The Predictive Retailer - Dynamic intelligence and the science of connected customer experiences - Sizmek
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The Predictive Retailer Dynamic intelligence and the science of connected customer experiences
Contents
New frontiers in shopper science 2
Predictive marketing and trend forecasting 6
through machine learning and artificial intelligence
Agile operations: Leveraging dynamic intelligence 16
to become a predictive enterprise
Functional integration: Converging digital and 22
physical consumer experiences
Building a predictive retail enterprise and data-driven ecosystem 27
The connected consumer experience: Leveraging data 28
flows to optimize brand connections
Conclusions 31
Five strategic imperatives for predictive retail 32
1
© 2017 Sizmek Inc. All rights reserved.
New frontiers in shopper science
The impact of the web on retailing is so However, the explosion of data goes both
profound, it’s hard to remember what life was ways. Shoppers are bombarded by ads and
like before online shopping existed. The global offers from increasingly homogenous retail
retail market will see steady growth over outlets. Retail has become so commoditized
the next few years, and in 2018, worldwide that customers are faced with the tyranny of
retail sales will increase 5.5 percent to reach choice—typing “red shoes” into the Google
$28.3 trillion USD.1 Digital technologies search bar returns 280 million Google
power almost every step of the consumer Shopping hits. Physical retailers that don’t have
path to purchase. Shopping is no longer just a a digital presence cannot compete, and digital
weekend activity or an errand you run when retailers must have a way to stand out and get
it’s convenient, but rather a perpetual and shoppers to take notice.
cyclical journey that can happen 24 hours a This saturation is a marketing challenge in
day, 7 days a week. which the traditional “funnel” and “spray
The amount of customer data generated by and pray” advertising methods no longer
this around-the-clock shopping activity is a prove successful amidst the ever-increasing
retailer’s dream come true. The explosion abundance of messages competing for share
of e-commerce, the advent of mobility, and of wallet and mind. But it’s also a tremendous
efficiencies driven by programmatic marketing challenge to provide a distinctive shopping
have created a wealth of opportunities for experience. Retail customer service needs
brands to capture signal-rich audience data. to be at a whole new level. Shoppers expect
no less than instant gratification, real value,
1
“ Retail sales worldwide will top $22 trillion this year,” eMarketer, and exceptional experiences. Nordstrom is
December 23, 2014
renowned for its above-and-beyond customer
2
© 2017 Sizmek Inc. All rights reserved.
service—hand-delivering the perfect pair analyze, and optimize these moments between
of shoes or taking returns on products it the brand and consumer.
doesn’t even carry. Today, that tier of service
At the intersection of these advances in
is the baseline, and retailers are constantly
digital commerce, consumer connectivity,
pushing the envelope with touches such as
and big data, is the rise of machine learning
Zappos’ surprise upgrades to VIP services and
and artificial intelligence (AI)—which enables
Amazon’s same-day delivery.
marketers to not only more accurately predict
“In a world where the assortment is endless, the context in which a customer would be
and price and convenience factors have been most receptive to a message to make a final
exhausted or are no longer a competitive purchase decision, but also empowers retailers
advantage . . . consumers are going to want to automate and transform customer service
real interaction,” said Cal Bouchard, senior experiences altogether. Savvy retailers are
director of e-commerce at The North Face, a already employing artificial intelligence to
brand that is pioneering the use of advanced create distinctive and transformative shopping
technology to create exceptional customer experiences. The Amazon Echo, a hands-free,
experiences. “So I think technology that can voice-controlled digital assistant, lets you do
further interactions, help brands and retailers everything from play your favorite music tracks
tell stories, and make consumers feel special to reorder toilet paper using Amazon Alexa
will be the key.” 2
AI technology. At The North Face, an IBM
Watson-enabled search engine helps you find
That enormous volume of transactional data
EXPONENTIAL GROWTH OF COMPUTING the perfect jacket by analyzing the weather,
being generated by shoppers is the key to
your activity level, your gender, and whether
retailers creating distinctive, personalized
you’re in a remote or urban location, just from
shopping experiences for their customers.
a few pieces of information you provide. Macy’s
In the future, successful retailers will be
is developing Macy’s On Call, its own intelligent
those that can use this data (anonymously
shopping service based on Watson technology.
or pseudonymously, to protect privacy) to
enable smarter investment decisions that IBM, Apple, Microsoft, and other major
capture mindshare and influence omnichannel technology players are making their AI
purchase decisions. Retailers must use this technology available to businesses, including
data to create value for audiences throughout retailers, via third-party application
the entire path to purchase. However, the programming interfaces (APIs). Within a few
human mind alone can no longer process all years’ time, AI will be everywhere. But the real
the digitized transactional moments that are power of AI is not just in using it reactively
now generated in real time—let alone govern, to provide valuable information and great
experiences based on customer input. Data
2
“ AI and virtual reality may propel future of retail,” Computerworld, management platforms must become decision
February 4, 2016
management platforms. The most successful
retailers are those that will be able to share
3
© 2017 Sizmek Inc. All rights reserved.
AI modeling and machine learning intelligence real-time visibility and actionable intelligence
across systems to be truly predictive and available from the IoT is becoming a reality.
responsive in real time. They will discover and Digital technologies are not only creating
fulfill customer needs that are not always on wholly new capabilities—automation, for
the surface by putting millions of actions example, enabled by embedded analytics—but
and data points into context. These predictive are changing the role of employees, redefining
retailers will be the market leaders of how retailers operate their stores at scale.
the future.
