Customer Traffic Provides Keys to Conversion Analytics

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2013
Analytics Insights Deliver Competitive Differentiation 1
Mastering analytics has become vitally important for retail-
ers’ ability to differentiate themselves from their competi-
tors. It’s always been critical for retailers to be able to iden-
tify who their most valuable customers are, but today they
need predictive analytics solutions that provide insights
into the specific engagement tactics that will keep these
valuable customers loyal in the long term. Today’s sophis-
ticated analytics also give retail organizations the tools to
handle omnichannel operational challenges, identifying the
optimal location from which to fulfill an order to maximize
both efficiency and profitability. As analytics solutions tap
into newer data sources, such as social media and location-
based information, they will help retailers not only identify
new trends but predict which ones will have a lasting impact
versus those that will simply flash and fade. By providing
insights into all aspects of an increasingly complex purchas-
ing process, analytics solutions let retailers stay in step with
– and even move ahead of – today’s empowered consumer.
Charting the Path That Links Technology and Business Goals
JULY
2013
SPONSORED BY
Analytics Insights Deliver
Competitive Differentiation
R O A D M A P

2. R O A D M A P
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2013
Analytics Insights Deliver Competitive Differentiation 2
“K
nowledge is power,” according to the old
adage. Retailers today would amend this
maxim to read “Knowledge is profitability.”
And the tools to gain that knowledge, and the profits
that accompany it, are business analytics solutions.
These are the simple truths behind an increasingly
complex set of challenges for individual retailers, and
for the industry as a whole, in the business analytics
arena. One impossible-to-ignore factor is that there is
so much more data available to gather, digest and an-
alyze. The Citi Research 2013 Retail Technology Deep
Dive quotes estimates that 2.5 quintillion bytes of data
are created daily: “Such an increase means that 90%
of the data in the world today has been created in the
last two years. The majority of new data is unstruc-
tured, Web-based, and outside the company. 70% of
unstructured data is stale after only 90 days.”
For retailers specifically, technological changes in
the way customers shop have opened up vast new
opportunities for gathering data. The rise of online
and mobile commerce provided retailers with the abil-
ity to trace every click, view, screen swipe and query
on the road to a customer’s purchase decision. Brick-
and-mortar stores had been lagging their digital coun-
terparts, but recent solutions that anonymously track
signals from shoppers’ mobile devices, along with
increasingly sophisticated video analytics, are rais-
ing in-store specificity levels about who shoppers are,
what they’re looking for, and how they arrive at a buy/
don’t buy decision.
And let’s not forget that data gathering, no matter
how granular or sophisticated, is just one element in re-
tailers’ ability to use business analytics effectively. They
are anxious to use data for solutions such as predictive
analytics – potentially the most valuable type of analyt-
ics because they can guide key decisions about market-
Source: Citi Research 2013 Retail
Technology Deep Dive
of the data in the world
today has been created
in the last two years. The
majority of new data is
unstructured, Web-based,
and outside the company.
90%

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Analytics Insights Deliver Competitive Differentiation 3
ing, merchandising, supply chain, direct commerce and
store operations, including workforce scheduling.
In fact, predictive analytics was selected by 42.5% of
retailers as a “Top 10” technology for 2013, tying for
third place with mobile POS in the RIS/Gartner 2013
Retail Technology Study. (Campaign analysis and fore-
casting, another key analytics area, was first at 50%.)
Yet only 10% of respondents currently have up-to-date
predictive analytics solutions in place, although 18%
have begun an upgrade in this area and 25% are plan-
ning to do so within the next 12 months.
Nor is this the only analytics area where retailers are
moving quickly to keep up in the knowledge race. On-
line retailers are bolstering their staffs in the area of
marketing analytics, another key focus area. According
to a recent Forrester Research/Shop.org study, 40% of
these retailers plan to hire for open positions in market-
ing analytics in 2013, reflecting their desire to wrestle
down volumes of marketing data to create more effec-
tive interactions and an improved customer experience.
Following are five mileposts retailers will need to
reach on the road to making effective use of business
analytics in a complex, data-drenched environment:
Advance from Business Intelligence
to Business Analytics
Business intelligence (BI) and business analytics
are often used interchangeably, and even within the
strictest definitions there is some overlap between
them. According to EKN, BI refers to tools and soft-
ware focused on retrieving, analyzing and reporting
data stored in an existing enterprise database, with
tools typically focused on querying, reporting, Online
Analytics Processing (OLAP) and alerts. In general, BI
is concerned with understanding what has happened
in the past, and delivering that information via regular
reports and/or structured queries.
of retailers identified
predictive analytics
as a Top 10 technology
for 2013, but only
10%have up-to-date
solutions in place.
Source: RIS/Gartner 2013
Tech Trends Study
42.5%42.5%

