Delivering search results that match what consumers are looking for is a strong determinant of an eCommerce’s site success. If people can’t find the products they are interested in, retailers don’t make a sale and consumers get frustrating and unsatisfactory user experience.
Nielsen Norman Group has been tracking the progress of eCommerce search for the past 17 years, analyzing more than 500 queries across three studies. In 2018, the latest research revealed that “search success rates have improved steadily, when counting both the overall successful searches […] and those searches that returned correct results the first time when the participants used the search.”
However, even with the positive results, the longitudinal study still found challenges for eCommerce search. In particular, it mentioned “lack of support for typos, errors, or common keyword synonyms” and “poorly executed filters (irrelevant attributes, bad functionality, empty result sets).”
Using visual search to augment standard search (and more)
With traditional, keyword search limitations preventing the growth of revenue and smooth user experience, visual search proves to be a suitable solution.
As defined by Gartner analysts Robert Hetu and Kelsie Marian, “Visual search is the use of AI technologies such as computer vision to replicate the common human task of looking for something in a cluttered visual environment. Consumers and retail associates use images obtained from various sources, as well as those created from their physical environment, to enable shopping for exact matches and reasonable alternatives.” (Hype Cycle for Retail Technologies, 31 July 2019)
Providing consumers with the ability to upload an image into a search engine and receive visually similar results, AI-powered visual search is poised to:
- Improve digital shopping capabilities
- Enable more targeted and accurate results
- Support future customer shopping success
As the technology expands to include multiple use cases from shopping for similar looks to extracting explicit and structured product tags, retailers can expect visual search to:
- Better understand customer preferences
- Enhance customer service
- Improve the ability to select product assortment to replenish
The Gartner research advises, “As we anticipate this technology to move quickly through the Hype Cycle, there is an urgency to identify and partner with a visual search AI provider, to test and build out robust visual search capabilities across all channels. Look for vendors that provide the more targeted search capabilities that support accurate search. Look for use cases that will also support internally facing business processes with more accurate product attributes for merchandising and marketing.”
Syte was mentioned as a Sample Vendor for visual search in the report. To read more of the Hype Cycle for Retail Technologies, 2019, Gartner subscribers can click here.
Besides augmenting text-based search, Syte’s visual AI technology offers an end-to-end solution for the entire product search and discovery journey—backend and frontend, online and offline. With accurate textual and visual search results, retailers empower consumers with a more intuitive and seamless shopping experience, leading to increased sales and customer satisfaction.
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