Big ideas around connected customer
As retailers become more skilled at harnessing platforms continue to pave the path to
big data to build predictive intelligence purchase in more interesting ways, fostering
capabilities, they will learn to create more innovation in experience optimization as well as
personalized customer experiences and retail operations. For example, we are moving
drive operational efficiencies throughout from a retail landscape where digital and
their organization as a result. Predictive physical retailers compete for market share to
technologies can be useful across many an era where physical and digital experiences
different applications—powering product converge to provide one holistic shopping
recommendation systems, providing product experience. Apple has long been an example of
assortment and planogram analytics with the a retailer that strives to blur the line between
help of in-store spatial recognition systems, a physical and digital shopping experience.
using information from shopper radio frequency Luxury retailer Burberry is successfully
identification (RFID) and beacons to customize merging the more practical aspects of digital
digital and physical shopping experiences, and shopping with the sensory physical shopping
automating mundane retail tasks by combining experience—so critical to luxury shopping—
advanced technologies in drone delivery with online profiles, global purchase history,
services, mobile payments, checkout optimizers, and in-store technology, fueling a more
and connected supply chain platforms. personalized, efficient, and fulfilling store visit.
As these technologies are streamlined to Meijer and other grocery chains are making
function seamlessly on a unified platform, shopping more convenient for customers with
retail marketers will capture unique attributes digital ordering, auto list creation, and pick-
per device that will allow them to provide up and delivery services—a combination of
opportunities to message to individual devices services that lets shoppers spend as much or as
more meaningfully and be more predictive little time in the store as they wish.
about what customers want to do next.
These smart retailers understand that while
The Internet of Things (IoT) is fueling the digital engagements can be convenient, so
next wave of connected, technology-enabled can dropping by the store on your way home.
disruption. IoT-driven developments offer Shopping in the future doesn’t mean the
retailers the chance to harness new levels elimination of physical stores, but rather the
of connectedness. The promise of increased convergence of digital and physical in the way
that best suits the individual, to make shopping
easier, more satisfying, and more relevant.
4
© 2017 Sizmek Inc. All rights reserved.Predictive retailers make this new kind The fundamental shift in shopper science
of shopping experience look easy: it isn’t. technologies is propelled by self-learning
Sophisticated practitioners use a multitude of systems that get better at tasks over time.
wireless and integrated systems to combine Imagine a recommendation engine that
existing operations with digital touchpoints knows not only which clothing styles you
to focus on customer centricity, supply chain like, but which ones will fit you best and
resilience, and in-store operational efficiency. which colors work on you, and recommends
Harnessing effective connected retail clothing knowing that you’ve gone up or
applications starts with the integration of data down in size—just like the best and most
across disparate systems. This integration trusted salesperson or personal shopper
offers a wide array of applications that can you know. Automation workflows that
sense, connect, correlate, and automate enable these kinds of breakthroughs are
operational and logistical processes while
being elevated by technologies powered by
gathering keen customer intelligence that
machine learning and artificial intelligence.
can infer future purchase behaviors. Business
AI is already disrupting countless industries
leaders recognize the need to leverage
by eliminating menial tasks, enabling more
customer data through connected platforms
accurate personalization standards that drive
in ways that make their organizations smarter,
brand value, and creating more resonant
more efficient, and poised for growth and
experiences that can both amplify and
profitability.
optimize the entire customer journey.
In short, there are three significant macro-
Intelligent and connected customer
trends in retailing that will completely disrupt
experiences are all centered around a
the industry, by using amplified connections
framework in which AI in the future will
to push the boundaries of what’s possible in
separate the signal from the noise; determine
business efficiency and customer service and
what will make a message more resonant;
adding tremendous value to the retail industry
identify what products are important to
and the shopping experience:
specific audiences at both individual and
• Predictive marketing and trend forecasting
household levels; know exactly where to place
through machine learning and artificial
a product on the shelf in a specific aisle; and
intelligence
figure out how to make delivery processes so
• Agile operations: Leveraging dynamic seamless that anything beyond the touch of a
intelligence to become a predictive single button will seem like overexertion. It will
enterprise change not just retail, but all customer-facing
• Functional integration: Converging digital industries, and lead to implications around how
and physical consumer experiences we connect with brands and each other.
5
© 2017 Sizmek Inc. All rights reserved.Predictive marketing and trend forecasting
through machine learning and artificial intelligence
Digital transformation in retail and beyond interactions and web connectivity are flowing
through modern technology platforms at a
With the widespread adoption of the web
lightning-fast rate.
comes a combinatorial explosion of big data—
an unprecedented volume and intersection of What does technology transformation mean
attributes with which we can drive business to retailers? How can they use it to thrive, not
growth and uncover insights and connections just survive? More data and more channels
that previously remained in the dark. How do mean being able to predict and inform
you harness, govern, and derive meaning from future outcomes. There are more digital
this explosion of data? and physical paths to purchase. However,
data fragmentation makes identifying and
“Machine learning is the automation of
understanding these paths a huge challenge.
discovery—computers learning by themselves
Retailers must evaluate every customer
by generalizing from data instead of having
interaction at the level of the touchpoint
to be programmed by us,” AI expert Pedro
or impression, understanding all there is to
Domingos said in a 2015 interview. “It’s like
know about the moment in which a message
the scientific method on steroids: formulate
can be made relevant and resonant for a
hypotheses, test them against the data, refine
customer. The age of programmatic media
them—except computers can do it millions of
buying has created an environment rich with
times faster than humans.” 31
these types of stage-gate signals, which now
Machine learning and AI are already beginning enable understanding the intersection of
to power the next generation of innovations, physical and digital experiences. The state of
including autonomous cars, personal data collection for decision-making enhances
assistants, simulation sciences, fuel and experiences because customer interaction
microbe production, and medical diagnostics. today is a conversation. It’s no longer about
Countless bits of data captured from digital preparing to respond. It’s about listening,
3
“ A Q&A with Pedro Domingos: Author of ‘The Master Algorithm,’” asking, answering—it’s a two-way interaction
UW Today, September 17, 2015
that creates deeper connections between the
brand and client.