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Analytics Insights Deliver Competitive Differentiation 5
Business analytics consists of a broader set of tools
and solution sets, which can be used for functions
such as playing out “what-if” scenarios that can pre-
test and predict the impact of specific actions. Busi-
ness analytics can also provide the ability to detect
previously undiscovered patterns within data, for ex-
ample identifying areas where costs or manpower are
higher than the norm, or where sales/margins are low-
er. Such discoveries can point retailers to issues that
need attention or uncover new opportunities they had
been unaware of.
The EKN State of the Industry 2013 Future of Re-
tail Analytics report defines Business Analytics as
the “art, science and philosophy of utilizing insights
to improve decision-making in the context of a par-
ticular business function or process. It is focused on
a continuous, ongoing, and iterative exploration of
past business or business process performance to
gain insight, drive business planning, and deliver a
particular business outcome.”
The difference is more than just technical and se-
mantic. EKN identifies the ways today’s leading re-
tailers, including Best Buy, CVS, Amazon, Target and
Walmart, are leveraging analytics to:
• Gain a deeper understanding of their customers’
behaviors, needs and preferences to build a more
personal relationship
• Improve marketing effectiveness through micro-
targeting, personalization and delivery of context
and channel sensitive promotions and offers that
increase the likelihood of purchase
• Optimize the supply chain to ensure the most
profitable outcome in terms of demand fulfillment
balanced against cost of carrying excess inventory
• Determine pricing, including bundle and basket
pricing, based on the value customers attach to their
needs at any given time
The rise of online
and mobile commerce
provided retailers with
the ability to trace every
click, view, screen swipe
and query on the road
to a customer’s
purchase decision.

