By
Andrew Park, InMoment
Companies say converting more leads to customers will be
their top priority over the next year, according to recent
research. This is certainly a worthy goal,
but it begs a natural next question — how
do you keep customers once you have them?
This conundrum is one retailers have been trying to solve
for decades. Thanks to new technologies, that’s becoming easier to do in 2017.
Recently, Walmart announced a
plan to bring Minority Report-style facial recognition technology from the big
screen to retail stores to identify and intervene with unhappy customers at
scale.
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Where
Facial Recognition Technology Provides The Most Value
Walmart may not have been top-of-mind when it comes to
innovation in the past, but a number of significant tech innovation pushes this
past year demonstrate that this legacy brick-and-mortar behemoth is committed
to evolving with, and perhaps leading significant change.
Walmart’s stated goal in implementing facial recognition is
to understand customer sentiment in real time so staff can provide support to
alleviate situations that could damage a customer’s experience around a single
transaction, as well as their longer-term loyalty.
But the potential benefits are much broader than simple
triage. Here are three scenarios where facial recognition technology can earn
retailers greater customer feedback in-store, as well as what retailers can do
to productively implement that information.
● Understanding
The Journey
With facial recognition technology, retailers can examine
touch points and flow on the journey purchase and determine how each is
impacting the customer experience, including spend, whether positive or
negative.
In-store shoppers have many interactions that collectively
determine their overall experience. That’s why retailers must work to
understand if every single touch point — interactions with sales associates, products, environment,
technologies etc. — is working well, and what can be improved if it’s not.
For instance, if shoppers typically leave a retailer’s
‘Health and Beauty’ section more frustrated than when they entered, this
indicates issues with experiences specific to that department. Granular
insights like these will help retailers make small improvements across their
overall in-store customer experiences. Armed with this understanding, human
workers can be trained to provide specific types of assistance at various touch
points to improve or enrich that specific experience.
● Personalizing
The Experience
Facial recognition by itself has interesting and helpful
applications. However, the real promise lies in using this data in concert with
other data sources and analytics technologies to gain a comprehensive
understanding of individual customers.
One of the most talked-about buzzwords of the last 18
months has been personalization. And while application of this concept has been
used primarily by digital marketers to target offers and content, a study earlier this
year confirmed that consumers value personalization during purchase and service
interactions above marketing/advertising moments, which they ranked least
important of the three.
A future scenario might be leveraging facial recognition to
understand when a customer had entered a store, and then harnessing the
plethora of other customer and contextual information to serve up a
personalized and very meaningful experience, based on past interactions and
nimble enough to read and analyze in-store behaviors and sentiment. This stream
of real-time “customer experience intelligence” could power everything from
targeted offers based on same-day comparison shopping from a customer’s mobile
device, to individual customer dossiers to support more helpful
associate-to-customer interactions.
Imagine a store manager receiving an alert that a VIP
customer had entered the store, a record of her recent browsing history of both
your web site and your competitors’, her recent purchases, as well as social
reviews and feedback she’s given about your brand — along with past and current
sentiment. Instead of extending a generic greeting, the technology would
augment the floor staff’s expertise to create a very different customer
experience, indeed.
● Anticipating
Their Needs
The ultimate promise of today’s emerging technologies and
analytics are moving beyond responding to, and instead anticipating, customers’
needs, wants and opportunities for delight. With enough data and time,
predictive algorithms can find patterns in past behaviors, and make an educated
guess at what customers, and metrics, will do in the future. This allows
retailers to avoid drastically bad experiences by preventing the conditions
that cause them in the first place. It also allows brands to identify elements
of the experience that drive the most positive business and relationship
outcomes, and proactively build those into more places along the customer
journey.
One national brand we worked with brought together
individual store sales data and goals, with customer feedback and sentiment. We
ran predictive models that identified which locations would miss sales goals,
and exactly why — by location. Armed with this information, each store manager
could focus their team on bolstering the experience in ways that both make
customers happier, and get them to their monthly sales goals.
In the past, predictive models were run almost exclusively
on structured data, and netted a respectable, but still wanting 60% to 70%
accuracy rate. By incorporating unstructured human data from facial recognition
software, social reviews and survey comments, accuracy can reach well into the
90% range.
Just like any new technology, facial recognition won’t be a
silver bullet for understanding and interacting with today’s born-digital
customers. However, applied thoughtfully, and in concert with a broader set of
data and technologies, facial recognition is set to become a very powerful lens
into one of the most elusive and important questions standing between buyers
and sellers: Why. Why do they love
this and shun that? Why didn’t they purchase? Why did they choose our
competitor over our brand? Why do they come back over and over again? Why did
they spend more this time than last? Every tool retailers can bring to the
solving of this mystery is priceless.
Andrew Park is a
customer experience expert who has spent more than a decade designing,
deploying, and consulting on CX programs for global Fortune 1000 companies. He
currently serves as Senior Director, CX Strategy for customer experience
intelligence pioneer InMoment.
