Unlock new Business Potential in the Offline World Through Wi-Fi & Bluetooth Location Analytics

Unlocking the Business
Potential of the Offline World
Through Wi-Fi & Bluetooth
Location Analytics
A Practical Guide for Brick-and-Mortar Companies
Jan, 2018
BLUE UNICORN

Table of Contents
Overview 4
Foundational Phase: “Table Stakes” for any offline business 5
Formalized Phase: Know the entire offline environment 9
Integrated Phase: Act and make the right changes across offline locations 11
Optimized Phase: Engage customers across any channel 15
Conclusion 16
16
A Technical White Paper from Blue Unicorn
Unlocking the Business Potential of the Offline
World Through Wi-Fi Bluetooth Location Analytics

IntroductionExecutive Summary
Retailers in stores need deep
insight into consumer behavior and
foot traffic patterns to better engage
shoppers and combat their drift
toward shopping online. The
exponential growth of
smartphones, Wi-Fi Bluetooth
infrastructure offer an opportunity
for retailers to capture this insight in
the physical world, much as online
retailers have been able to do for
some time.
Blue Unicorn, a pioneer in this
emerging field of mobile location
analytics, offers a solution that can
be deployed quickly and at very low
cost—and, unlike competing
technologies, can easily scale
across hundreds or even thousands
of stores. BU gathers the industry’s
largest and most diverse data set,
processing billions of data inputs
daily. The influx of data feeds into
BU's continuously evolving
algorithms that process and
compute meaningful business
metrics across hundreds of millions
of shopping sessions yearly. BU's
commitment to developing the
industry’s leading proximity based
data science ensures retailers base
their customer engagement
strategies on the freshest and most
accurate analysis.
Online retail (or “e-tail”) has had a significant competitive advantage
over retailers from the start: their ability to capture customer metrics
that answer fundamental questions about how effectively their
marketing promotions drive traffic. By their very nature, e-tailers
have been able to capture every interaction, from click-through
to checkout, and analyze it across multiple dimensions. E-tailer
analytics reveal the frequency of customer visits, their duration,
whether and how often they return, conversion, even the extent to
which coupons and other special offers change behavior. The results
of this analysis in turn allow e-tailers to identify their best customers
and most likely prospects, target their messages to the audiences
most likely to respond, and achieve greater ROI for every marketing
dollar spent. To the chagrin of traditional retailers, this means e-tailers
are more able to respond faster to changes in the marketplace.
To overcome this handicap and protect their ability to compete,
retailers need greater understanding of when their own customers
visit, whether and how they’re engaged, and how often they return.
Blue Unicorn invented a way to leverage three now-ubiquitous
technologies—smartphones, Bluetooth and Wi-Fi—to enable
retailers to capture these insights across all their stores.
Smartphones continuously search for and/or connect to Wi-Fi
Bluetooth access points. At the same time, access points are
constantly listening for access signals being emitted by devices
looking for a connection.
Of course, not everyone has a smartphone, and some people with
smartphones switch off their Wi-Fi Bluetooth capabilities.
Nonetheless, smartphones are so common that they provide a
statistically relevant sample of shoppers in the retail environment.

