Consumer expectations and behaviors have seen a seismic shift in the last several years due to COVID, yes, but also the ongoing, systemic proliferation of digital technologies powered by cloud services, AI, and machine learning.
As AI continues to develop, so does its ability to ‘learn’ smart responses to a growing array of challenges, helping customers and retailers navigate the holidays and beyond through ways of mitigating labor and inventory challenges, enabling personalization and reducing friction in the buyer journey.
That’s good news; the challenges retailers face today are only set to mount up as the industry marches forward into a deeply uncertain decade.
New tools will be needed to meet persistent problems caused by inflationary woes and the maintenance of competitive business models as globalization progresses.
Notes Vance Clipson, a senior principal at Nuance (an AI-powered service provider) in an interview with RETHINK Retail, “The tight labor market, and attracting and retaining agents through improved empowerment and experience are just a few of the problems retailers are facing.”
Building socioeconomic pressures such as rushing, historic inflation (near 10% YoY in multiple countries), labor shortages, an increased rate of ecological disasters, and the threat of an official recession all call for the leveraging of new AI and ML-powered tools to affect efficiency gains, a strategy that has become the steady marching beat of the retail industry as a whole.
The Ever-Evolving Effort to Manage Customer Needs
For some experts, of these roadblocks, one stands out in particular: managing those ever-evolving customer expectations. That’s Sebastian Reeve’s view, Director of Intelligent Engagement at Nuance. “Retailers are under pressure. These new customer expectations first come to mind,” he notes.
“It’s the same old story,” argues David Leibowitz, general manager for retail and consumer goods industry at Microsoft. “Retailers are being asked to do more with less, but also to do more to meet the evolving expectations of their customers.”
“Using tools and technologies like AI shorten time to market in response to these pressures,” he continues, explaining how AI fits the call for greater and greater efficiencies.
Yet, to understand how best to leverage those new technologies, one must understand the specifics of the task before them. If retailers need to address new customer expectations, what exactly are they?
First, on a basic level, it should be understood that brick-and-mortar isn’t going anywhere despite some dire predictions to the contrary within the last many years (brick-and-mortar sales, after all, grew faster than e-Commerce in 2021).
Contends Reeve, “The human desire to get back to more social, in-person interactive experiences is there in the big rush back into stores within the last year.”
The point? Retail strategists need to keep their eye firmly on how physical store experiences can mirror digital store experiences (and vice versa).
The reason is simple enough on paper: particularly after COVID, consumers became more tech-savvy about digital shopping than ever, and even previously underrepresented demographic groups (e.g. much older shoppers) joined in on e-Commerce in a way they hadn’t had occasion to before.
Notes Reeves, some of the changes in consumer expectations are now ‘settling in’ to one increasingly-clear lesson in particular, however: the need for robust omnichannel engagement both physical and digital in response to consumers’ ever-growing demand for a personalized, streamlined, frictionless ‘Just Walk Out’ shopping experience.
In other words, to join the intelligent data-centered shopping experiences of e-Commerce with the immediacy of local retail. That type of personalization and convenience is ‘it’ in a nutshell.
Yet, while retailers have largely accepted the need for more sophisticated, data-driven omnichannel consumer engagement, what it actually means to successfully achieve that engagement continues to be negotiated and discovered.
“Personalization is where many consumer expectations are going, and it can get tricky,” continues Clipson.
That shoppers want in-store experiences to know them as well as algorithm-powered ads do on big-box retailers sites is one thing, he continues. Actually defining that in-store in a way customers will consider and accept will require ongoing shifts on how much technologies such as AI can be an increasingly-intimate part of public and private life.
Helping the New Customer to Help Themselves: How Conversational AI Steps In
The good news is that those shifts are happening, Clipson maintains, and are on a likely course to meet new implementations of AI technologies so long as they are done tactfully, with intention and precision (though varying concerns will inevitably remain according to recent Pew research, as are there regional considerations).
One way of doing this is what can be called conversational AI, defined most easily as technology that enables humans and machines to communicate in their natural language with clarity and effectiveness whether by speech or text.
It’s a capability that in the past was largely resigned to theories such as do machines have the ability to exhibit intelligent behavior that is equivalent to, or indistinguishable from, that of a human. (Turing Test)
It’s yesterday’s science fiction working for us today, and indeed, during the height of the COVID-19 pandemic, its these very AIs that eased pressure off of immensely short-staffed and overtaxed customer relations agents in answering routine questions regarding masks, safety, and other CDC procedures.
The broader question remains, however: how exactly does a machine’s ability to read and understand human inputs manage other retail challenges, particularly beyond answering simple questions?
The short answer is pretty much everything that involves human communication, even when AIs aren’t being directly interacted with, but rather, are monitoring conversations between (e.g.) agents and customers.
Indeed, AI can do perhaps more than any other growing retail technology to affect that aforementioned blend of digital and physical shopping experiences, bringing those two worlds together via recommendations that greet customers—and their data—with a digital smile of sorts.
Keeping on the subject of conversational AI that ‘monitors,’ however, this tech has another application that is likely less-readily thought of: preventing retail theft and stopping scams/fraud before they can succeed in a way that protects both the store and customers.
By learning telltale speech and digital biometric patterns and having a database of existing fraud attempts, AI can reference a wealth of data in a way the human simply couldn’t, and all in real-time, creating alerts and warnings while the efforts are in progress.
It all adds up to that personalization that’s so sought after, but just as important is the way in which it all takes those aforementioned pressures off the backs of attrition-prone labor at a time when shortages continue largely unabated.
Yet, for retailers looking to turn the bend on adopting these technologies—particularly as the holidays fast loom with a rush of customers fated to meet with reduced staff—knowing they exist (and knowing you need them) isn’t enough. That’s where AI providers such as Nuance come in.
Acquired by Microsoft following significant successes in addressing the needs of pandemic-stricken retail operations, Nuance focuses on not only providing AI services aimed at the varying applications discussed above, but helping them to implement it intelligently by looking at retailers’ needs, settings goals, and tailoring their service to match.
“It isn’t truly about the technology, but rather delivering services that create real business outcomes. There are lots of misimplemented technologies out there,” reminds Reeve.
Retailers will need both the expert attention and the tech to meet a holiday season that is expected to be as fervent as ever despite inflationary pressures.
Nothing is ever truly new under the sun, though, an idea as trite today as it is stubbornly true. AI is an exciting, fast-developing technology meeting an old need: efficiently getting customers what they want. To survive into 2023 and beyond, retailers will need every ace up their sleeve to do just that.
