In the digital realm, every action and idea is driven by one primary goal—getting the visitor to take action—because getting customers to click the ‘buy’ button is what drives revenue growth. However, data from Statistica reflects that digital experiences are falling short, hemorrhaging revenue that could be driving the bottom line. In 2019, shopping cart abandonment averaged 70%, which by a broad estimate equates to a loss in revenue of almost $5 trillion. In the COVID era, it is widely accepted that these statistics have not improved. In fact, the rise in online traffic and increase in ecommerce sales is masking poorer conversions experienced by many businesses and the corresponding loss in revenue.
Leading analyst firm Frost & Sullivan believes that at least half of that revenue can be recovered if companies optimize the digital customer experience more effectively—a task that might be considered simple, if only it weren’t for the break neck speed at which technology, offerings, marketplaces, and customer expectations are constantly changing.
Companies may have many ideas on how to optimize the customer experience, but implementing untested ideas can be costly. Unfortunately, implementing ideas after processing them through traditional testing tools can be just as costly, because these rarely generate accurate or definitive conclusions. Such companies are severely constrained in their ability to evaluate all the options that might optimize the digital experience, and the results may take months to generate—by which time they’re largely obsolete.
So how can companies optimize a customer experience that is influenced by so many dynamic factors? You look to a solution that can keep pace and empower informed decisions based on a very large number of possibilities or what we call a search space. You use AI-driven optimization that can process thousands of individual variations and different combinations in real time, on real visitors, in a real business environment. If you want relevant insights, that’s how to learn what constitutes a positive customer experience.
People have mixed responses to AI. Some fear it, others are weary of it, but those at the forefront of technological innovation are leveraging ways for AI to help businesses perform better.
Conversions are not driven by a specific scientific formula. There is no one right answer. This is why trying to optimize the customer experience is like trying to find a needle in a haystack. There is simply too much data, too many possible ideas, and too many variations to sort through than is humanly possible. Faced with this seemingly impossible task, most companies try to select which ideas they think will work. It’s guesswork, at best influenced by historical data and bias more than being able to identify what’s really impacting the customer experience.
AI in ecommerce has the ability to handle an immense number of variations and largely automate the optimization process. It can help take the pressure off teams and provide a solution that results in real revenue growth. Ideas no longer have to be tested one at a time. The right approach needs to incorporate formulating strategies, facilitating ideation, and leveraging AI technology to produce specific insightful conclusions. It answers the question: what customer experiences are driving results?
What makes AI-driven optimization so powerful is that it’s an active learning process which gets smarter as it learns. At any point in the optimization, ideas can be added, removed, or modified based on how they are performing without impacting the integrity of the experiment or its past results. The Evolv Digital Growth Optimization solution supports and optimizes for a number of target metrics. The AI-driven optimization automatically recalibrates to build on the ideas that are most likely to produce lift. The results not only show the best optimization ideas, but simultaneously drive actual growth because it’s serving up ideas to customers in a real-world environment.
This type of application of AI in ecommerce is taking the guesswork out of the relationship between customer experiences and achieving specific target metrics. It’s enabling teams to experiment with riskier ideas and lesser ideas that may not have been considered before, both can impact the customer experience in a positive way. Optimization of the customer experience becomes about the performance of multiple ideas, many variations, and visitor behaviors, combined. Teams can see which ideas, variations and even combinations are delivering results, by how much and why.
Here’s a real-world example: For a communications service provider (CSP), 8 optimization changes with multiple variations for each were made across 3 pages. This resulted in a search space with more than 62,000 different possible combinations that were served up to real customers in real time. Within 30 days, the Evolv Digital Growth Optimization solution was able to identify and pull together the variations that produced the best customer experience and generated an additional $90 million in revenue.
Using an AI-driven optimization didn’t produce insights on what might drive lift, it produced data on what had generated real revenue growth. No more guesswork, no more bias, just thousands of ways to optimize the customer experience and make more money. For companies targeting aggressive growth or customer retention strategies, it provides a solution that keeps pace with changing dynamics and delivers an immediate return on investment. That’s a competitive advantage AI inecommerce provides, and that shouldn’t be ignored.