6
© 2017 Sizmek Inc. All rights reserved.Programmatic marketing delivers an data reporting, digital data is both unique
explosion of data to the individual and longitudinal, making it
possible to understand and target the exact
What is programmatic marketing, and what
person, over time, across locations. Consumer
part does it play in predictive retail? At
segmentation models that once drove all
the start of the millennium, we had digital
marketing efforts now serve as a first filter,
advertising networks. These networks
augmented with digital knowledge and applied
evolved into ad exchanges, in which display
to the unique engagement.
impressions could be funneled through a
central inventory system. Demand-side All of these moments, in aggregate, inform
platforms could connect and bid on each retailers as they devise ways to automate
individual opportunity to show someone an processes, shorten purchase cycles, predict
ad prior to that person’s browser loading. trends, and personalize customer experiences.
Along with this evolution, an influx of data Programmatic technology can enable
captured from programmatic campaigns businesses to not only automate the process of
ignited a series of shifts at the intersection of collecting and modeling customer engagement
digital marketing, e-commerce, and customer data, but also automate decision-making and
experience, which created the opportunity for the sharing of intelligence with other systems—
programmatic marketing. all in real time. With self-learning algorithms,
these automated real-time decisions become
With programmatic technology, retailers
more accurate with each iteration. Upwards
and consumer brands can capture audience
of trillions of daily customer interactions
intelligence through integrated moments.
means that programmatic technology today
We can already measure some transactional
is an extremely comprehensive capability
moments—a single interaction on a website
that leverages the increasing connectivity
or instances of “showrooming” (that is,
of digital technologies to drive actions and
browsing for a product at a physical store
improve results, provides an infrastructure for
and then purchasing the product online
operational agility that creates unparalleled
from a competitor). But the transactional
efficiencies, and reveals predictive insights
data available to retailers is becoming more
with intelligence that flows bidirectionally
sophisticated with new technology: in-store
across systems.
behavior monitored by a connected device,
digital signage displays that influence purchase Paving the path to purchase starts with the
patterns, automatic checkout via RFID or collection and integration of data, combining
mobile wallet solutions, and autonomous a broad variety of attributes from media and
customer service representatives that can marketing observations to track demand,
match you with the right size or offer style sentiment, and brand affinity, while combining
suggestions. Unlike most point of sale (POS) these elements with product-specific tags and
logistical proxies.
7
© 2017 Sizmek Inc. All rights reserved.The critical piece here is integration. There’s As customers are increasingly becoming the
vast potential for new connections, and the masters of their own digital universe, with the
ensuing data that companies can harness for ability and growing expectation to personalize
performance and insight is what will drive these journeys in new ways—thanks to
innovation. The rich data sets that will result emerging technologies such as wearables
from these connections make possible a new and augmented reality—these complexities
level of predictive intelligence and agility in will prove challenging. More journeys, many
business. However, growth and innovation in of which are more personalized, don’t lend
the digital sphere also stimulate new complexity. themselves well to the old way of marketing.
The maze of shopping journeys Companies need a new way to gain an
understanding of these more nonlinear,
To illustrate the new complexity of this unconventional shopper journeys and what
digital transformation, consider how the influences audiences to make a purchase.
shopping journey has evolved over time. Cisco
If retailers want to synthesize this complex
conducted research in which it evaluated the
array of shopper marketing channels,
variety of shopping journeys, from the brick-
they need to make a pragmatic shift from
and-mortar days through the age of Amazon
traditional segmentation approaches to
and other e-commerce platforms, and looking
refined predictive solutions. The first step
forward into the IoT era. With each shift came
is to understand the range of paths to
a combinatorial explosion of complexity.
purchase and the most common avenues to
According to Cisco: “Shopper interactions in the destination. However, being predictive
the past added up to a total of three linear also means understanding every individual
shopping-journey options: in-store, through touchpoint along each of those paths.
a catalog, or prompted by print or broadcast-
Every one of those individual moments contains
media advertising. The advent of e-commerce
vital contextual data that can inform how to
expanded this number to approximately 40.
influence that shopper’s behavior within that
Now, IoT promises more than 800 unique
unique instance. The result is that the retailer
variations of possible shopping journeys.”42
can make a decision that suits the precise
Managing this complexity has become context of a shopper—where she is, her goals,
increasingly difficult, even impossible, for and even factors like inventory or the weather at
retailers using legacy marketing approaches, the time. The key is to be able to serve the right
broad audience segmentation, and dated message as the single opportunity becomes
targeting strategies. And the number and available. Programmatic infrastructure enables
complexity of shopping journeys is not about this. Brands can dynamically deliver on specific
to slow down, but will continue to multiply. needs, or even predict needs that the customer
4
“ Winning the new digital consumer with hyper-relevance: doesn’t realize she has.