Over the past 20 years, the online world has fine-tuned its capabilities
to accurately target prospective buyers and streamline the purchasing
and fulfillment process. To create the perfect online customer
experience, every step of the value chain is measurable and based
upon data science and fact-based decision making.
In stark contrast, the offline world that incorporates physical stores
and brick-and-mortar businesses essentially remains stuck in analog.
Why? Since its very inception, the offline world has been difficult to
detect and measure at scale. Through the years, businesses have tried
various approaches including manual counting, gut intuition, and
complicated counting devices or cameras.
For businesses with hundreds or thousands of store locations, or
venues with dense and unpredictable foot traffic such as airports or
hotels, the ability to measure at scale becomes a complex, error-prone
and expensive proposition. As a result, businesses are often flying blind
in the offline world. On the flip side, offline consumers are on the
receiving-end of a poor customer experience across every physical
touch point.
Thankfully, much has changed over the past several years. The
explosion of mobile devices and the dawn of The Internet of
Things (IoT), combined with the power of big-data in the cloud,
have created a perfect storm to now unlock the mysteries of the
physical world. In the United States today, 64 percent of the
population owns a smartphone. In Europe and Asia, smartphone
penetration hovers at 80 percent.1
With a smartphone in
everyone’s pocket or purse, the physical world has finally become
machine readable through proximity location analytics in the
cloud.
For brick-and-mortar businesses
such as retail stores, quick service
restaurants, hotels, grocery, airports
and shopping malls, this new insight
creates a tremendous business
opportunity. By understanding
consumer traffic and behaviors within
physical locations, businesses can
optimize marketing, in-store operations,
strategic decision-making and staffing
activities. At the same time, customers
benefit through efficient service and an
exceptional customer experience.
Transitioning from analog- to data-
driven decision-making creates a host
of questions and challenges for brick-
and-mortar businesses. What should be
measured within offline locations? How
should these new data sets be applied
across the business? How is consumer
privacy protected? How should online
and offline activities converge?
Figure 1: The Offline Maturity Model
64%
80%
In the
United States
today
In Europe and
Asia smartphone
penetration
hovers at
of the population
owns a smartphone
Overview
1
2
3
4
PHASE
PHASE
PHASE
PHASE
Foundational
Establish a modern
offline infrastructure
incorporation door
counter, Wi-Fi, point
of sale (POS) and CRM
Formalized
Measure and analyze
offline metrics and
establish a baseline
Integrated
Align offline metrics
with business data
and outcomes;
Integrate third
party apps
Optimized
Fully converge
online and offline
metrics and
processes
Table Stakes
Know
Act
Engage
Customer
Impact
Time

Foundational Phase:
“Table Stakes” for any
offline business
Understandably, the knee-jerk reaction for every company is to
attempt to rapidly replicate a parallel online universe into their offline
business. The reality is that making this digital shift is an evolutionary
process and does not happen overnight. As such, companies should
implement an incremental approach that progressively builds upon
foundational technologies, best practices and key metrics.
This white paper is based upon the Offline Maturity Model (see
Figure 1) and provides practical strategies to help companies as they
begin their journey of measuring, analyzing and optimizing their
offline or brick-and-mortar locations through proximity location
analytics.
In the Foundation Phase,
offline locations lay the
groundwork for the next-
generation of retail stores,
restaurants, airports,
shopping malls and hotels.
Recently, most companies have invested
heavily in high-speed Wi-Fi infrastructures,
new Point of Sale (POS) systems, cloud-
based CRM applications and big-data
frameworks. Other foundational items
such as door counters should also
be incorporated during this phase.
1
PHASE
Figure 1: The Offline Maturity Model
1
2
3
4
PHASE
PHASE
PHASE
PHASE
Foundational
Establish a modern
offline infrastructure
incorporation door
counter, Wi-Fi, point
of sale (POS) and CRM
Formalized
Measure and analyze
offline metrics and
establish a baseline
Integrated
Align offline metrics
with business data
and outcomes;
Integrate third
party apps
Optimized
Fully converge
online and offline
metrics and
processes
Table Stakes
Know
Act
Engage
Customer
Impact
Time

