The big trends in retail are just what you’d expect – What they mean for retailers is surprising

Explore how AI is transforming the retail industry, highlighting insights from the CommerceNext Growth Show.

By Steve Feyer on June 13, 2024


“AI, obviously.”

That’s the answer every ecommerce leader gives when asked about the biggest topic in retail this year. And they give the same answer in predicting next year’s top trend.

How AI and other big trends will change retail is less obvious. That discussion consumed much of this week’s CommerceNext Growth Show in New York. The expert practitioners had a lot to say about every big trend, and their conclusions aren’t what you may expect.

Here are three of the major topics from CommerceNext, and what they mean for retail.

AI basics are overdone—AI-powered products are just right

Naturally, everyone is talking about AI. The excitement around AI shows no sign of slowing down, but that doesn’t mean retailers have an endless appetite for AI topics. There’s been enough talk about the big picture—now it’s time to focus on exactly what AI can do.

Over the past two years, AI education and prediction topics have been popular. Audiences have enjoyed learning how AI works, what relative strengths different machine learning techniques can offer, what technical capabilities are pending, what big investments are being made, and so on. This year, these “foundational” topics fell flat. Retailers don’t want more homework about AI.

Now, retailers want to talk about exactly what they can do with AI products. They want to see how AI products fit into their flow of work. They want to acquire business-ready solutions rather than tool kits. They want to know what results they will achieve.

Generative AI, in particular, needs specific use cases for retailers to buy in. And providers of tools that use generative AI must explain how their products will augment or improve existing business processes, rather than replace those processes. Talk of generative AI fully replacing human efforts will be a leap too far for retail leaders.

Used as a productivity tool, AI-powered products are succeeding. Retailers are operating with budgets reduced up to 20% from the height of pandemic ecommerce in early 2022. They are maintaining the same levels of output by deploying new technologies, including AI.

Retail executives did talk about ways to use AI for the challenges of disappearing third-party cookies and anonymous traffic. One solution is to gather first-party cookies and convince visitors to identify themselves, approaches that can be improved with AI techniques to discover the best ways to influence visitors; the fact that this use of AI may be very simple, whereas the hottest new gen AI technology is technically complex, isn’t relevant. Retailers can also bypass the need to identify visitors and simply convert anonymous visitors—again, with the help of AI.

The surprise? Universally, every retail leader and AI expert described AI as augmenting rather than replacing current roles and processes. This is not the approach that talking heads were taking with AI just last year. So, for example, AI will not cause creative jobs to disappear, but it will become part of the day-to-day tools that creative professionals use to become more efficient. AI will not eliminate SEO, but it will change how businesses manage their online presence to appear effectively in the answer-based chatbots that will augment search engines in the future.

Data is a mountain of rocks—actionable insight is gold

Retailers are buried in data. The proliferation of channels and tools means that every customer interaction throw off hundreds of data points. What does it all mean?

Increasingly, the answer is that more data creates more cost and delay. Mountains of data can bury the signals that actually matter, and it can become difficult to find those signals in a reasonable period of time. In a world of seemingly limitless observation, insight becomes the valuable currency.

Retailers can’t solve this problem by gathering less data. Several executives noted that they are increasingly cautious about using tactics that don’t generate data to measure effectiveness because these retailers have reduced budgets and a need for efficiency. So out-of-home and linear TV advertising are deemphasized because they don’t generate enough data.

Meanwhile, new digital channels like AR/VR and social commerce will add even more data flows that must be analyzed and merged with existing data.

The situation seems like a paradox: retailers are compelled to gather even more information even though doing so creates challenges. Retailers will rely on AI-powered tools to make sense of the growing data volume.

Somewhere in the data are answers that will lead to the conversion, efficiency, and decisioning that retailers need to compete. Finding these seams of gold in the data mines is an important area where AI can help. The most valuable new applications of AI can deliver impact by automating insight and action quickly.

The surprise? The data paradox applies to many areas of retailer operations. Retailers need much more user-generated content, not less, so they can find a few creatives that actually convert. Retailers need many more product varieties, not fewer, so they can find the ones that sell. To the extent AI has promised a smooth path toward ideal conversion funnels and effortless insights, the AI-powered age of commerce will only deliver this promise if the AI has a much larger volume of options to optimize.

Loyalty is out of fashion—quality is timeless

The covid pandemic led to a burst in ecommerce growth, causing some observers to predict a permanent shift toward online selling. In reality, the pandemic proved to be more of a temporary shift—a fashion, in a sense—pulling ahead a few years of ecommerce growth. Then growth fell below expectations in the latter half of 2022 and 2023. By 2024, growth has returned to trend. So what has changed permanently?

By forcing people out of their rhythms and spending habits, the pandemic invited consumers to try new products and providers. This change—a new comfort with change itself—may be more lasting. Consumers are less loyal to brands simply because they have enjoyed a product or shopping experience in the past, and loyalty is now at an all-time low.

Consumers will certainly keep buying when they have good experiences. They are just more likely to examine their experience each time, and be quicker to try alternatives when their satisfaction drops. In other words, quality of the entire customer experience is supplanting brand loyalty and comfort. The implications of this shift affect brands, products, and channels.

As brick-and-mortar stores steadily lose traffic to digital alternatives, the best locations that offer the most of what consumers want are continuing to thrive at the expense of secondary locations. Such winning locations include premium shopping centers, accessible retail districts, and outlet malls.

Products that embed a compelling experience may also succeed at retaining some loyalty where more forgettable products don’t. Such factors might include an engaging social presence, customer communities, and even choice of packaging.

Consumers will try new purchasing channels, and may grow more committed to particular channels over brands. Judging by the wisdom of crowds, retail attendees at trade shows in 2024 believe that TikTok Shop will be a winning channel in the years ahead even though its unlikely to create brand loyalty.

The surprise? With all the focus on AI, social selling, Gen Z, Gen Alpha, and every other hot topic, retailers seem ready to give up on good-old-fashioned loyalty. Don’t the best customers drive most sales and profit? Can’t data and AI help retailers identify who will become the best customers so they can be cultivated? While retail experts are talking about the change in loyalty, unlike for other topics, they don’t seem to be talking about solutions. Even while acknowledging that the most trusted brands have seen no drop in loyalty, retail leaders don’t appear to think their own brands can replicate this result.

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