In retail insight currency and context is king,” Cisco, 2015
8
© 2017 Sizmek Inc. All rights reserved.The variety of journeys available to shoppers is
growing exponentally
Store Both Non-store
PRODUCT PRODUCT
RESEARCH PURCHASE RECEIVE SUPPORT
PRE-AMAZON ERA
In-store
browsing
3
Staffed In-store In-store
checkout pickup associate
Print/
broadcast
Journeys
Catalog Phone Home Call
payment delivery center
OMNICHANNEL E-COMMERCE ERA
In-store
associate
In-store
browsing
Staffed In-store
checkout pickup Call
40
center
Print/
broadcast
Journeys Email
PC Home
payment delivery
Catalog
Online
chat
INTERNET OF EVERTHING (IOE) ERA
In-store
associate
In-store
browsing
In-store Interactive
pickup kiosk
Digital Staffed
signage checkout
Deliver Retail
800+
to car mobile app
Print/ Self-
broadcast checkout
Journeys Drive-thru
pickup
Live
video
...and growing Mobile
Retail device
mobile app payment
Secure Call
locker center
Web PC
search payment
Home
delivery Email
Retail
website
Online
chat
Source: Cisco Consulting Services, 2015
9
© 2017 Sizmek Inc. All rights reserved.PERFORMANCE
PREDICTIVE
MARKETING
Maximizing opportunities at individual
touchpoints while leveraging real-time
PROGRAMMATIC data and machine learning
MARKETING
Marketers learned to buy single
impressions in real time through the
transformed infrastructure
DIGITAL MARKETING
The “spray and pray” model of simply
moving what worked in “terrestrial” to
the digital ecosystem
ADVANCED AUTOMATION
Source: Sizmek Institute research
Predictive marketing: From personalization automated optimizations to occur. Marketers
to moment maximization no longer need to manually throttle inventory
or shift media budgets to the highest
In today’s world, there are two major
performing tactics. The science of prediction
value drivers for any business solution:
emerged when individual impressions were
performance and insights that drive more
valued against respective outcomes—and
performance. In retail, optimal performance
consequently, each moment could then be
results from offering value at a shopper’s
evaluated based on its likelihood to deliver
critical moment of need and resonating with
a specific result. This works very well, as AI
the customer in a way that impacts their
predictive models inherently apply contextual
decision. Immediate action requires more
and behavioral attributes along with millions
than real-time reflexes—true immediacy
of other features to expose the most relevant
requires companies to think predictively.
message to a consumer.
As more impression opportunities became
The most successful companies will be those
available, more data attributes and variants
that can predict relevance and resonance
could be utilized in real time to make a
within a specific moment in time to present
targeting decision. But this approach still uses
someone with the optimal message.
programmatic marketing from a segment view
Companies can then deliver meaningful and
of the world rather than an outcome-based
personalized experiences by anticipating
view. As programmatic continues to transform
ways to drive efficiencies, offer savings, and
the digital advertising industry, and marketers
deepen brand engagement with a customer
focus more on business outcomes than on
throughout the shopping lifecycle.
targeting tactics, artificial intelligence allows
10
© 2017 Sizmek Inc. All rights reserved.Relevance and resonance— By applying analytics, a retailer could see
beyond personalization that a particular shopper in a store buys
A common error marketers commit is mistaking many automotive products and could infer
personalization for relevance and resonance. an enthusiasm or aptitude toward cars. That
We’ve all gotten a personalized email, where is interesting information, and a coupon for
a retailer addresses us by name. That’s not Castrol Oil may or may not be useful. But
enough to impress today’s savvy shoppers. But imagine that a shopper is in a store and sensors
even an email suggesting clothing related to determine that his shopping cart is traveling 20
lifestyle or special events may not catch the percent faster than average. That customer is
attention of a person who is, at that moment, in a hurry. He doesn’t need a coupon. He needs
in a home improvement store shopping for a to find the fastest way through the store. In the
yard project. That customer is a very specific real-time context of that moment, automatic
shopper around whom there is a whole other processes that help the shopper check out and
opportunity to engage on a personal level—in a get out quickly are more relevant and resonant.
way that fulfills immediate needs and leverages
Personalization can be a significant factor in
what is top of mind for that person.
deepening brand engagement. However, the
Relevance and resonance arise when a deeper context of relevance in the moment and
retailer knows what you need—sometimes a more memorable, resonant experience are
before you know it yourself—and enables you what build customer loyalty and relationships.
to accomplish what you want to do at that Creating the opportunities to achieve this level
moment—whether that is maximizing loyalty of precision starts with predictive intelligence
points, getting through a checkout line quickly through data and analytics.
to catch a flight, or obtaining help from a
Data will soon connect the store and the
qualified customer service rep.
home, through which personal preferences
Geo-location in a city or even in a store, the and convenience will continue to be optimized.
browsing history of a smartphone, or interaction Relevance and resonance will exist wherever
data from a Bluetooth beacon can all help shopper experiences can be accessed and
a retailer make the right decision on what specific customer demand can be met.
message to provide that customer—without
The building blocks of dynamic
using any personal data about the individual
customer intelligence
holding the device. Whereas personalization is
explicit, retailers’ efforts to create relevance and Many retailers already engage in data-driven
resonance may be virtually imperceptible to the marketing—how does that become predictive
customer. Yet it’s enough to enable the retailer customer intelligence? Twenty years ago,
to create an experience that is more efficient, every retailer planned around a static shopper
cost-effective, and satisfying—that resonates and persona, using planograms, assortment, price,
creates a connection. and promotions—all very broad action options
that were often based on outdated information.