45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
2010 2011 2012 2013 2014 2015 2016 2017 2018
(Actual)
Clothing
Large Retail Stores - DIY/Warehouse/Electronics
Food Grocery
Dinning/Beverage
Small Retail Stores
Airports
Financial Services
Auto/Car Dealerships
Shopping Center Malls
Other
Wi-Fi Bluetooth: The Digital Platform
for Next-Generation Brick and Mortar
Over the past few years, Wi-Fi Bluetooth have become
commonplace utility within the offline world. In fact, today it’s almost
impossible to find a store, restaurant, hotel, airport, or public space
without Wi-Fi or Bluetooth access. In fact, 82 percent of medium and
large retailers have already deployed in-store Wi-Fi and Bluetooth.2
Over the next decade, Wi-Fi Bluetooth networks and hotspots are
expected to rapidly grow across a variety of industries. In fact, the
prevalence of Wi-Fi Bluetooth will create new business opportunities
across venues for retail, hospitality, grocery, airport, financial services
and auto dealerships
(see figure 2 for additional details).
Figure 2: Global Wi-Fi Bluetooth Networks in Venues by 2020 (IBN Research)
The common Wi-Fi Bluetooth thread that runs across the offline
world has now emerged as a reliable data platform for supporting
proximity location analytics at scale. Proximity location analytics
from Blue Unicorn leverages the existing or deploys new Wi-Fi
Bluetooth infrastructure within offline locations such as stores,
restaurants, hotels, airports, shopping malls and other public
spaces. As companies move towards an omni-channel model,
Blue Unicorn also provides the ideal platform to integrate multiple
customer touch points and datasets.
Through this “passive” approach, Blue
Unicorn proximity system will detect a
mobile device trying to connect to the
network and collect anonymous device
information, which is then aggregated
and analyzed in the cloud. The offline
metrics generated from proximity
location analytics paints an accurate
picture of customer behavior and
patterns to help businesses better
understand their physical stores,
restaurants and other offline locations.
More details about the key offline metrics
will be discussed in the Measurement
section of this white paper.

As companies build out their Wi-Fi
Bluetooth infrastructures during
the Foundation Phase, they should
do so with an eye towards privacy.
Fostering consumer trust and
ensuring privacy requires three
critical components:
1 A comprehensive policy:
Any privacy policy should outline
the parameters of what data is
collected, stored and protected.
Any policy should clearly
communicate the scope of the
non-personal data collection
process.
2 Disclosures:
Well-placed signage in the physical
location should communicate to
consumers about the presence of
proximity location analytics.
3 Opt-out process:
Every consumer should have the
opportunity to opt-out of any data
collection process. This opt-out
process should be During the
Foundational Phase, any
company considering deploying
proximity location analytics
should carefully analyze all privacy
considerations, establish a
comprehensive policy and
consistently exhibit transparency
with customers.
Twenty years ago with the dawn of online e-commerce, consumers
reacted with immediate suspicion. Understandably, consumers
expressed concern about fraud or identity theft when providing their
credit card and other personal information online. Over time, online
businesses incorporated stringent consumer protections, privacy and
security measures into their ecommerce engines. Today, most
consumers don’t even think twice when hitting the “One-Click”
purchase button on Amazon.
The ubiquity of mobility and its ability to accurately measure the
offline world is reigniting the privacy discussion. Consumers have
a reasonable expectation of privacy whenever they walk into a store,
bank, airport or hotel. As such, every business has an obligation to
address privacy concerns and instill consumer trust with an effective
set of protections and policies.
Blue Unicorn is a co-signatory of the
Mobile Location Analytics Code of
Conduct from the Future of Privacy
Forum. This policy was authored and
reviewed with the consent of the
Federal Trade Commission, industry
leaders and members of Congress.
Today, this code is regarded as a best
practice for any company deploying
proximity location analytics.
Unlocking the Business Potential of the Offline World
Through Wi-Fi Bluetooth Location Analytics
Privacy First

Why Wi-Fi Bluetooth?
Key facts by the numbers
There is a access point for every 150 people on Earth. Over
the next four years, global hotspot numbers will grow to more
than 340 million, the equivalent of one hotspot for every 20
people on earth (Source: BBC). Mobile data traffic will
approach almost 197,000 PB (Petabytes) by 2019, the
equivalent to over 10 billion Blu-ray movies. To handle this
load, 59% of network traffic will be offloaded to networks
(Source: Juniper Research).
82%
of medium and large
retailers have already
deployed in-store access points
Today, 82% of medium and large retailers
have already deployed in-store Wi-Fi.
At the same time, nearly 70% of specialty
retailers are designing their next generation
Point-of-Sale system that relies upon a
powerful and reliable Wi-Fi backbone
(Source: IHL Group).
94%
of hotel customers
cite Wi-Fi as the most
important amenity
A recent survey found that 94% of
hotel customers cite Wi-Fi as the most
important hotel amenity, with 38% saying
that they would book elsewhere if there
were no Wi-Fi available. Hotels are taking
notice with 64% offering free Wi-Fi to their
customers. (Source: from Hotelchatter)
65%
of consumers expect
free Wi-Fi in restaurants
In a 2014 survey, 65% of consumers
expect restaurants in the quick-service
segment to offer free Wi-Fi access in their
restaurants (Source: Technomic Inc.)
By 2020, the Internet of Things will create
an estimated 32 billion connected and
machine-readable devices (Source: IDC).
Wi-Fi, is perhaps most suitable and reliable
network for the IoT.
Through Wi-Fi Bluetooth Location Analytics

