Search is a fundamental aspect of the digital experience–it is the mechanism we use to navigate vast amounts of information and products online. Yet, the search solutions provided in most digital commerce platforms lack the sophistication needed to be effective in driving conversion and ascertaining behavioral data to help brands and retailers make intelligent business decisions.
In a recent webinar with Forrester VP and Principal Analyst Mike Gualtieri with Zoovu and eMarketer, Gualtieri asserted the solution to solving today’s search complexities is cognitive search. Businesses need to help customers find what they are looking for and meet their needs when they go on a digital commerce site, the mechanism for this is product discovery. What makes product discovery so effective is the AI that helps engage in digital conversations about that specific customer’s journey–in the moment of need.
Businesses need technology that leads to a conversion at the moment a customer enters a site with the intent to either purchase or browse. Engaging a shopper with a conversation when they are navigating your site keeps them on the customer journey and reinforces your product or services are there to help fill their individual needs.
According to Gualtieri, for cognitive search in digital commerce to be effective in increasing conversion and growing customer loyalty there are 6 elements required and if a solution is missing one, it will not provide a true product discovery experience.
6 elements required for cognitive search in digital commerce
1. Integration
Any cognitive search solution should seamlessly integrate with existing commerce systems. If a business assumes the search functionality of their current digital commerce or product content platform is sufficient, they are losing out on an opportunity to deliver a better search experience. When looking at external solutions, ask if they come with pre-built applications to help accelerate the implementation and effectiveness of cognitive search applications quickly, and if they have experience with a certain domain and within your industry.
2. Information
Cognitive search requires data and access to it from search engines to be successful. By integrating with existing systems and search engines, cognitive search is able to utilize dozens of sources of data like product content, imagery, catalog information, and other data. Your business’s own data is invaluable for machine learning to maximize its power to enrich the product discovery experience. The reality is: data is the accelerator of cognitive search and AI, and connections to multiple systems are non-negotiable. A true and tried cognitive search solution will have pre-built data and content connectors.
3. Intelligence
When you look at how powerful Amazon, Google, and other internet giants are in delivering hyper-personalized experiences and results to users, remember it’s all derived from artificial intelligence. The first step in finding personalized information is to understand the user’s intent and context. The only way to understand user’s intent on digital commerce channels is to offer relevant information, and cognitive search’s powerful intelligence can find a needle in a haystack each time a person starts a query. Cognitive search leverages every user interaction to automatically tune relevance to signal the machine learning to make a relevant, personalized experience for each customer. Choose a solution to maximize AI for intent, relevance, query nodes, and tuning.
4. Operations
Conversational search solutions sometimes need a little help, and that is to be expected. Thus, a solution needs usage analytics to let you measure the success of cognitive search and you need something to help navigate it. Remember, Google and Amazon have millions of users helping their AI fine-tune results and experiences. Tuning tools let you boost and bury search results to improve relevance manually. The automatic nature of AI can be a catch 22: there is a need for human control as a conversion is not always the singular goal for user interaction for a digital commerce site. Whether it be a promotion or trying to understand true user interest in a product type, a solution must allow for human tuning with rules to ensure initiatives can be managed.
5. Architecture
As we mentioned earlier, search is fundamental to digital commerce, and if search goes down, digital commerce will too. A cognitive search solution needs to be as resilient as your digital commerce platform. Applications and data exist everywhere — on-premise, in the cloud, and across your technology stack. Both should be pulled from wherever they may live. Search must scale to handle an increasing number of data points about signals, past journeys, user-generated content, catalog, support information, and of course, customers. When you look for a solution, understand how it’s built, why it won’t go down, and choose one that employs scalable, high-availability, and cloud design maxims.
6. Search
Search is the heart of conversational technology to guide customers through the experience of browsing and searching to purchasing, and coming back for more. Businesses spend billions of dollars driving customers to websites and then deliver a sub-par search experience because the search solution within your current digital commerce platform is not powered by AI. Digital retailers must maximize conversations to stay competitive. This competitive advantage results in more conversion, more wallet share, and a digital commerce experience that provides more information and insight than keyword search could ever be capable of deriving.