Through precise location analytics, retailers now can monitor the entire path to purchase. With this data, marketers better understand what led to the purchase providing the ability to move beyond the traditional blanketed “campaign” to a year-round interaction based on consumer behavior. Customers “opt-in” by mobile app to receive highly-targeted promotions, information about merchandise they may have “visited” but didn’t purchase, and discounts for major events – based on correlations like visits, dwell and intent – to drive sales like never before.

1. SOLUTIONSGUIDE
technology
SmarterInsights,SmarterStrategies
There is little doubt that customer analytics, along with the volumes of data that
drive it, is empowering retailers with new insights and smarter strategies. Ben-
efits are derived by enabling retailers to become more predictive and personal-
ized in the way they interact with shoppers and merchandise products. Shoppers
get a return for being included in the data and retailers get a return by being
better able to manage inventory across physical stores and digital channels.
But with that power comes a host of challenges: respecting consumer’s privacy
and safeguarding their data; ensuring data accuracy and integration; managing
and making sense of the deluge of new data points; and entrusting the data to
cloud-based vendors or other third-party providers. Nonetheless, many retailers
are now rushing to see how they can best exploit the growing mountain of data
and become truly analytics-based enterprises. Properly aggregated, the data can
be processed and answers can be drawn from multi-dimensional queries that
can segment customers and help deliver highly personalized messaging and mer-
chandising programs.
Q
What are best-prac-
tice techniques for
segmenting custom-
ers and then market-
ing to those segments?
Kellie Peterson: There are many shop-
per segments, but retail traffic analytics, for
the first time allows us to segment custom-
ers by their in-store behavior, and most
importantly, by their intent. Both passive
(anonymous) and active (mobile app) lo-
cation tools provide insights into shopper
behavior and influence how marketing
programs are designed to address shoppers
by in-store behavior groups. We can seg-
ment shopper paths for example, and ex-
pertly employ contiguous marketing tech-
niques to group products based on where
that shopper is likely to go. Retailers can
identify specific traffic segments such as
repeat visitors, employees, cross-store shop-
pers or shopper groups who don’t make a
purchase. For non-converting shoppers, we
can identify where and when this is likely
to occur – and install resources to increase
conversion. iInside’s passive technology is
anonymous so no personal data is collected
or accessible without consumer consent.
Bruce Armstrong: At a recent mar-
keting conference Gary King, former EVP
and CIO at Chico’s, led a great discussion
about marketing to customer segments
with Kaitlin Moughty from Freshpair.
com, Rob Bowers from Total Hockey, Peter
Leech (The Partnering Group and former
CMO of OnlineShoes.com) and Shelley
Nandkeolyar (The Ivory Company and
Board Member Emeritus of Shop.org).
Bruce Armstrong
President & CEO
PivotLInk
Kellie Peterson
Director of Marketing
iInside
PRODUCEDBY
SPONSOREDBY
marketing intelligence

2. Their conversation highlighted the evolu-
tion we see taking place as retailers prog-
ress through five stages of marketing matu-
rity. They underscored the importance of
centralizing customer data from internal
systems and third party data sources –
something we do so marketers or their IT
teams no longer have to do it themselves.
Once customer data is unified, retailers can
explore who their customers are and what
they do, and apply advanced customer
analytics to pinpoint the likelihood they’ll
take the next action and which marketing
activities and channels have the greatest
impact on revenues.
Q
:Are today’s custom-
er analytics tools
enabling marketers
to work smarter
and if so how?
Peterson: By an order of magnitude!
Customer location analytics is one of the
biggest changes in retail in the past 100
years. Online shopping experiences have
taught retailers the rich value of detailed
purchase path data, and now it is available
for in-store behavior – for the first time.
With location analytics, a retailer can mon-
itor shopping path and behavior through
every department, aisle and fixture. The
better we know our customer behaviors,
the better we can target-market and mer-
chandise to meet and exceed our goals.
With location analytics, retail leaders look
at traffic reactions to merchandising, mar-
keting and operational efforts. They look
at how they are measured in total traffic,
conversion, most trafficked, first visit, re-
peat visits, cross-store visits and loyalty, and
this goes right down to the departmental,
brand or fixture level.
Armstrong: Social mobile consumers
are very disruptive. When a consumer can
walk into a store, take a picture of an item,
walk outside and buy it on Amazon, eBay
or a competitor’s site it puts a huge amount
of revenue at risk. Customer analytics from
companies like ours helps retailers defend
against this existential threat. Today’s mar-
keters need an analytic application suite,
not a tool. We do all the integration – both
your data and external data – and inject
domain expertise and business process so
marketers can answer key questions, like:
“Who should I be selling to?” “When
should I time my next promotion?” “What
should the offer be and what are the right
channels for this sub-segment of custom-
ers?” Marketers can now pinpoint how to
increase marketing ROI without worrying
about integrating and analyzing the data
themselves.