With predictive intelligence, retailers can
11
© 2017 Sizmek Inc. All rights reserved.look at customers in a more dynamic way. business intelligence tools, a data management
According to Rama Ramakrishnan, chief data platform, a marketing automation platform, and
officer for Demandware, “The key value stems campaign management systems. When trying
from the way predictive models look at both to unlock and understand a customer journey
product affinities and customers with similar that is nonlinear and complex, broad audience
preferences. This allows retailers to present targeting segmentation won’t get the job
individual customers with new products or done. However, creating data architecture is
promotions they normally wouldn’t have a good start, because customer segmentation
considered or been aware of—but which data forces you to think about what is similar and
science predicts they will actually enjoy. The what is different about the composition of
result: vastly enhanced new opportunities for
your customers. The key is to always improve
personalized product discovery.”53
these audience characteristics over time. This
Traditionally, business intelligence (BI) and is why an agile and iterative analytics cadence
customer intelligence (CI) relied on data results in better insights and more optimal
delayed by days or weeks that was not tied to performance. The segmentation in an audience
any individual. In the 1980s and 1990s, insight data architecture is based on sophisticated
that informed product development, location modeling of real-time moments.64
investments, and other similar initiatives took
months to gather, requiring manual market Redefining segmentation
research, focus groups, and other time- Predictive marketers of the future will still
intensive activities. use some core segmentation strategies to
Future success lies in dynamic intelligence: organize audience data. But more advanced
real-time, individual-level, in-the-moment data use cases will continue to drive efficiencies in
that allows for direct action. Immediate digital performance and insight.
data that is properly collected and managed For instance, AI-powered systems can
lets you spot signals in a much faster, more syndicate segments back and forth, improving
complete, more actionable way. Dynamic audience definitions, refining clusters at an
intelligence has several key features. attribute level, and in turn making them richer,
based on more fundamental features.
Creating an audience data architecture
An audience data architecture, or customer Leveraging propensity models
taxonomy, refers to how you organize your Predictive marketing moves away from broad
data in a centralized system. In the case of segmentation and toward using probabilities
predictive marketing, the system is most likely a to make more informed messaging decisions
marketing stack—a combination of a customer that amplify the customer journey. Propensity
resource management (CRM) system, models (also called likelihood models) are core
“ Predictive Intelligence—The Next Stage in Retail Personalization,”
tenets of predictive intelligence and analytics.
5
Multichannel Merchant, April 20, 2016
These models make educated estimations
6
evin, Dominique, “The definitive guide to predictive analytics for
L
retail marketers,” 2015
12
© 2017 Sizmek Inc. All rights reserved.about a customer’s future behavior—this is products to achieve maximum margins. And
because a customer’s previous interactions, in another scenario, the system could use
such as browsing behavior, previous purchases, predictive modeling to help executives decide
and interests, as well as metadata about their whether or not to open a retail store in an
devices and thousands of other variants, in up and coming part of town. City planning
aggregate paint a holistic picture of the entire and urbanization data can be integrated
customer journey. Propensity models can with census data to deepen reporting and
be used not only to maximize moments of understand how that store can achieve steady
influence, but also to provide a snapshot of a profitable growth.
business’s most valuable customers.
This type of forecasting most certainly applies
Trend forecasting: Advanced to making decisions on what future products
recommendation systems retailers will put on their shelves both
Future use cases for recommendation systems physically and virtually. Being able to combine
are abundant. The key is in the data pass data sets from pertinent sources will enable
back and syndication capabilities of retail innovative retailers to forecast future trends
information systems once they are connected as they begin to emerge in product categories,
through APIs. These are the foundational so they can make more accurate investments
connections that will power the Internet of at wholesale prices, saving millions of dollars
Things in retail. These connections are the before markets catch on and drive up prices.
pipes through which signal-rich data can inform This will be critical, because this inherent data
how to engage and influence customers; enable will not only give retailers insights on what
marketers to deliver specific information, they should stock up on in the short term but
convenience, and resonant experiences; and also what types of products to start investing
find early triggers for wise investments or in before those products saturate the market—
logistic decisions. providing strong ROI potential. As a result,
retailers that implement this competitive
In the future, achieving granular purchase-
advantage will not only be perceived as
based insights will be as simple as presenting
bleeding-edge innovators in the latest and
the system with the data inputs and desired
greatest products, but will also be more agile
outputs or business objectives. In one
operationally. They will have critical insights to
instance, the system can recommend the top
steer their businesses in the right direction.
three creative assets for a site to display that
will increase conversion rates for specific Gearing up for connected and predictive
lifetime-value customers. In another example, customer platforms
the system could recommend how to bundle Gearing up for connected and predictive
customer platforms
13
© 2017 Sizmek Inc. All rights reserved.Example: Category Cluster DNA
CLUSTER 1: SWEATERS CLUSTER 2: ACTIVE WEAR
1.0
7.0
6.0 0.8
5.0 0.6
4.0 0.4
DNA
DNA
3.0
0.2
2.0
0.0
1.0
-0.2
0.0
-0.4
SWEATERS
CLASSIC SPORTSWEAR
IMPORTS
DESIGNER
COLD WEATHER
YOUNG CONTEMPORARY
ACTIVE
OUTERWEAR
SUITING
CONTEMPORARY
FASHION ACCESSORIES
DAY DRESSES
SPECIAL SIZES
LADIES
BEAUTY
INTIMATES
JEWELRY
HARD HOME
HANDBAGS
SOFT HOME
SWIM
EVENING DRESSES
KIDS HOME
CLASSIC SPORTSWEAR
SUNGLASSES
ACTIVE
WATCHES
FURNISHINGS
OUTERWEAR
YOUNG CONTEMPORARY
GIRLS
BOYS
CONTEMPORARY
KIDS
MEN’S
-0.6
YO U N G C O N T E M P O R A R Y
OUTERWEAR
ACTIVE
SWIM
C O L D W E AT H E R
SUNGLASSES
IMPORTS
WATC H E S
UNKNOWN
CLASSIC OUTERWEAR
LADIES
CONTEMPORARY
FA S H I O N A C C E S O R I E S
DESIGNER
BEAUTY
SPECIAL SIZES
SUITING
HANDBAGS
SWIM
D AY D R E S S E S
S W E AT E R S
ACTIVE
SOFT HOME
JEWELRY
I N T I M AT E S
KIDS HOME
HARD HOME
OUTERWEAR
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Common audience clusters in retail71 • Category-based audiences group customers based
on what types of products they tend to buy. People in
• Conversion-based audiences are perhaps the most one customer segment may tend to buy only shoes,
critical audience clusters. By analyzing at scale whereas those in another customer segment may
the conversions that took place over time against buy different types of active wear products, or kids’
the impression opportunities and ad exposures clothes, or jewelry.