Formalized Phase:
Know the entire
offline environment
Establish a Metrics Baseline for Offline
In the Formalized Phase,
offline businesses gain an
understanding of the core
metrics driving their physical
locations. Armed with this
new insight, businesses will make smarter
decisions that optimize business
outcomes. As companies begin to align
this new insight across their business,
they will begin the process of building
a “culture of analytics” and data-driven
decision-making.
The first step for any offline business is to accurately measure the
foundational metrics that define their physical spaces. Leveraging Wi-Fi
location analytics, companies can rapidly establish a baseline across
nine key attributes for customer attraction, engagement and retention:
Visitors: How many customers are in a store at any given
point in time? How does current traffic compare to the
same period a year ago?
Storefront Conversion: How well does a storefront pull
customers into the store? Most stores have no empirical
data to assess the effectiveness of their storefronts or
window displays.
Walk Bys: How many people walked by an establishment,
but did not enter?
Outside opportunity: What is the total sum of customers
who walked by and entered an establishment over a period
of time? This data helps determine the potential of store’s
or restaurant’s location, storefront appeal or best days to
launch a sale.
Duration Time: What is the average amount of time
a customer spends in an establishment?
Bounce: How many people leave after spending
a short amount of time in an establishment? For
example, a store may establish a 5-minute threshold
for customers who leave after not engaging with the
merchandise or store associate.
Engagement: How many customers spend greater than
20- or 30-minutes in a given store?
New visitors: How many net new customers visited
an establishment?
Repeat visitors: How many repeat customers visited an
establishment? How many of these people represent new
customers from the past month?
2
PHASE
Through Wi-Fi Location Analytics

Create a Culture
of Analytics
For the past several decades, traditional
brick-and-mortar businesses were well
served through intuition and gut decision-
making. As the online, mobile and offline
worlds rapidly converge, this intuitive
approach does not align with the realities
of today’s hyper-connected consumer.
Unfortunately, many offline businesses –
especially brick-and-mortar retailers –
are behind the analytics curve. In fact,
a recent study of the 200 top retailers in
North America, a whopping 80 percent
stated that they are behind Amazon in
terms of analytics maturity. At the same
time 71% perform basic or no analytics
or reporting, with another 42% having
no single owner responsible for creating
an analytics strategy and roadmap.3
As traditional offline businesses make the shift from intuitive
to data-driven decision-making, they must instill a new culture
of analytics based upon four important concepts:
Invest in a new breed of analytics: Invest in the right technologies
and solutions that provide a complete view into consumer
behaviors, patterns, paths to conversion, and ongoing loyalty.
Wi-Fi analytics provides the foundational metrics to understand
offline behaviors, while helping connect the dots with the online world.
Hire data-science expertise: Investing in analytics tools and
technologies is only half the battle. Companies must also bolster
their in-house expertise across all core business functions.
As such, companies must hire analytics talent and leadership
to define the analytics best practices, drive the transformation
process and implement the chosen analytics technologies. Today,
many companies are hiring Chief Data Officers or VP of Analytics
to help bridge the divide between the organization’s data assets
and core business functions.
Empower everyone: Analytics are not just for the line of business
and CXOs located at the corporate headquarters. By empowering
stores and individual locations with analytics, local managers can test
and fine tune new store layouts or promotions, rapidly solve problems,
and make quicker decisions that affect store conversions.
Break down data and organizational silos: Every business employs
an endless array of online and offline customer touch points spanning
physical stores, catalogs, mobile ads and apps, direct mail, television,
web storefronts, social media and loyalty programs. Unfortunately,
these touch points are often manifested in separate data and
organizational silos creating internal friction and ultimately a poor
customer experience. Consumers want a seamless experience with their
brands, and a company’s internal processes should reflect the same.
71%
42%
of retailers
perform basic
or no analytics
or reporting
of retailers have
no single owner
responsible
for creating an
analytics strategy
or roadmap

