“Building the better customer experience” is rapidly becoming retail’s favorite phrase in 2017 — every merchant and their mother is currently attempting to create one.
The concept is not wholly new, of course — few ideas are — and “the customer is always right” has long been a staple in the round-up of retail wisdom. But “always right” and “totally and completely in control” are not quite the same thing.
In the U.S., 80 percent of consumers are connected to commerce 24/7 thanks to smartphones — devices that also give them nearly complete transparency into the pricing of almost anything they might want to buy. Consumers with that much knowledge and choice aren’t merely right — they’re more or less completely in charge. That gives merchants two options: run that race to the bottom or build that better customer experience.
Truth be told, there are an awful lot of competing ideas about how exactly that better customer experience is built. Like the proverbial “better mousetrap,” it’s easier to talk about than do — and the options for improvement are myriad.
This is particularly true when it comes to e-commerce players trying to leverage their single biggest competitive advantage in the experience building game — the first-person consumer data streams they have access to. Wanting to leverage that data into a better consumer experience is a rational desire – but knowing how to actually do it isn’t exactly easy for retailers that aren’t also data scientists in their spare time — or who aren’t large enough to employ a department worth of data scientists to analyze all those petabytes of information they have about customers and their habits.
And, adding to the complexity, there isn’t one right solution for all merchants, according to Reflektions CMO Kurt Heinemann — the data doesn’t and shouldn’t work for everyone in the same way.
“There is no one panacea to answer that data question,” Heinemann told PYMNTS in a recent conversation. “We learned very quickly from a correlation perspective that what is the most relevant data for each retailer is going to change — because what they do and who their customers are all quite different.”
Reflektion wants to solve that problem by combining a “sincere love of playing with data of all kinds” with the business objective of helping their e-commerce retail partners build better individualized experiences for their customers. Instead of trying to build a better customer experience, Heinemann notes, they are trying to build thousands (and eventually millions) of better customer experiences.
“The idea is to help customers convert through all kinds of ways to get products and contacts that are incredibly relevant to just them.”
And, he notes, with the launch of Reflektion Partner Data Network, the firm can now do a better job of discovering — and aggregating — insights across the network to further refine those experiences.
Why Retail Demands Bespoke Solutions
On a macro level, Reflektion uses learning AI to track every part of the consumer experience on its mechants’ sites — every click, every search, every basket add.
But below the hood, on a micro-level, is where their more interesting addition comes in — which is customization, according to Heinemann.
“We use a bespoke algorithm for each client site and for each page in the site — landing pages and product pages,” he noted. “We optimize any location we are working with to make sure it is as relevant as possible.”
Because relevance is the make-or-break in the experience — particularly as retailers are trying to grow that basket size — and it is place where the experience just tends to go off the rails.
“We had maybe a 15 minute breakdown last week in a client meeting about how you could have a detective agency around some of the recommendation and serach results that show up on pages,” Heinemann noted. “A customer is looking for a black dress — and something comes up that is neither black nor a dress — and you have to ask yourself how in the name of God did that get there. It makes you want to start digging under the data to figure out how it happened.”
Which is more or less what Reflektion did, and learned that every choice a consumer makes throws off massive amounts of data — simple things like looking at a pair of pants tosses up data about color, cut, style and pricing preferences. Separating the noise from the signal is difficult — and made more so by the fact that what is signal on one merchant’s site is noise on another’s — or at least a less important part of the signal.
Reflektion’s goal is to cut through that and help retailers keep clearly focused on signal — and then make sure that it’s beamed directly and quickly to consumers, who are more likely to convert because they’re being guided through products correctly.
“Our goal is for the consumer to see their own personal shopping aisle of goods.”
And, Heinemann noted, for merchants to be able to start building those personal shopping aisles as quickly as possible — even for customers who are first time shoppers on their sites.
Which leads to the launch of the Partner Data Network.
More Partners — More Data — Better Solutions
Given their enthusiasm for parsing ever-more specific data sets, the launch of the the Reflektion Partner Data Network makes sense — it gives them a chance to combine their data with data from various other technology and ecommerce companies.
At launch, the Reflektion Partner Data Network includes integrations with Edgecase, Narvar, BlueKai, and Yottaa. By integrating data sets from these partners, joint customers can ensure they are getting more from their data, mostly because they can see how it all interacts with each other — and from that, draw better insights.
For example, says Heinemann, by integrating with Edgecase and their expertise in shipping logistics, the team at Reflektion learned something interesting about chatbots — namely that for about a third of consumers, their main use of a chatbot is to ask it when their package is going to arrive. That tells Reflektion that more retailers need to make it easy for the customers to use the search bar to find that data.
And from partners, he notes, the data insights are almost endless.
“From another one of our integrations, we found that during afternoon hours between 1-4 pm, consumers shopping on an iOs device are shopping for female merchandise 80 percent of the time.”
That data artifact is the sort of thing that once would have been easy to “leave on the cutting room floor,” Heinemann noted, but because of the structure of the interconnected network, it is now easy to turn to a merchant partner and note that even for first-time customers they can make personalization decisions by essentially playing the rather stacked odds. If it is between 1-4 pm, starting out with female-centric goods is probably a firm starting point — with the understanding that the bespoke algorithm’s job is to keep monitoring and tweaking from there.
The challenge of Reflektion’s work of building a better series of customers’ experiences is that it is work that is pretty much never done. But being busy is better than not — and the strong response from merchants looking for better ways to leverage their data sets has been strong.
“Their response is that they are getting more value from that data,” Heinemann noted. “And then they started asking about other partners they want to be part of the network — and we were surprised how quickly they latched on to the concept and then started wanting access to more data sets.”
And it’s access that Reflektion is excited to give them — and can give them sooner rather than later. Heinemann says that within the next few months, they will be rolling out an even longer list of participants in their Partner Data Network.
We’ll keep you updated when they do.