leading up to incremental purchasers, retailers can
• Brand-based audiences tell you what brands
not only optimize to the business outcomes they
people are most likely to buy. This can be relevant
wish to achieve, but also learn about what variants
when marketing within a brand, but can also offer
are most influential across the customer journey—
broader insights into related brands that may
which leads to a discussion that moves beyond
resonate. These clusters begin to reveal what
broad segmentation and into predictive modeling.
brand loyalty looks like in the form of share of
• Life-stage, psychographic audiences and requirements or share of wallet. Similar customers
interactions group audiences based on interactive are often segmented based on heavy, medium,
triggers, or how shoppers behave while shopping. or light buyers. These groupings can inform more
Do they use the website or the call center? Are they sophisticated targeting strategies that provide
thrifty shoppers or big spenders? How frequently do insights about audience affinity.
they buy? How much do they spend? These smaller
triggers, in aggregate, may present information about
the life stage and mindset of a customer.
7
Levin, 2015
14
© 2017 Sizmek Inc. All rights reserved.Predictive marketing through analytics and an individual and as a unique engagement
modeling has huge potential for retailers, but to opportunity.
be effective, it must be intrinsically mapped to
What’s more, core insights from data
business and marketing objectives. According
clusters can help the retailers design an agile
to Dominique Levin, it’s imperative to directly
companywide framework that can improve
integrate the predictive analytics platform
operational efficiencies, drive more impactful
with marketing execution systems such as
ROI, and continue to deepen customer
marketing automation platforms, websites,
experiences in meaningful and
call centers, apps, POS systems, and advanced
measurable ways.
business intelligence tools.85Taking this a step
Predictive intelligence through digital
further means complete integration with
innovation is not only transforming the
data management systems and programmatic
way brands engage with audiences to drive
platforms. The key is to start with one integrated
purchases. It is also disrupting the way
and actionable model that can drive effective
retailers do business. One of the biggest
results while generating recommendations,
ways intelligent decision-making platforms
rather than experimenting with all explored
can inform how businesses strategize and
models without an actionable plan.
take action is by drastically improving
The newest predictive intelligence technologies
operational agility, both in terms of customer
allow retailers to scale insights and improve the
service and internal processes.
relevancy of recommendations that come out
of individual models, even for those consumers
who have had relatively little interaction with
the brand. Armed with predictive intelligence,
retailers can now look at each customer as
8
Levin, 2015
15
© 2017 Sizmek Inc. All rights reserved.Agile operations
Leveraging dynamic intelligence to become a predictive enterprise
To achieve peak operational agility, can help achieve efficiencies in brick-and-
businesses need systems that enable mortar stores as well. Across the board,
retailers to execute seamless data processes can be improved and automated,
integration, granular audience insight, and eliminating manual tasks, operations, and
real-time activation. From a user experience legacy systems that cannot keep up with
perspective, the right solution architecture the influx of brand channels, shortening
creates a business intelligence platform that attention spans, and increasing information.
can help maximize customer moments based Retailers can respond with nimbler solutions
on resonance and relevance. On the back that leverage business intelligence and
end, this same solution architecture can also customer data in broader ways.
help sustain long-term innovation and steady, However, one of the more significant
profitable growth for retailers. improvements that comes with digital
With this system in place, retailers can realize efficiency and operational agility lies in
a number of efficiencies—for example, in innovation. An intelligent digital platform
customer service. According to the Cisco enables businesses to test, learn, and tweak,
study, customers value efficiency, savings, and giving them the freedom to build initial proof of
engagement. Retailers have addressed digital concept solutions and improve them through
demand by creating more channels, but an rapid iteration. In other words, retailers
influx of channels doesn’t necessarily equate gain permission to try new concepts—and
to more value or a more cohesive, seamless fail—without significant consequence. With
path to purchase. To achieve a more long- this environment of constant, recursive
term effect that gives customers the things iteration, retailers can quickly optimize value
they value most, retailers need to be more for audiences and achieve significant returns
innovative and deliberate in their approach— when experiences or services gain traction
and operational efficiency is critical to making in market. Each of these promising solutions
that shift. can bring significant returns to retailers. And
each one starts with solid information through
Certainly, digital shopping platforms can
which behavioral proxies can be mapped to the
significantly offset operational costs and
individual user level.
create efficiencies. But digital innovations
16
© 2017 Sizmek Inc. All rights reserved.Leveraging untapped data to serve customer based on purchase history. Retailers
customers more efficiently can seamlessly integrate people, processes,
data, and experiences—to the benefit of the
With retailers, as with most businesses,
retailer and the shopper.