Act and make the right
changes across offline
locations
Incorporating Business Data
and Processes
In the Integrated Phase,
companies align their offline
metrics with business data
and processes. With this
business-level context,
companies can adjust the appropriate
levers across their physical locations to
optimize their business outcomes. During
this phase, businesses may also integrate
other data sets that play a role in helping
define the customer experience.
Offline metrics will paint an accurate picture about historical consumer
behavior and patterns within brick-and-mortar locations. Once this
data is aligned with relevant business data, companies then have the
context to make fact-based decisions and drive the right business
outcomes. Core business processes and systems that should be
aligned with offline metrics include:
Point of sale:
Individual brick-and-mortar locations live and die by
their individual sale results. Understanding the underlying
physical factors driving sales helps individual stores or
locations isolate areas for improvement while creating
certainty in the decision-making process.
Marketing attribution:
Marketers always struggle with the age-old question:
Are marketing activities driving new sales in the store
– and can this be proved? Linking offline metrics
with marketing campaigns gives marketers the ability
understand the efficacy of their marketing programs
and campaigns.
Employee staffing:
Understanding historical offline traffic patterns takes
the mystery out of staffing requirements. With this
new insight, brick-and-mortar locations can staff
appropriately based upon seasonality, day of the week,
holidays and other forecasting attributes. When this data
is aligned with HR and staffing data, businesses can
also optimize for hiring, staffing and resource planning.
Event Testing:
Brick-and-mortar businesses will often adjust variables
within their physical environment (new store front or
layout, in-store greeters, etc.) to optimize sales and
customer engagement. By leveraging Wi-Fi location
analytics, businesses can now conduct A/B event
testing to determine which changes to the physical
environment deliver the best outcomes.
3
PHASE

How Vertical Industries
Optimize Business
Outcomes with Wi-Fi
Analytics
Specialty Retail
Wi-Fi location analytics produces a
common data set, regardless of the
physical location. That said, every
vertical industry leverages Wi-Fi analytics
very differently to solve specific business
challenges. The following section details
how various industries incorporate Wi-Fi
location analytics within the context of
their businesses.
Today, online retailers are empowered with detailed insights about
customer activity (traffic, banner ads, mouse clicks, web paths, etc.)
to drive “mouse click” sales. Without similar data and insights about
physical store locations, brick-and-mortar retailers often struggle to
optimize key operational variables to boost in-store traffic, loyalty,
engagement and sales.
• Campaign and Event Testing: What was the difference in
storefront conversions before and after a change was made
to a store window or layout? What was the difference between
bounce and duration rates before and after the window change?
• Loyalty Marketing: Did a promotion attract the same shoppers
who typically accept offers? Or did the promotion attract new
shoppers, who can be later converted into loyal shoppers?
• In-store Engagement: Are traffic and engagement rates increasing
within specific locations of the store? For example, if higher-margin
furniture is sold on the second floor, is the in-store merchandising
driving more traffic upstairs?
• Staffing: What is the optimal staffing plan for normal, peak, holiday
and promotional periods? Are there certain areas of the store that
require additional staffing needs? How can retailers identify
opportunities to improve customer service?
From a marketing perspective, retailers execute a slew of programs
to drive traffic into their physical store locations including advertising
campaigns, loyalty programs, promotions and catalog mailers. Wi-Fi
location analytics helps marketing organizations accurately assess
campaign effectiveness, ROI and sales attribution
to specific marketing activities.
• Marketing Attribution: Did shopper traffic increase in the
two-week period following a promotion or catalog drop?
Did the boost in traffic correlate an increase in sales?