Q
Are marketing cam-
paigns one-off events
or is there a way to
develop a customer
lifecycle approach?
Peterson: Through precise location an-
alytics, retailers now can monitor the entire
path to purchase – from consumers using
smartphones to comparatively shop or ac-
cess a coupon/promotion, to the way they
interact with merchandise in a brick-and-
mortar location. With this actionable data,
marketers better understand the specifics
of what led to the purchase providing the
ability to move beyond the traditional blan-
keted “campaign” to a year-round interac-
tion based on consumer behavior. Custom-
ers “opt-in” by downloading a mobile app,
and the retailer can push highly-targeted
promotions, send information about up-
coming sales on merchandise they may
have “visited” but didn’t purchase, and of-
fer discounts for major events– based on
correlations like visits, dwell and intent – to
drive sales like never before.
Armstrong: Campaign lifecycles are
getting shorter and shorter. There used
to be a season to campaigns – there was
a plan, a budget and then reports on a
monthly or a weekly basis. Now, in the
holiday season, there are daily and intra-
day campaign lifecycles. This is the perfect
storm that retail marketers, and really any
B2C marketers, face today. This is the en-
vironment where customer analytics from
companies like ours provide value.
Q
The goal of retailer
investments in cus-
tomer analytics is to
increase marketer
intelligence. How can this
best be accomplished?
Peterson: E-commerce taught retailers
the incredible value of observing the on-
line purchase path. Armed with this data,
e-commerce divisions constantly modify
the online experience to improve shopping
performance at every step in the process.
The yield and conversion process is incred-
ibly effective. Now retailers are applying
these location analytics and traffic data
lessons in the store to gain powerful shop-
per behavior insights and translate them
into performance improvement just as it is
done online. By implementing an innova-
tive, low-cost, easily integrated platform
that delivers this rich data from every me-
ter in the store, marketers are armed with
the business intelligence needed to make
informed decisions and ensure a rapid in-
crease in key performance indicators.
Armstrong: B2C marketers face a lot of
data challenges, from new marketing chan-
nels to evolving demographics, including
younger buyers who are comfortable with
technology and expect an omnichannel
experience. Traditionally, retail marketers
either outsourced the problem of under-
standing customer interactions to agencies,
consultants or third party database provid-
ers to tell them what they should be think-
ing about relative to their customer base,
or they tried to make sense of data from
disparate marketing execution systems.
With the evolution that’s taken place in
the cloud-based infrastructure and analytic
applications, we’ve been able to pull all of
this together to help marketers excel at
their jobs. RIS
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3. COMPANY NAME/ WEBSITE RELEVANT PRODUCT/SOLUTION KEY CLIENTS
1010 Data
www.1010data.com
Market Basket Analysis, Loyalty Card Analysis,
Inventory Optimization, Out of Stock Analysis
Dollar General, Rite Aid, Vitamin Shoppe
Aerohive
www.aerohive.com
Retail Analytics 7-Eleven, Drakes Supermarkets
IBM
www.ibm.com
Smarter Analytics Barnes & Noble, Dillard’s OfficeMax
iInside
www.iinside.com
Business Intelligence, Mobile Applications,
Increased Basket Size, Clienteling
NA
Lighthaus Logic
www.lighthausvci.com
Visual Customer Intelligence (VCI) System Champs Sports, Foot Locker
Manthan Systems
www.manthansystems.com
ARC Merchandise Analytics, ARC Customer Analytics,
ARC eCommerce Analytics, ARC Store Operations,
ARC Human Resource Analytics
Canadian Tire, Crocs
MicroStrategy
www.microstrategy.com
Intelligence, Express, Cloud Guess?, Limited Brands, Lowe’s
Oracle
www.oracle.com Customer Analytics, Merchandising Analytics
Burlington Coat Factory,
Deckers Outdoor, Finish Line
PivotLink
www.pivotlink.com RetailMETRIX, DataCLOUD, AnalyticsCLOUD Carhart, Party City, REI
Predictix
www.predictix.com Forecasting, Planning, Pricing & Promotions Crate & Barrel, dELiA*s, Rent-A-Center
QuantiSense
www.quantisense.com
Decision Orchestration Platform, Q Merchandising,
Q Direct, Q Mobile
Reitmans, Urban Outfitters, Pac Sun
RetailNext
www.retailnext.com
People Counting, Marketing & Merchandising Cache, Gander Mountain, Gordmans
SAP
www.sap.com
Business Objects, Lumira, Crystal Reports,
Predictive Analysis
Ace Hardware, eBay, Chico’s FAS
SAS
www.sas.com
Demand Forecasting, Intelligent Clustering,
Revenue Optimization Suite, Size Optimization
Autozone, Brooks Brothers, Macy’s
Teradata
www.teradata.com
Big Data Analytics, Business Intelligence,
Demand Planning
Charming Shoppers, Hallmark,
Metro Group
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CUSTOMERANALYTICS