As discussed in our previous article, “How Digital Experience Platforms Work with AI,” Artificial Intelligence has become an integral part of the DXP package, particularly for medium to large companies. The expansion of the structure and functionalities of DXPs have seen human processes simply outpaced by the exponential increase in dependencies from all areas of a company’s digital environment. AI is the solution to this predicament. Unlike our previous, more broad big-picture discussion on the topic, this article will provide a specific look into how Artificial Intelligence bridges the gap between company needs and human capacities.
Semantic Search
One of the premier benefits of incorporating AI into DXPs comes in the form of semantic search capabilities. Although relatively minor in scope, this feature can drastically improve the quality of a customer’s digital experience on a website. In essence, semantic search expands typical search functionalities within a website. Without AI, search queries rely solely on keywords to generate results. However, semantic search incorporates derived intent and contextual meaning by using AI algorithms to provide better search results that are more likely to yield expected results from the perspective of customers.
Semantic search artificial intelligence uses a variety of factors to predict the user’s intent. Part of this process involves an analysis of the user’s history, tying it to the ever-prevalent industry of big data. Another part of semantic search is the algorithm’s ability to create links between the words of a query. Non-semantic search techniques can not recognize words of a search query in relation to each other, but semantic search processes incorporate typical human language patterns to understand the meaning of a query outside the bounds of individual words. Semantic search also utilizes learning patterns that tailor the feature to individual users. By analyzing metrics such as bounce rates and conversion rates, the process will self-adjust to generate better results with improved satisfaction.
From a more general perspective, semantic search is contributing to significant improvements in Search Engine Optimization (SEO). Through these advances, technology in the digital environment is experiencing a trend where the power in the market is shifting towards the customer. Optimal search functions allow the customer to find the exact product they want at a price they are willing to pay. This trend only increases the necessity of providing user-friendly and optimal performances for prospective customers visiting your website.
Contextual Personalization
Customers have many experiences when visiting a website or platform. They may access the website on a laptop from the comfort of their own home, or they may access it abroad on their smartphone. Furthermore, there are countless other situations a customer may encounter when accessing a website or platform. Therefore, companies find a way to enhance the digital experience in all these possible situations the user faces. They do this through Contextual Personalization.
Contextual Personalization personalizes the digital experience by taking into account “every piece of content, device use, customer behavior, and success conversion paths to learn, deliver, and learn again which patterns lead to better outcomes for which people at which times” (Bloomreach). Companies do not have to personalize each situation the user encounters manually. Instead, machine learning is used to learn from the problems a customer experiences and prevent them from happening in the future. Therefore, the customer remains happy and the business lucrative.
Contextual Personalization cannot happen without the resources DXPs offer. The ability of machine learning to identify problems and improve user experience is enhanced with the connectedness of DXPs. The digital experience platform is the connected heart of all the solutions contextual personalization offers. It can store significant amounts of intelligence and provide a vast solutions toolkit to “keep learning about your visitors and continuously and automatically improve their experience” (Bloomreach). Overall, adopting a Digital Experience Platform is beneficial because it elevates consumer experience with the deeper level of personalization that contextual personalization offers.
Man and Machine
Having AI involved in a DXP allows for a company to deliver an amazing digital experience, as it allows the use of connected data within a company to give the customer exactly what they need or want. But while AI allows marketers and product management teams to gain insight into things they may not even have looked into before, AI is not the end solution. Rather, it is a combination of man and AI that allows for the best possible solutions to be presented to customers.
For example, there are always different metrics used to measure different customer experiences. AI can lead to new innovations and insights within a business by sorting and reviewing through a business’s data, identifying which patterns and trends are making an impact, and giving them insights on what can be done to maintain, improve, or change those patterns.
But AI can not create new innovations or excellent digital experiences on its own. AI is quick and accurate in compiling and analyzing data, but it is humans that use those findings to develop new strategies and innovations that lead to success. Marketers and product managers can utilize AI as the ultimate tool for success, compiling the data and analysis that leads to great products and services delivered by humans within a company. Essentially, a business needs to let AI sort through the data and logic that powers personalization, discover all the hidden findings passed over by humans, and let the real people behind the brand focus their efforts on the creativity and original ideas that ensure a business delivers the best possible digital experience to its customers.
Sources:
- https://www.bloomreach.com/en/blog/2018/what-is-digital-experience-platform-dxp
- https://www.bloomreach.com/en/blog/2019/semantic-search-explained-in-5-minutes
