That retail is changing rapidly — and that many of its oldest and most established players are struggling to keep pace — is not much of a surprise these days.
“Everyone knows retailers are in trouble — at this point, the whole market knows it. And retailers also know they have a problem,” said Arish Ali, CEO of Skava.
Retailers, he said, have some clarity about where the solutions might lie. Brick-and-mortar sales — still the lion’s share of revenue for the majority of retailers — are declining and stores are being closed, which further exacerbates the problem. On the other hand, digital commerce in its many omnichannel forms is soaring, but oftentimes not enough to compensate. Those who do well have found ways to successfully fold in the in-store experience into the greater omnichannel journey.
“So there is growth, and there are a variety of platforms powering that growth directly or indirectly. The retailers who play their cards right really can capture that opportunity,” Ali said.
That is the good news — there’s the potential to turn a negative trend into a positive one. But that potential is not all that easy to tap into, particularly for the largest and most established players in the market.
“If you look at the state of [the retail] industry for the last 10-15 years, with one big exception, the dominant players are all running on old — very old — legacy systems,” he explained.
But, as Arish Ali said, that doesn’t necessarily align with a marketplace that’s becoming more sophisticated, in which consumers are increasingly expecting to see customized and personalized experiences. Those old stacks are like lead weights holding retailers back from what is possible.
“Older tech can’t deliver digital experiences,” Ali said. “And it’s amazing that this many years into the rise of eCommerce and now mobile commerce — the templates are the same. There’s a big disconnect.”
But, Ali noted, it doesn’t have to be that way if merchants step back and ask — and then answer — two main questions when trying to build and tailor their digital commerce experience.
What Is Being Sold? And Who Is It Being Sold To?
Those may seem like obvious questions to ask, Ali said, but that doesn’t mean retailers always know the answer.
And he used a brief anecdote about a partner firm who designed the mobile app as a direct copy of their website, assuming that what worked well on the web would work just as well in an app.
The problem, Ali explained, is that when evaluating their customer base, the customers who bought on mobile were very different from those who bought via the web, which meant what they bought was quite different as well.
“So we started helping them build a better mobile customer journey. At the end of the day, if a retailer isn’t delivering the right mobile experience, they’re losing money.”
That’s where bricks-and-mortar, Ali said, have something of an advantage. The customer’s physical presence gives a sales associate a lot of information to work with to build a customized experience for each shopper.
Digital merchants don’t have that physical touchpoint with a consumer, but data are a good proxy, if the right data is delivered at the right time.
“The point is to use data resources to try to understand the consumer — and all aspects of her experience, including external factors like the weather, to upsell and cross sell in a more contextually relevant way.”
For instance, if it’s snowing in Boston and sunny in Miami, Ali said, showing customers from both cities the same thing when they hit a landing page is a sure way to send at least one of them to a more relevant site.
“The data set is wide, and what we build depends on … the customer we are powering an experience for. It’s why we felt strongly that building a platform that considered that customer journey was the only way to help retailers contextualize the experience for their shoppers.”
The Tough Tech Requirements
Really understanding customer intent and offering relevant marketing isn’t easy and involves a fairly notable assist from AI to get the data-driven picture of what a consumer is doing across all of their touchpoints. That alone is tricky, particularly when consumers often change their minds while shopping.
So, we asked Ali, how do you track change of intent?
“This is where AI and machine learning comes into play,” Ali said. “We get specific intent from obvious indicators of intent like actually going to a site, searching out and buying an item, and then use machine learning to tie together all those disparate indirect intent experiences. It’s not always perfect, but when it is, it’s a magical experience for a customer.”
That smart technology magic, he said, has certain pre-conditions, particularly when it comes to integrating the backend into a more automated and usable source of data.
“It is sort of like in the early days of mobile commerce in 2008 and 2009 when retailers wanted to build apps, and retailer stacks just couldn’t handle that expansion,” Ali explained. “When you see how much of backend operations are powered by human intelligence — people filling in spreadsheets — still, it’s amazing. AI can drastically reduce an awful lot of friction and do a much better job of keeping the right things on the right shelves for the right customers.”
This, he noted, will probably not kill all human intelligence in the backend — as is widely feared — so much as turn human intelligence on the areas to which it is more uniquely suited.
“It is very hard to replace, for example, a good merchandiser’s instinct. AI, even at the highest, isn’t replicating that skilled human eye that spots trends,” Ali said. “But gifted merchandisers in the back who have a pulse of the market are in a few stores and departments and isn’t a scalable model, because it is not based on anything but individual aptitude that can’t be programmed. What retailers can do is take their best merchandisers and programmatically replicate their experience across the board. AI can be used to amplify human instinct instead of replace it.”
Those smart technology amplifications, he noted, will mean the retail journey may continue to look quite different than it does now.
Today, he noted, when one shops on Amazon, one gets the “people who bought this also bought” recommendation.
Tomorrow, retailers may know enough about your intent to offer you a pre-loaded cart the minute you enter the site, because it has a good “idea” of where the customer is going next. Talk about efficient marketing.
It may sound sci-fi today, but tomorrow it might just be how we all shop.
But the more things change, the more some things will always remain the same.
“After that it becomes about product — if you have good stuff and it is unique, people will always come to you, as long as you don’t accidentally give them a reason to go somewhere else.”