5. I N D U S T R Y I N S I G H T S
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eium rehendusaes dicae rero mi, te plaboris abo. Catem et qui omnis doluptium
qui dipictur renda solorit ad ulpa
iInside, a WirelessWERX company,
is a market-leading provider of
highly detailed indoor shopper
analytics and insights to brick-and-
mortar retailers and high-traffic
venues. Through patented, low-
cost and easy-to-install technolo-
gies, the company offers privacy-
compliant statistical data and
solutions that aggregate consumer
traffic behavior in order to help cli-
ents increase revenue and improve
operational efficiency. With more
than 24 global patents and over
30 years of unrivaled expertise,
iInside is the best-in-class choice
for consumer analytics and indoor
positioning solutions.
Q: What do in-store customer traffic solutions add to retailers’ analytics efforts?
JON ROSEN: The ability to add traffic data to other performance measures addresses
a very retail-specific challenge and opportunity. Precise retail traffic data paints a path-
to-purchase picture previously unavailable to the retailer. Retailers now can learn exact-
ly where people go in their stores, for how long and in what order. That data translates
into the ability to manage the business: Operations, Merchandising and Marketing, in
order to increase shopper time, increase visit frequency, sequentially-merchandise and
decrease wait times at the registers. The effect of any action, from store layout changes
to promotions, can be measured in traffic and at the register. Advanced solutions also
include location-enabling mobile applications to communicate with shoppers in the
store, based on location. We can also now connect online and offline purchase behavior.
It’s a true sea-change in retail data resources, and as we grow, we’re focused on aggre-
gated data and other privacy protections.
Q: What kinds of questions does this allow a retailer to get answers to?
ROSEN: There are at least two segments of unique, valuable data: performance re-
porting and cause-and-effect. With performance reports, retailers can measure each de-
partment’s performance across several factors including conversion, draw, dwell-time,
repeat visits and more. Various individuals from store GMs to merchandisers and others
can drill down across the chain to evaluate performance by store and by department. As
a result, resources to increase departmental conversion and other performance metrics
have never been more powerful.
Q: How can retailers make the best use of this data?
ROSEN: Retailers will want to look at which departments are doing better than oth-
ers using key measures like conversion. Let’s take two different stores with TV depart-
ments that have similar revenues. But with traffic data we learn that the TV department
at store 61 converts at 4%, while store 62 converts at 9%. Armed with that data we are
now aware of the need to find reasons for sub-optimal conversion and resolve them.
Are the departments merchandised the same way? Is one location better within the
store? Is the employee training better in one store versus another? The store manager
can see how well they’re performing, by department, against regional and national
averages, and these better performers can influence the retailer on what constitutes
best practices.
For staffing, because traffic solutions measure how many and how long shoppers
are in each department, they can help establish correlations between staffing levels and
their impact on merchandising and marketing. Are shoppers in the store for 15 minutes,
or for an hour? That’s a big staffing question, especially in a store where associates are
assigned to a particular department.
A retailer dealing with showrooming might discover exactly which departments
were being “showroomed,” i.e. where people were visiting but not buying and at which
times throughout the day or week. Perhaps shoppers weren’t just looking for a lower
price. Perhaps they couldn’t make a choice of product, or maybe there was no one avail-
able to help. If traffic data tells us where and when the behavior is occurring we have
another key resource to increase sales and enhance the customer experience.
“Precise retail traffic
data paints a path-
to-purchase picture
previously unavailable
to the retailer. Retail-
ers now can learn
exactly where people
go in their stores, for
how long and in what
order.”
Jon Rosen, Executive
Vice President, iInside,
a WirelessWERX company
Customer Traffic Provides
Keys to Conversion Analytics

6. R O A D M A P
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2013
Analytics Insights Deliver Competitive Differentiation 7
• Spot flash trends, such as a celebrity sighting in
a particular pair of jeans, that have an impact on
demand to be able to turn them into revenue
capturing opportunities.
This is a list that any retailer, large or small, would
rate as highly valuable.
Gain Insight by Mixing Data
from Multiple Domains
Analytics solutions, and the insights they produce,
have often focused on the needs of an individual de-
partment. This data “silo-ization” has often been an
There’s a major
mismatch between how
retailers believe their
analytics resources
should be structured
versus the current
organizational reality.
Shared services
format for analytics
Each department
responsible for
own analytics
resources
IT primarily
responsible for
analytics
Currently structured
Should be structured
Source: EKN 2013 State of the Industry Research: The Future of Retail Analytics
Organizational Structure
of Retailer Analytics Resources
71%
18%
58%
53%5%
5%

7. JUly
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Requirements for
Business Analytics
Strategy
• Mission: Leverage Business Analytics insights to help accomplish
key business goals (e.g. growth, customer engagement, profitability)
• Move from Business Intelligence focus on rear-view analysis to
forward-looking, ‘what-if?’ predictive analytics
• Gain 360-degree view of customer activity across all channels/
touchpoints
• Optimize delivery of insights to the time when their consumption
will be most valuable
Technology
• Deploy solutions to monitor social media and identify emerging
networks relevant to customer base
• Use location-based technology to improve understanding of in-
store customer purchase journeys
• Establish consistent internal data model
• Invest in Big Data tools to handle accelerating growth of data set
sizes
• Deploy contextual, visual, mobile-friendly vehicles for delivering
analytics insights to front-line associates
Process
• Establish C-level or senior VP-level executive in charge of analytics
• Move from a department-based or IT-centric analytics organization
to a shared services model
• Invest in specialist skill sets such as statisticians, actuaries, data
scientists and economists
• Decrease time from data acquisition to analysis and insight pro-
duction
• Incorporate available third-party or government data to enrich
analytics insights
• Use A/B testing to constantly measure impact of actions
• Compare test results among various customer segments to assess
variances
Requirements
Every major business initiative requires a detailed assessment that examines the proj-
ect’s impact on internal processes, technologies, personnel, strategic alignment and
costs. One goal of the assessment is to identify granular and high-level requirements
that are essential elements in the project’s game plan. Managing and addressing these
requirements is critical to success.

