By Gary Saarenvirta,
Daisy Intelligence
Today, offering WiFi
access is so ubiquitous that seeing an ad for
it seems odd. But check out the window of your
local coffee shop and you might still see an old,
fading sign that says, “WE OFFER FREE WiFi!” Exclamation point and
everything.
By now, merchants know WiFi is an expectation, not a value
add. But when WiFi
was first introduced, it represented a new
form of retail one-upmanship.
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You can
always introduce products to outflank the
competition or renovate a store with shiny new
shelves, but WiFi was different in that it was something consumers could not see, hear or feel. But it
was transformational.
Artificial
intelligence (AI) is similar in that it is invisible, impactful, and transformative, but retailers should pause before jumping
on the bandwagon. According to a forecast by market
research firm IDC, retailers will spend $5.9 billion on AI tools this
year. Throw in the fact that the term “AI” is
the technology du jour, if you will, and it’s easy to understand the urgency with which CEOs are questioning their AI strategies — and examining whether or not they even have one.
However, just because a
benchmark for deployment exists doesn’t mean every retailer needs to jump on
the bandwagon and implement a new technology. Companies have their own specific goals around revenue, profit
margins and expenses, so decisions and ROI should be calculated based on
those goals.
Next, let’s consider
what AI is. It’s often used to describe everything
from basic predictive analytics (where historical data is used to guess what
might happen in the future) to chatbots on an e-Commerce site. Recent research,
however, suggests AI based on reinforcement
learning is the
technology that will truly make a difference in complex environments like
retail. By conducting
experiments, reinforcement learning identifies what to do based on the results
in a trial-and-error fashion.
Finally, and possibly most importantly, AI isn’t something retailers can just go out and buy like
other technology solutions. Identifying and/or
building a custom-made AI solution tailored to specific business needs is
complex and needs to take into consideration the desired outcomes, and your competitive
landscape.
Confusion around an
emerging technology is not new. Remember virtual
worlds like Second Life? Retailers were encouraged to set up shop there, but
it’s practically a wasteland today. Think of mobile apps as well. Should every retailer have one? Some experts suggested it at first, but today retailers
are encouraged to maintain a solid, informative, mobile-ready web site instead.
The AI Use Cases Retailers
Should Consider
To gain a
competitive advantage through AI, take inspiration from your smartest customer. You know
the one — the customer who seems to have done a lot of research before they
come into a store. And even once they have a product in their hands, they have
specific questions about how it will work in the context of their daily lives.
You know they’re likely to make a purchase, but their meticulousness means they
are more likely to recommend your store to family and friends if they have a
good experience.
Investing
in AI is similar. Take the
specific situations and questions asked by
your smartest customers and consider them your
“use cases.” Instead of jumping on the AI
bandwagon out of fear, what are the areas within your company where AI can do things humans could never do, even if you hired
an army? Do you have data on which business
recommendations and decisions can be made using sophisticated analysis
and interpretation? If so, there’s an opportunity for AI.
Once you
find the right AI use cases, everything else follows — from the specific
companies to work with to the way your processes and compensation packages will
be adjusted. Examples of the best AI use cases in retail include
promotional product selection and pricing.
When it works well, true
AI — which has been deployed to deliver optimal benefits for retail
environments — isn’t technology that consumers will
notice the way they came to look for WiFi signs. That’s because AI automatically
and transparently improves the
retailer-customer connection — and the bottom line.
Gary Saarenvirta is
Founder and CEO, Daisy Intelligence, leading the development of the
company’s AI platform that transforms massive quantities of consumer data into
profitable decisions. A preeminent authority on AI, Saarenvirta works with
leading global corporations to drive revenue and growth. The former head of IBM
Canada’s data mining and data warehousing practices, he also led Loyalty
Consulting Group, providing analytical services for one of the world’s most
successful coalition loyalty programs, the AIR MILES® Reward Program. Saarenvirta
holds a B.A.Sc. and M.A.Sc. in Aerospace Engineering from the University of
Toronto.
