With the proper knowledge, strategy, and tools, creating a seamless, AI-powered UX is well within reach for retailers of any size.
Today, e-commerce is very active in utilizing artificial intelligence to create seamless, engaging, and effective experiences for its users. The industry is at the forefront of cutting-edge technology and does a lot in-house but also integrates and utilizes external solutions to create the best possible user experience for site visitors.
While it may seem impossible for most companies to harness AI to create a UX that holds up in comparison, it’s not. With the proper knowledge, strategy, and tools, creating a seamless, AI-powered UX is well within reach for companies of any size.
Big tech UX requires big tech resources — at least until recently
Consumers spend most of their time on big tech platforms and are now accustomed to “Big Tech UX.” Unsurprisingly, other businesses are striving to keep up with the level of convenience and usability. In fact, it has become a matter of competition.
While AI-powered UX is achievable, it requires a lot of work and resources. Even if you don’t develop anything in-house and you utilize external tools and solutions, you still have to do a lot and have a large team of dedicated specialists, from product and UX experts to engineers and data scientists.
To come up with a single UX optimization that works, you have to go through multiple product cycles: ideate, design, develop, launch, test, and start all over again, and the user response may still be zero. If you venture into creating a unique, responsive experience for each user, you must do a lot of heavy lifting by segmenting your audience and creating journeys for each segment.
Everyone is reinventing the wheel by optimizing UX failures
We are now at the point where businesses are competing for user convenience, trying to find new ways to solve the UX issues they’ve identified and leveraging those opportunities to increase performance. It’s both fair and expected in a competitive environment? McKinsey research indicates a 10% to 15% uplift potential in revenue and retention from omnichannel personalization, but there are downsides, too: It necessitates a considerable workload, is slow in yielding results, and of course, creates the added expense of additional staff — not to mention the money you pay for the solution you are using to give you the AI capacity.
But how smart is this approach when everyone is constantly creating something new, when most new ideas are tossed out after an extensive and costly production cycle and only a tiny fraction of the improvements are implemented? It’s a colossal waste. Perhaps industry verticals would be better off uniting and working on the perfect experience together with the help of smart machines. Look at all e-commerce stores — they are the same for a reason: We don’t want to shock our customers. We want them to feel at home, even if they are a first-time visitor.
An AI-backed storefront adapts to each user’s needs automatically
If you think about e-commerce stores, they are all very much unified in terms of their structure: the same homepage, collections, checkout, menu, and navigation bar. And all for a reason: It’s the only way to create a brand-new page that won’t make its user get lost. A fundamental law of UX design is that smart use of conventional UI elements will make your product user-friendly — and this applies here.
In the time of responsive, personalized digital interface experiences, it’s high time for storefronts to step up to the plate and make this conventional e-commerce interface smart and responsive to suit each user’s need and goal for every moment they spend on your site.
Just as a physical store needs an empathic shop assistant, e-commerce should offer that delightful level of service with the help of AI UX. A successful shopping experience is not only about finding products quickly; it’s about delivering the right UX that fits the goal of the moment: leading but not being too pushy (and the level of “too pushy” is different for each customer), knowing when to step back and let the customer do things for themselves, offering a discount when appropriate or complimenting their choice, giving the customer the social proof they require because they identify that the individual needs it.
With AI, we should also know that the more visitors it processes, the better it learns and the better it becomes increasingly efficient. This means that the more stores that are optimized with one and the same set of optimizations, the better they will serve their clients. This is the greatest competitive opportunity for stores like Amazon.