8. Analytics Insights Deliver Competitive Differentiation 10
40%
issue in retail, with different departments unable to
speak the same language in terms of data, resulting
in different descriptions of products or definitions of
what its price actually is.
In some ways, the spread of new analytics technol-
ogy has made the problem worse. “Even recently,
marketing’s adoption of Web and social media analyt-
ics was initially driven more from a channel perfor-
mance measurement and improvement perspective,
rather than a need to understand consumer behavior
and preferences better,” writes EKN Research Director
Gaurav Pant in the Future of Retail Analytics report.
Retailers are moving aggressively to make greater
use of social media data: EKN projects that retailer in-
tegration of social data will go from 30% in 2013 to ap-
proximately 90% in 2015; mobile data will see a similar
growth in integration, albeit from an even smaller base.
The demands of omnichannel retail and the custom-
er-centric nature of these kinds of social media data
are creating new opportunities for retailers to gain in-
sights that will benefit multiple departments and func-
tions. “New insight can be drawn by mashing up data
across domains,” writes Greg Girard in the IDC Retail
Insights September 2012 report titled Big Data and An-
alytics in Retail: Unlocking Hidden Opportunities. “For
example, contextual analysis of contact center call
logs, tweets, ratings and reviews, lot tracking of ship-
ment records, product design information, and loyalty
data taken together could spot product defects from
customer feedback, identify root causes from product
design information, identify stores holding any defec-
tive merchandise, and find loyal customers who pur-
chased the item.”
Address Organizational Structure
of Analytics Resources
This type of productive mixing of data and ana-
lytics insights doesn’t occur without organizational
R O A D M A P
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2013
Retailer integration
of social data will go
from 30% in 2013 to
approximately 90%
in 2015
Source: EKN 2013 State of the
Industry Research: The Future
of Retail Analytics
30%
50%
60%
70%
80%
90%
2013
2015

9. Analytics Insights Deliver Competitive Differentiation 11
R O A D M A P
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2013
change within the retail enterprise. Current depart-
mental structures tend to discourage sharing: 71% of
retailers surveyed by EKN have individual departments
responsible for their own analytics, and just over half
(53%) primarily rely on IT for analytics support. How-
ever, only 5% of respondents say these structures are
their desired/optimal state.
In contrast, 18% of respondents use a shared ser-
vices format for analytics, but 58% say this is the way
their organization should be structured.
Align Delivery of Analytics
Insights to User Needs
Another of the enormous challenges in this area
involves getting the insights that analytics solutions
produce to those who can make the best use of them.
The classic example would be a predictive analytics
solution identifying the customer a sales associate is
currently helping as someone who is highly likely to
purchase a second pair of shoes if she is offered even
a small percentage discount. Getting that crucial piece
of “intel” to the salesperson in time to affect the out-
come of their interaction, however, requires high lev-
els of coordination among various systems, databases
and communication devices.
In these and other time-sensitive situations, deliver-
ing the equivalent of a spreadsheet with the relevant
data buried somewhere in it will make the entire ef-
fort an exercise in frustration. That’s why EKN predicts
that retailers “will invest in contextual, visual and mo-
bile-friendly delivery of insights to combat the biggest
challenge that prevents them from leveraging analyt-
ics strategically – delivery of insights to the right re-
source at the right time.”
Even as they explore the new frontiers of analytics,
retailers can’t afford to lose sight of the basics. “Half
In time-sensitive
situations, delivering
the equivalent
of a spreadsheet
with the relevant data
buried somewhere
in it makes the entire
effort an exercise
in frustration.