having “enough” data is not the issue. Most
organizations have mountains of valuable What a retailer should not expect is a
data—much more than they ever use. They perfectly linear process through the traditional
simply lack the ability to exploit it. This “dark marketing funnel. With customer journeys,
data” could potentially lead to insight, but it one size does not fit all. Retailers must
instead lies untapped. To derive insights from employ a holistic perspective that takes into
all data, dark and otherwise, you first need the account that most customer journeys are
means to capture it. nonlinear, with channels, options, and means
to reach audiences that are exponential. Once
Next-generation technologies such as
devices are connected—including the Internet
wearable computing devices, augmented
of Things (e.g., shelves, shopping carts,
reality, and connected home technology are
displays)—processes can become dynamic,
reaching a tipping point and stand to become
automated, and capable of driving competitive
significant for the retail industry. Consumers
advantage. But this kind of performance starts
are increasingly ready to adopt these
with building a central integrated business
technologies—including a more converged
intelligence and audience hub where retail
digital environment that leverages both
stores can harness, govern, and analyze data,
in-store and anytime shopping—to make
and syndicate decisions to increase business
shopping experiences more meaningful and
agility and begin to predict customer needs.
efficient. Again, these opportunities create
This hub serves as the foundation for the
a foundation for being a more data-driven
retail store of the future.
enterprise, but this capability needs to be
harnessed intelligently. This future store may be an amplified
showroom that helps audiences become
The contextually aware retailer can set and
smarter shoppers—a responsive environment
automate dynamic processes, while deploying
that enables micro-personalization at
resources accordingly to heighten consumer
scale. These stores will become emotional
emotions at pivotal moments of decision or
destinations that drive deeper interactions,
at other critical points along the shopping
where every store associate is a shopper
journey. For example, a store associate can
advocate. Technology will drive value and
receive an automatic prompt to lower a price
remove roadblocks to meeting customer
for a customer who tends to shop sales, or a
needs. This highly personalized sensory
platform can serve up a particularly compelling
environment will be powered with tools that
ad that is more likely to grab an individual
connect business processes with right-sized
customer experiences.
17
© 2017 Sizmek Inc. All rights reserved.Connected retail, big opportunity purchase paths and operational processes
that can be too complex for humans to
According to the Cisco (2015) study,
execute at the speed and scale required to
retailers believe it’s possible to fully
achieve optimal results. This is why real-time
automate up to 50 percent of their existing
data pass back and syndicated decisions are
manual operational processes. However,
critical for success.
many operational processes are embedded
in business applications such as enterprise In another example, online retailers gain
resource planning (ERP) systems. As a key insights from the rich data created by
result, retailers lack true visibility into their the “clickstream” as consumers browse,
operational environments. research, and purchase products online,
registering their likes, dislikes, and interests.
In retail organizations, future value will come
Online retailers then use this data to gain
from real-time analysis and activation of data
a better understanding of each shopper’s
from connected sources—many of which
journey. Retailers can now, in effect, bring
were previously unconnected. POS systems,
this clickstream into the physical world and
tracking devices using barcodes or RFID tags,
gain real-time insight into constantly evolving
and GPS-enabled fleet logistics will talk to a
micro-segments within their customer base.
new generation of data sources, such as shelf-
edge labels, equipment and device sensors, Incremental lift models can then be created
smart digital signage, and beacons. And all of to drive penetration and purchase frequency.
these will communicate bidirectionally with the These models, based on third-party attribution
enterprise-at-large. reports, inform brands and retailers how to
tactically buy impressions via programmatic
Forward-thinking retailers understand the
exchanges. Ideally, campaigns should use
need for having predictive and programmatic
product-specific attributes (PSAs) and ad
systems that can automate decisions in real
campaign impressions, creating test and
time. Analytics are too often constrained by a
control groups within a sampling engine. Using
nightly batch-processing model for store data.
the attribution reports, advertisers can develop
For instance, with a traditional data warehouse
an uplift curve and incremental purchase
model, it might take days or weeks to transmit
projections, which can then be mapped to
all the data back to a central repository, sort
incremental offline sales. The goal for evolution
out what is relevant, and extract insights that
would ultimately be to assess offline sales and
improve operations or customer interactions.
all the attributes and variant combinations that
By that time, of course, the customer has left
drive lift.
the store, and the opportunity to add value is
gone. Digital platforms propelled by machine
learning and artificial intelligence automate
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© 2017 Sizmek Inc. All rights reserved.Customer insight informs the to examine interactions between associates
store of the future and customers, category-level conversion,
dwell times, customer traffic heat maps, and
Customer data is a powerful asset for
paths to purchase. This information, combined
today’s retailer, made even more powerful
with existing transactional and other data, is
by device and channel connectivity. With the
allowing management to answer questions
advent of data collection and analysis, we’ve
that go far beyond store operations alone—
been able to measure what types of brand
things like conversion by product category.
messages influence lift in purchases. But now
These insights will help management shape the
data, in communication with other systems
complete customer journey, not just in stores
including the IoT, can tell us in real time and
but online as well.
with increasing accuracy how to develop an
optimal store configuration, where to place As online and in-store experiences converge,
products on shelves, and what future store all data taken in aggregate, from the one-click
locations and investments will achieve the purchase to in-store browsing patterns, can
greatest returns for the company. help trigger the right real-time decisions to
help increase value and performance across
But the considerable worth of data doesn’t
all channels. Decisions and data in physical
lie only in customer service—it’s also a
locations should inform data and decisions in
precious commodity in business operations.
digital e-commerce platforms, and vice versa.