Hospitality
Shopping Malls
Large hotel properties always have a
constant stream of traffic flowing through
their lobby and other common areas –
yet don’t know the operational attributes
associated with guest activity. Armed
with this information, hotels can better
align the guest experience with the right
staffing support, amenities, and facilities.
• Revenue Generation: Where should
the hotel focus its marketing efforts
to drive traffic into the restaurants–
on-property or off-property?
How many visitors passing by
the restaurant are actual guests
of the hotel?
• Staffing: How many guests pass
through specific hotel zones? Are
there specific areas of the hotel that
require additional staffing needs?
How do I identify opportunities to
improve guest services?
Large format shopping malls require a comprehensive understanding
shopper traffic data to accurately align rent prices, optimize mall design
and create compelling mall campaigns to drive store traffic.
• Mall Layout: During what times of the day is the mall busiest?
Which zones were the busiest (or slowest) for the day?
How many zones did shoppers stop by? How engaged were
shoppers at each zone?
• Rent Optimization: Which stores are located in the busiest zones
and should their rents be priced commensurately?
• Mall Events: Are mall events effective at driving incremental traffic
throughout the mall, beyond the area of focus for the event?

Airports and
Transportation Hubs
Quick Service Restaurants (QSR)
By their unpredictable nature and
fluctuating traffic patterns, airports and
transportation hubs present many
logistical and operational challenges. By
understanding passenger traffic, airports
can create a pleasant traveller experience
across a variety of parameters:
• Security Screening Wait Times:
How long did it take for passengers
to clear security in the various airport
zones? Is security staffing aligned
accordingly?
• Airport Layout: Which airport
locations/zones would be better
suited for quick service restaurants,
coffee and gift shops? Similarly,
which locations would be better
suited for specialty restaurants or
retail? How should rent be attributed
to each location/zone?
• Taxi Wait Times: What is the
average wait time from baggage
claim to securing a taxi? How many
taxis are required in the taxi queue
to minimize wait times?
Integrate Other Location-based
Applications
Many brick-and-mortar businesses and physical locations
leverage other location-based technologies such as RFID and
iBeacon/BLEs for mobile proximity marketing, and micro-location
and user targeting activities.
The data sets produced from these technologies complement the
overall Wi-Fi analytics dataset analyzed by Blue Unicorn and can
provide additional context and granularity for customer
engagement, sales and service activities within stores.
The successful attributes of any Quick Service Restaurant include
speed, value and accuracy. To consistently deliver on these objectives
requires new insight into how customers regularly engage with a
restaurant’s facilities. By accurately analyzing patron traffic and
behavior, Quick Service Restaurants will make better business
decisions that bolster patron loyalty and the bottom line.
Revenue and Bottom Line: Are new menu items boosting restaurant
traffic and sales? Are the restaurants generating the right amount of
traffic during non-peak hours?
• Staffing: Is staffing aligned with peak traffic times?
• Loyalty: Last month, how many new customers visited the
restaurant, and how many are coming back again? How many
customers are visiting other restaurants within the chain?
• Chain wide Performance: Across the entire chain of restaurants,
which are performing the best, and why?

Optimized Phase:
Engage customers
across any channel
In this final phase, businesses
possess deep insights into
the offline metrics driving
conversions and sales within
their brick-and-mortar
locations. At the same time,
these metrics are integrated across
marketing, operations and other core
business functions. Finally, companies
are able to link online and offline activities
into a seamless experience for customers.
While every company wants to reach
this state of online-to-offline nirvana,
the reality is that few–if any–companies
today are able to execute against this
desired end-state.
Why? Most companies are still in one of
the first three phases of the offline maturity
curve building the Wi-Fi and application
infrastructure, in-house expertise, and
best practices to truly deliver an
“optimized” offline business. Over the
next 1-2 years, expect most companies
to accelerate their efforts across the
maturity curve to better link offline with
online activities.
Only with the right infrastructure,
internal resources, and business
processes already in place can
companies effectively extract
value from the linkage of these
two massive datasets.
4
PHASE