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Analytics Insights Deliver Competitive Differentiation 12
the time, retailers are better off when they know ex-
actly which problems they’re trying to solve, because
it helps them focus on the right questions to ask,” ac-
cording to Nikki Baird and Steve Rowen, writing in the
October 2012 RSR Research report titled Retail Busi-
ness Intelligence: A Work in Progress. “Retailers need
to stay focused on the ‘small bites’ – on the common
problems that need to be solved, and on how they can
pre-analyze to get end users, particularly front line end
users, as close to the action needed as possible.”
Apply Analytics Insights
Across Channels
The value of analytics-produced insights can be
multiplied when they are applied across a retailer’s
sales channels. Retailers capable of connecting shop-
pers’ online activities, i.e. when they are researching a
potential purchase, to their store visit, are much more
likely to be able to complete the sale when they arm
store associates with this knowledge.
In some cases the insights move from the store to
the digital channel. Brooks Brothers sought to repli-
cate online the complex process of building a dress
shirt, which generally takes place in the store with the
assistance of a sales associate. Multiple parameters
include picking one of four fit types as well as differ-
ent color and fabric choices. The retailer used testing
to communicate to the customer “at the right time and
using the right message,” according to Brooks Broth-
ers’ director of analytics Cindy Lincks.
She added that the retailer’s testing involved look-
ing at the responses of new versus existing custom-
ers, and noting that “we didn’t expect them to re-
spond the way they did. A lot of what we do involves
slicing and dicing customer segments, because it’s
not just about what appeals to the masses but what
appeals to the individual customer’s needs as they go
through your site.”
Best
Practice
When Brooks
Brothers sought
to replicate the
detailed in-store
process of building
a dress shirt online,
it used customer
segmentation data
comparing new
and existing
customers to test
and refine
processes and
communications

11. Analytics Insights Deliver Competitive Differentiation 13
ConclusionForward-thinking retailers realize how vitally impor-
tant analytics are to their ability to differentiate them-
selves. For example, it’s always been critical for retail-
ers to identify who their most valuable customers are,
but predictive analytics gives retailers insights into
what products, promotions and engagement vehicles
are most likely to keep these valuable customers loyal
in the long term. Analytics also offers retailers guid-
ance about increasing share of wallet, building mid-
value shoppers into high-value ones.
Sophisticated analytics can also help create an or-
ganization capable of handling the challenges of om-
nichannel retailing. For example, as fulfillment be-
comes more complex and spreads to the store level,
cost analysis can inform business rules that tell the re-
tailer the optimal location from which to fulfill an
order so as to maximize both efficiency and
profitability. Analytics can also help retail-
ers determine optimal pricing based on
the value customers place on the prod-
uct they’re buying at any given time.
Analytics solutions that can tap into
newer data sources, such as the wealth of
social media data and location-based infor-
mation from tracking of mobile devices, give
retailers powerful tools to identify new trends –
and also to test which of these trends will have real
staying power versus those that flash and then fade.
In addition, retailers can use analytics solutions to
answer questions affecting their long-term success,
such as which new geographic markets they should
expand into because they will be the best “fit” for the
retailer’s brand.
By providing insights into all aspects of an increas-
ingly complex purchasing process, analytics solutions
let retailers stay in step with – and even move ahead
of – today’s empowered consumer. •
R O A D M A P
JULY
2013

12. Charting the Path that Links Technology and Business GoalsR O A D M A P
JULy
2013
Business Analytics Mileposts
• Advance from Business Intelligence to Business Analytics
• Gain insight by mixing data from multiple domains
• Address organizational structure of analytics resources
• Align delivery of analytics insights to user needs
• Apply analytics insights across channels
Roadmap KPIs Infographic
90%
of the data
in the world today
has been created
in the last two years
Source: Citi Research, January 2013 Source: RIS/Gartner 2013 Tech Trends Study
Only
of retailers have up-to-
date predictive analytics
solutions in place.
Retailer integration
of social data will rise
from 30% in 2013
to 90% by 2015
90%
“In time-sensitive situations, deliver-
ing the equivalent of a spreadsheet
with the relevant data buried some-
where in it makes the entire effort an
exercise in frustration.”
Source: EKN 2013 Future of Retail Analytics
retailers use a shared services
format for analytics, but nearly
60%believe this is the way
their organization
should be structured
>1in5
Source: EKN 2013 Future of Retail Analytics