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How AI is Uncovering Hidden Treasures in Online Conversion & Revenue Growth

In this special guest feature, Michael Scharff, CEO of Evolv, believes that in the rapidly evolving world of e-commerce, today’s ideal customer experience may not be so ideal tomorrow. Fortunately, retailers can now use the power of AI and data-driven insights from online customer behavior to define that optimal experience today as well as in the future. Michael brings over two decades of digital commerce and retail experience; with leadership roles at some of the most well known retailers in the US including Sears Canada, Toys R Us, Staples and Best Buy. He has a wealth of experience in all aspects of retailing and across numerous industry verticals and channels. Michael has built and managed highly successful omni-channel and global eCommerce businesses, led teams in merchandising, digital marketing, innovation and other functional areas.

Creating an enjoyable customer experience, while simultaneously encouraging efficient purchasing, is the ultimate goal for those in e-commerce. Executed correctly, this digital duo creates a positive feedback loop: we know that when a customer enjoys their visit and easily finds what they are looking for, they are more likely to convert to purchase and repeat the experience in the future.

Within that delicate yet optimal balance of user satisfaction and revenue growth lie hundreds of variables. Some, like the positioning of elements on a page or the style of images, language and fonts, are within the web designer’s control. Other variables, such as consumer preferences or seasonality, are constantly in flux and difficult to pin down.

In the rapidly evolving world of e-commerce, today’s ideal customer experience may not be so ideal tomorrow. Fortunately, retailers can now use the power of AI and data-driven insights from online customer behavior to define that optimal experience today as well as in the future. 

ABCs of A/B Testing

There are a number of traditional techniques businesses can use to attempt to define the customer experience that will deliver optimal results — commonly revenue growth. One of the most widely utilized is A/B testing.

Pitting A against B can certainly help designers choose between two different versions of either a single page, or a whole funnel. However, pitching two disparate designs isn’t always a beneficial process. First, it’s not hugely informative towards your real goal: if design A performs better than design B, that’s great, but you’ll have little to no idea why it drove meaningful results. More crucially, even if design A is the best choice today, its impact will diminish as time goes on since the market and consumers’ expectations are always changing. 

Even after an A/B test has concluded, many questions remain: should this test result be implemented now, or should you wait to implement until you’ve had more time to experiment? How many hypotheses could there be, and in which order should you address them? How have consumer preferences changed between the time the initial hypothesis was tested and the time it can be implemented? 

While all of this is being determined, the clock is ticking and your users may be receiving a subpar experience.

Of course, A/B testing is useful: at least you’re getting out and digging for treasure.  However, A/B testing isn’t the most efficient, nor effective, way to figure out where the X lies on the “customer journey map.” The ultimate solution would be to employ a proverbial army of backhoes able to dig across the island morning to evening. 

The World has Changed … Time to Change with It

Ever since Google engineers ran the first online A/B test nearly two decades ago, there has been an explosion of web traffic to e-commerce destinations, exponential increases in computational power, and huge advancements in automation and applied AI, not to mention rapidly changing consumer expectations and buying patterns.

In the age of competitive e-commerce, consumers shop with increasing agility and transience. As new products, seasons, competitors — or all of these and more — shift the market, even a successful customer experience won’t remain the gold standard forever.

In order to keep up with this ever-transforming marketplace, companies will need to move beyond simple A/B testing and embrace continuous full-funnel optimization, which monitors, analyzes, and optimizes the online customer experience on an ongoing basis. Due to the number of variables and changing conditions involved, this process is designed and ideal for machines — namely AI — able to handle data at scale and empower creative teams to constantly test their newest and brightest ideas.  

Adding in AI Muscle

As an all-encompassing colloquial term, artificial intelligence refers to the machines that mimic cognitive functions. What makes AI so useful to continuous full-funnel optimization is that it’s able to process large volumes of data, recognize patterns, and then use those recognized patterns to optimize certain results.

In e-commerce, AI-powered experience optimization enables marketers to input a variety of ideas for a section of the user experience or funnel, so the program can then continuously search and apply the combination of ideas with the highest potential. Incoming traffic can be split to test multiple scenarios concurrently across devices, customer segments, and more. 

What makes AI an effective and agile tool in this context is its ability to immediately act on, and learn from, new information in near real-time. Combined with designers’ ingenuity, machine-powered testing is creating a new era of experience optimization. This exciting partnership will not only help pinpoint the X on the map, but also unearth previously unknown treasures amongst the infinite possibilities.

Accelerating Growth through Continuous Optimization

Testing one experience against another and hoping for good fortune along the way is great, but relying on A/B testing isn’t a long term strategy for optimizing an e-commerce business — not when there are rich, new possibilities for growth constantly being discovered. Continuous full-funnel experience optimization requires those in ecommerce to embrace a new approach and lean on new technologies to help.

The payoff of this shift will be the ability to efficiently explore a far greater number of experiences, helping retailers discover and constantly refine those that will deliver the best outcomes.

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