The Holy Grail: Online
and Offline Convergence
Physical stores and brick-and-mortar
locations remain the cornerstone of any
business model. In fact, about 92 percent
of all commerce still takes place offline,
suggesting that the social, physical and
interactive dynamics of the showroom
remain relevant instill confidence with
shoppers. Forrester Research predicts
that e-commerce will grow $150 billion
by 2018, but offline retail will increase
by $300 billion.4
While the offline world
remains an essential cornerstone of
everyday life, its underpinnings no longer
resemble the brick-and-mortar businesses
of yesteryear. Today, the lines are blurring
between the online and offline worlds.
Consumers are coming to demand a
seamless customer experience as they
engage with a brand across mobile, web,
and physical location in each buying cycle.
As such, brick-and-mortar locations
need to be capitalized and orchestrated
within a much broader mobile, online
and digital context.
This “holy grail” is the driving force behind transforming in-store
experiences by linking every online and offline touch point. Most
importantly, this shift is now requiring the offline domain to
produce metrics on par with their online counterparts to:
• Create a true omni-channel experience: In a recent survey,
34 percent of marketers at consumer brands admitted they do a
good job of linking their online and offline customer experiences.5
Marketing professionals have a large gap to cross: A majority
of dollars spent offline, yet the majority of product research
transpiring via the Internet or mobile.
• Understand how online drives offline traffic: Consumers often
gather information on the Internet – especially for complex or high
value products – and buy in the store. Similarly, online and mobile
marketing is also a prime vehicle to drive offline traffic into the
stores. Unfortunately retailers can’t see where their customers
are coming from.
• Justify online-to-offline marketing attribution: Marketing
budgets continue to shift towards digital channels. With the
explosion with mobile devices, marketing organizations want
to better understand mobile’s role in bridging the gap between
online and offline channels.

Conclusion
The blending of online and offline is today driving a new culture of
analytics within every brick-and-mortar business. As companies make
this transition, they ultimately aspire to replicate the precision, data
science and analytics created by the online world. Thankfully, the
explosion of mobile devices now makes the physical world machine-
readable and capable of being measured and analyzed at scale.
At the same time, the pervasiveness of Wi-Fi creates the ideal platform
for detecting and analyzing customer traffic, behavior and patterns from
mobile devices within brick-and-mortar locations.
About Blue Unicorn
Blue Unicorn is the world leader in Wi-Fi
and proximity location analytics. The
company provides answers and insights
for the physical world in the same way
that web analytics does for e-
commerce.
By accurately analyzing visitor traffic,
behavior and shopping patterns, BU
helps the world’s leading brands design
the perfect customer experience for their
brick-and-mortar locations and drive
better business results.
BU's network captures billions of
measurements per day, analyzing
hundreds of millions of potential shopping
sessions per year across tens of
thousands of locations including retail
stores, quick service restaurants,
airports and shopping malls. Only
anonymous, non-personal data is ever
collected and only aggregated trend data
is used for analysis.
Visit http://www.blueunicorn.co.in
for more information.
Gaining this new understanding requires a practical and incremental
approach. Many retailers, quick service restaurants, hotels, shopping
malls, transportation hubs, grocery stores and banks have recently
built a modern foundation of Wi-Fi and cloud-based CRM and point
of sale (POS) systems. Building upon this foundation, businesses can
now leverage their Wi-Fi as a platform for deploying location-based
analytics to understand customer behavior and its impact on business
outcomes. Through this insight, CXOs and line of business executives
can make data-driven decisions–a significant departure from the
intuition approach of yesteryear.
Finally, every company aspires to the “holy grail” of seamlessly
linking their online and offline worlds across every customer touch
point. That said, few companies today are able to execute against this
desired end-state. With this long-term vision, companies should take an
incremental approach and focus first on bolstering their infrastructure,
analytics expertise and business processes.

Unlock new Business Potential in the Offline World Through Wi-Fi & Bluetooth Location Analytics

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Unlock new Business Potential in the Offline World Through Wi-Fi & Bluetooth Location Analytics