Using AI-powered Search To Improve CX
Retailers have shown, through various studies, that improving the customer experience is considered a top priority. In a recent Digital Intelligence Briefing Report by Adobe and Econsultancy, 600 global retail leaders were asked how their organisations differentiate themselves, and customer experience was the top answer. Twice as many retailers (26 percent), also reported that they planned to focus on customer experience, compared to the second-ranked customer service (14 percent).
Similarly, Jabil’s Future of Retail Technology Survey reported that 95 percent of retailers sought technology to improve the customer experience. 73 percent also strongly agreed that innovative technology is crucial to address the high standards of shoppers. Despite this, retailers seem to overlook a key factor in customer experience, that of ecommerce search.
From a user-experience standpoint, most ecommerce sites have poor search capabilities, said Lauryn Smith, senior user experience researcher at Baymard Institute. “Almost every site within the 60 highest-grossing ecommerce sites in the United States would have to make substantial improvements to get to a performance that would be viewed as acceptable or good according to our benchmark.”
When Search Fails, Consumers Bounce
According to Baymard’s usability study on ecommerce search, respondents stated that they were either incapable of finding what they wanted or chose to abandon the search, almost a third (31 percent) of the time. For nearly two-thirds of the time (65 percent), it requires more than one attempt to find what they were searching for, figures that have remained relatively unchanged over the past few years.
If potential customers can’t find what they’re searching for in the first page of their results, or if they’re met with “your search returned no results,” the majority of them are unlikely to check their spelling, try another synonym or check a different filter to eliminate pages of irrelevant results. They generally end up leaving in this situation, despite the retailer having what they want, and so the retailer would lose a potential sale and long-term customer.
Retailers’ Big Data Solution Is AI
Despite search being a key component in the customer and sales experience, the technology behind ecommerce search is often an afterthought for retailers. Retailers invest millions in content management systems (CMS), ecommerce platforms and analytics solutions, which are all essential to the profits of an ecommerce site. However, retailers continue to underfund search, as critical as it is, to allow these three systems to work together.
Search is responsible for connecting the CMS and the ecommerce platform. The system organises the user by intent, through a query in the CMS, which leads to execution, where the user purchases on the ecommerce platform. Search adds value to interaction data because a user query displays intent and has context. The clicks and sorts that follow help add further context. Making this ‘record of intent’ active, works for retailers by helping keep users on their site, helping them buy/convert more often, and reducing overall time and effort spent merchandising, ‘searchandising’ and tuning relevancy.
For years, the search engines already integrated into CMS and ecommerce platforms were adequate for retailers, but due to recent advances in artificial intelligence (AI) and machine learning (ML) technology, search functionality and performance has now been elevated to a new level. A plethora of data is involved in ecommerce search, including user preferences and behaviour, such as search terms, pages viewed, items added to and subtracted from the cart, purchases, and all the attributes for its products.
The sheer amount of data involved is what makes search ripe for integration with AI. Most search tools currently rely heavily on manually categorising products and keywords, but AI can read unstructured data and provide great benefits. By integrating natural language processing and data management tools into your search, customers will be able to identify more relevant results, which can have an immediate and positive impact on sales.
Adopt AI Technology Based on Specific Needs
Businesses across most industries are racing to implement AI. Spending on AI systems was projected to increase by 44 percent in 2019 and to reach almost $36 billion worldwide, according to a report by the International Data Corporation.
Retailers are now faced with multiple companies claiming to provide AI-powered systems, with some of these firms misrepresenting or misusing the term. For a system to be considered as AI, it must have the ability to learn contextually and be able to apply this learning to alter the way it works.
So, for retailers looking to adopt AI led ecommerce search, rather than spending time trying to understand the underlying technology, aim to discover how exactly search and AI/ML will drive value for your business. This starts by asking how the technology will help customers get to a retail website, to buy and convert more. Then, consider how the technology tests and improves traffic volume, conversions and incremental purchases. Finally, how does the technology reduce time and effort required, while accomplishing these goals?
Hesitation Is Risky
Retailers still waiting to deploy AI and ML are doing themselves a disservice and missing out on incremental benefits. AI-driven technology gradually gets more effective over time, so the ROI you realise three years from today will be far more substantial if you started tomorrow, than if you start half a year later. See how Lenovo is using AI and ML Search as the Universal language of Lenovo customers, and driving ROI.
A Salesforce & Deloitte Digital study found that search is one of the most common use cases among retailers and brands that have adopted AI for at least one application, with 40 percent using it to provide relevant search results. As the popularity of AI-powered search continues to grow exponentially, retailers should get started now if they haven’t already, and hope that it’s not too late.
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