Putting the “AI” in Ret(ai)l Clienteling

There are huge opportunities for AI in the world of retail. Here are some ways we could see clienteling and AI enhance brand-customer relationships.

Depending on what online circles you frequent, AI is either going to destroy the customer relationship… or elevate it to the level only dreamed of in the most utopian sci-fi movies.

The truth is decidedly somewhere in the middle at the moment, but the retail industry is trending toward the latter. According to a report by Precedence Research, retail investment in AI is expected to quintuple in the next ten years to over $45 billion, and that seems like a conservative estimate considering the pace of interest and adoption in the space.

But can AI truly deliver a clienteling experience in the way the top retail brands use the term? At this point, we’re all familiar with the chatbots on the corner of websites acting like a modern version of Clippy, ready to help you with customer service questions. Given how hit-or-miss these bots are at the moment, can any AI tool actually improve the brand-customer relationship in any meaningful way?

Instead of just asking ChatGPT, let’s take a deeper look at just a few of the clienteling areas where AI could indeed foster an impactful connection to the individual customer.

A Reminder that Clienteling Isn’t Just Customer Service

First, let’s please keep in mind that clienteling isn’t just good customer service. For example, good customer service is a chatbot loaded up with FAQs that can help any online visitor find their shipping tracking code. But clienteling is knowing that Emily from Boston, Massachusetts is inquiring about that one yellow sundress that wasn’t in her size last week at her store down the street, and letting her know that it’s back in stock before she even asks.

We already know that AI can provide decent customer service. That’s why Wendy’s is starting to use an AI chatbot to take drive-thru orders. But the entire idea of clienteling is offering a VIP experience that increases both loyalty and frequency of visits from your customers. The real question is whether AI can help your brand offer that level of intimate experience.

So where do we see AI fitting into the clienteling equation in retail?

Prescriptive Analytics for Product Recommendations

Retailers already know how important good product recommendations are to not only good clienteling, but to their bottom line. In fact, according to studies by SalesForce and Barilliance, “shoppers that clicked on recommendations are 4.5x more likely to add items to cart, and 4.5x more likely to complete their purchase.”

Today, nearly all brands have some sort of product recommendation plugin on their ecommerce sites. These algorithms can range from basic (eg. same slippers but now in red) to complex (eg. Amazon’s secret recommendation sauce).

The better ones leverage predictive analytics, which is exactly how it sounds: algorithms based on customer data that can predict what products each shopper might want to purchase next. But today’s AI can go one step further into prescriptive analytics.

Prescriptive analytics not only looks at future scenarios based on customer data, but uses machine learning to get to the “why” of these outcomes. In other words, AI leveraged in this way can understand a customer well enough to model her behavior and provide product recommendations that go beyond what’s being offered today.

For example, your AI could recommend to Emily a curated list of apparel she may want to purchase each month, for the next year. Or shades of makeup that she never would have thought to try, but somehow the AI knew she’d love it – even when it initially seemed completely outside of her wheelhouse.

Doesn’t that sound like what a personal shopper could do after years of working with Emily? Exactly. An AI using prescriptive analytics can offer that level of clienteling, but en masse, to every one of your customers. This will lead to increased loyalty and higher sales.

Zegna is starting to offer this type of personalized recommendations. Via Vogue Business:
"The AI-powered styling component is the newest addition to Zegna X, which currently accounts for more than 45 percent of Zegna retail stores’ revenues. Customers who shop with one-to-one service using Zegna X spend 75 per cent more than those who walk into the store. Zegna said it allocated more than €5 million to Zegna X last year."

We asked ChatGPT to write us 8 text campaigns for midsize retailers to increase store traffic and drive sales.

And while we knew AI was good, we didn't think it was this good 🤯 💰

Coining a Term: Individualized Messaging

We’ve all heard the term “personalized messaging” a thousand times in retail marketing; so much so that it's sort of lost its meaning. Some brands do it poorly, with perhaps a tweaked subject line in certain emails to certain groups of their audience. Other brands do it extremely well, with truly segmented campaigns in both email and SMS, targeting tight groups of customers with exactly the products they are interested in.

But if you’ve used ChatGPT at all, you know that written words are now effectively free. Every brand will be flooding blogs, emails, and every other channel with an endless stream of words. So, now that the actual writing part is easy to do, the real trick is in writing for each individual customer.

Consider this level of individualized messaging: your AI has learned the words, sentences, and paragraphs that Emily likes to read. Maybe Trevor likes a lot of emojis in his emails. And maybe Trish likes a brand with more attitude and sarcasm to make her laugh. And maybe Olivia is really motivated by inside jokes about her shopping history.

As AI barrels forward, your team can prompt:

Write an email for Olivia for her to read with her morning coffee. Include 5 products she’ll like from our summer collection with a promo code for 20% off if she comes in-store. Add a lighthearted joke about her home city at the end.

Brands that can leverage their AI to write toward individual customers will be at the forefront of clienteling. And you can also see that a human element to think through these prompts will probably always be necessary, no matter how good the AI becomes. This way, AI becomes a powerful clienteling tool to provide an amazing communication experience for every single one of your clients.

Virtual Try-Ons, Virtual Appointments

The hardest part of shopping for apparel online is that the customer can’t truly try-on the products to see how they might really fit her body. Augmented Reality (AR) tools have tried to mimic how items may look in real-time, but they’ve always left customers wanting. Enter AI tools like Midjourney:

None of these are real photos, nor are these real people. Incredible, right? Now imagine if you could load up your AI tool with the exact specifications of your apparel and ask it to show how Emily might look in that yellow sundress. All of a sudden, Emily doesn’t have to step foot in a store to see exactly how that dress may look on her. It’s a level of clienteling that was only available in-person, now from the comfort of her couch.

Of course, all of these potential forms of clienteling powered by AI will have to address major issues of customer privacy (will Emily want to allow your brand to have a photo-real version of her body?), technological limitations, and – perhaps most importantly – cost. But these offerings aren’t science fiction anymore. They’re literally just around the corner.

We here at Endear are keeping a close eye on the AI revolution we’re all witnessing, and are taking steps to harness just some of its clienteling power to offer more options to our clients. It’s definitely an exciting time to be in this industry!