdles in the product discovery experience on retailers’ ecommerce properties. Gone are the days where retailers can expect a customer to search, filter and refine repeatedly to find what they want. People around the world now expect site search engines to understand their intent deeply, return relevant results and help them discover new products easily with personalized recommendations.

New data from a Google Cloud-commissioned Harris Poll survey finds that search abandonment—when a shopper searches for a product on a retailer’s website or mobile app, but doesn’t find what they are looking for—Rs. 70.9T each year in India

Unsuccessful searches put consumer loyalty and repeat business at risk

The problem is that consistency is lacking in retailers’ search experiences. 96% of Indian consumers say that they have used the search function or search box on a retail website on an average 5 times and it did not provide the item they were looking for.

And after an unsuccessful search experience using the search function or search box on a retail website, 63% of consumers in India say they typically abandon their entire cart and go elsewhere if there’s at least one item they can’t find on a website.

Search abandonment has a real impact on brand loyalty too. 65% of Indian consumers say they are less loyal to a brand when it’s hard to find what they want on a website. To this point, nearly 73% of them agree that after an unsuccessful search experience on a retail website they are more likely to leave the site and purchase the item elsewhere. Furthermore, 70% of Indian consumers say they avoid websites where they have experienced search difficulties in the past

The search bar is a retailer’s most important online asset

It is still a struggle for many retailers’ search engines to understand exactly what shoppers are looking for, especially without capabilities like understanding natural language. And failing to understand what shoppers are looking for comes at a cost. When a shopper searches for a “long floral dress with short sleeves and comfortable fit” on an ecommerce site, they expect to immediately get results for precisely that—rather than adjusting their search multiple times, or worse, giving up their shopping journeys.

But why is product discovery so difficult? In retail ecommerce, the challenges of providing high-quality search functionality and personalization are centered around three key areas:

Understanding user intent Also sometimes called query intent. A search box is a very small place for shoppers to express themselves, and the input is very sparse for a search engine to understand the consumer’s intent, especially without capabilities like understanding natural language.

Context. The same search term from different users in different locations with different search histories can all have very different meanings, and aren’t easy to interpret or apply to search results.

Product knowledge. It’s very difficult to completely describe products and services just through a long list of attributes and metadata fields.

Personalized experiences = happy and loyal customers

With today’s consumers increasingly expecting a seamless and personalized online shopping journey, search abandonment and personalization are real challenges facing retailers. Addressing the reasons for why a shopping session is abandoned can help retailers meet their customers’ needs, boost conversions, and ensure greater customer loyalty and satisfaction. And optimizing customer data to create individualized experiences also goes a long way in building trust and loyalty for retailers.

Google Cloud’s AI can help retailers quickly and concretely tackle the industry challenge of search abandonment — when a consumer searches for a product on a retailer’s website but does not find what they are looking for. Google Cloud Retail Search, which provides advanced query understanding that can produce better results from even broad queries, including non-product and semantic searches, to effectively match product attributes with website content for fast, relevant product discovery.

Integrated tools such as Google Cloud’s Recommendations AI can then take the data even further, delivering real-time bespoke recommendations and allowing retailers to anticipate and predict their customer needs, thereby creating a highly personalized and superior service experience

Conclusion

By adopting and leveraging cloud technologies, retailers can consolidate, analyze and activate this data, and give shoppers the search and browsing experience they want.

In doing so, retailers will be able to dramatically reduce search abandonment, improve conversions and drive profitable growth. Building strong capabilities around product discovery especially in retail search can not only enable the retailers to offer superior customer experience but also enhance retention and loyalty while positioning themselves for the future.

By Sameer Dhingra is Director Retail and Consumer of Google Cloud.