In-store data can influence staff optimization,
The power lies in combining this intelligence to
planogram compliance, and loss prevention,
create a unified view of the customer.
among other operational concerns. How
many employees will a location need on Black Behind the scenes: Implementing the
Friday if the weather is clear, as opposed to if connected supply chain
it’s snowing? What’s going to be the hottest
Connected devices and products provide
product this year? What are the most logical
retailers with the opportunity to help
product bundles to help move merchandise
optimize operations in the face of a more
more quickly? What’s the optimal store traffic
complex supply chain, increasingly important
flow to prevent long lines and altercations?
digital channels, and a more demanding
How do you more effectively prevent theft
customer. RFID technologies can improve
with heightened crowds and chaos? Customer
the precision of inventory tracking. Data
data, store performance data, and even
visualization technologies make it easier for
external data such as weather and construction
employees to gauge inventory performance
reports can help retailers predict the answers
across the supply chain. Data visualization
to these questions more accurately than ever.
also applies to customers, allowing them to
One large office supply company deployed track any order through the production and
sensors and cameras throughout the store distribution process.
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© 2017 Sizmek Inc. All rights reserved.Optimizing supply chains offers significant transparency with customers, who increasingly
potential to generate greater value in want to know where their food comes from.
retail, whether through leveraging scale in Barilla piloted track-and-trace technology on
negotiating with suppliers, improving efficiency a limited number of its pastas and sauces. By
and productivity in warehouses, reducing the scanning a QR code on the package for these
need for stock checks, automating resupply, or products, consumers can now see information
improving collaboration and communication on everything from where the ingredients
with suppliers. for that particular batch were grown to a
detailed view of the item’s journey through
For example, when one large retailer
the production process. The new tracking
overhauled warehouse operations, improving
process provided significant marketing value
efficiency and safety was a high priority. In the
and added increased compliance and quality
previous warehouse layout, the poor timing
control capabilities, because the ability to trace
of key deliveries and lack of communication
foods through the whole chain of production
among staff created major bottlenecks—and a
is critical to meeting increasingly strict
high risk of workplace accidents.
international standards on food safety, quality,
First, management used Wi-Fi data to track
and origin.
handheld scanners and forklift trucks in the
According to Accenture, the “Industrial
warehouse, which enabled managers to see
Internet” describes how companies are
exactly where and when the bottlenecks
leveraging cloud, mobile, big data, and
and safety hazards occurred. Then the
other technologies to improve operational
company optimized traffic routes through
efficiencies, foster innovation, and more tightly
the warehouse, specifying exactly where
integrate the digital and physical aspects of
drivers should go—and in which direction—as
their businesses.91The combination of the
they picked items for an order. Workers no
Industrial Internet and IoT devices could
longer had to spend time making decisions on
add more than $14 trillion USD to the global
where to go, and in what sequence, to fulfill a
economy by 2030.102
given order. After implementing this system,
the company saw a substantial increase in These technologies hold much future promise.
the number of orders filled per shift and Retailers could potentially use web-enabled
a reduction in the risk of collisions on the smart tags to raise or lower pricing in real time,
warehouse floor. depending on product supply and demand.
Kroger is now testing smart-shelf technology
In another example, Italian pasta producer
in its grocery stores, where shelves display
Barilla needed to improve visibility across its
dynamic digital price tags and, soon, sync with a
entire production chain, from field to finished
shopper’s mobile application to help them find
product. This higher visibility would not only
items on shelves or remind customers about
improve food safety, but would increase
add-on purchases, such as baby wipes when
9
“Industrial internet insights report,” Accenture, 2015
10
Accenture, 2015
20
© 2017 Sizmek Inc. All rights reserved.buying diapers. Digital tags already help store information on products than ever before,
employees more efficiently tag and price items, increasing satisfaction and reducing the
freeing them up to spend more time interacting number of returned purchases. Territorial
with customers. coverage evolution will enhance digital
Other IoT devices can be integrated within channels, enable intelligent remote advice,
the supply chain to further improve store and migrate transactional activity to the
operations and help reduce cost. IoT-enabled channels that will maximize purchases. As
sensors can monitor lighting and temperature a result, products become more widely
controls and adjust settings to improve available to customers in those respective
customer comfort and support more cost- channels. This next wave of platforms will
effective energy usage. also support alternative means for payment
and transactions, increasing convenience.
Agile, predictive, and personalized marketing
Retailers will be able to assess customers
The interactions that flow across the retailer across all channels to define very targeted
ecosystem are owned data for the enterprise, moments in which customers will be
and the number of these interactions keeps responsive. As this capability accelerates,
growing. Insights come from the patterns that retailers will be able to forecast demand more
emerge from these first-party touchpoints, accurately with advanced analytics, creating
which increasingly help retailers blend niche experiences for micro-segments with
physical and digital experiences to deepen as many messages as there are individual
engagement while driving efficiencies. personas. Brands that can offer a modular,
features-driven, just-for-me customer product,
Retailers that can optimize their physical
while at the same time practicing minimum
footprint while boosting sales effectiveness
viable distribution methodologies that reflect
can also optimize operating costs, drive
agile product development processes, will lead
commercial performance improvement, and
the market, winning the hearts, minds, and
deliver higher quality service. As patterns
wallets of a new group of cherished loyalists.
emerge from data that help personalize
experiences at the user level, retailers will
also begin to differentiate shop formats
and new discrete service models, moving
away from a one-size-fits-all approach for
marketing. Data streams that move across
devices and channels will enable right-
sizing of customers while providing better
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