This document discusses using location-based services and mobile consumer analytics to increase consumer engagement for brands. Some key points: 1. LBS allows brands to understand consumers' shopping preferences, store visit patterns, and travel habits by analyzing location data from opted-in mobile phones. 2. A study tracked 200+ participants' locations over 2 weeks using GPS from their phones. Insights included most visited store types, popular shopping times, travel routines. 3. Brands can use these insights to strengthen existing customer relationships, target prospects near competitors, and measure out-of-home advertising effectiveness. Understanding consumers' locations helps deliver more relevant offers and content. 4. However, incentivizing continuous data

1. Using Location-Based
Services to increase
consumer engagement
April 2010

2. :: Using location-based services to increase consumer engagement ::
contents
1. Executive Summary | 3
2. Introduction: Mobext and Cadio study | 4
3. Benefits of Marketing using GPS-Based Mobile Consumer Analytics | 5
4. Brand Challenges | 8
5. Brand Application Process | 9
6. Conclusion | 10
contributors
Phuc Truong
Managing Director, Mobext US
phuc.truong@mobext.com
Sharon Bernstein
VP, Insights Director
sharon.bernstein@mediacontacts.com
Jared Hopfer
Mobile Marketing Manager, Mobext US
jared.hopfer@mobext.com
Dr. Thaddeus R. F. Fulford-Jones
CEO, Cadio US
thaddeus@cadiomobile.com
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3. :: Using location-based services to increase consumer engagement ::
1.
executive
summary
Location-Based Services (LBS) uti-
lizes a mobile device’s geography
to deliver relevant information to
a consumer, and is creating a new Mining consumer
means of mobile marketing. location data
Advertisers can now overlay location patterns
with existing customer data to deliver prospects
custom messages at the right time by serving
Predicting behavioral
unique, relevant, time-targeted offers based on
patterns
shopping patterns, consumer segmentations,
and travel history. Mobile consumer analytics
is not limited to consumers who have high-end
smart phones; a majority of standard feature
phones in the US have GPS hardware that can Protecting users
transmit location data with a consumer’s opted- privacy
in consent.
LBS technology allows an advertiser to yield
various insights, including shopping preferenc-
es, competitive store visits, time and frequency MOBILE
for shopping activities, as well as travel patterns. CONSUMER
Armed with additional mobile consumer ana- ANALYTICS
lytics, advertisers can enhance their marketing
efforts by strengthening the value of existing
customers while using the data to supplement
competitive intelligence.
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4. :: Using location-based services to increase consumer engagement ::
2.
Introduction:
mobext and CADIO STUDY
In late 2009, Mobext, the mobile time stamped and returned to Cadio’s servers
in real-time. The maximum data acquisition fre-
marketing network of Havas Digit- quency was 10 GPS data points per hour.
al, partnered with Cadio, a mobile
In the study, over 200 retail or lifestyle-relevant
consumer analytics firm, to analyze participant destinations were mapped. These
GPS data from opted-in mobile destinations included: airports, hotels, train sta-
phones to better understand con- tions, large national retailers, supermarkets, and
sumer interests and habits. selected other categories.
Mobext recruited Sprint subscribers to share
semi-continuous GPS data (once every 10 min-
utes) with Cadio via their mobile devices. Partic-
ipation was entirely voluntary and no incentive
was offered to candidates.
In order to participate in the study, the volun- Female 42% Male 58%
teers signed a consent form, in effect opting into
the study. The participants were all between the
ages of 25-54, 58% male and 42% female. They
resided in three different metro areas: Boston,
MA, Chicago, IL, and New York City. The loca-
tion data was collected for two weeks, from No-
vember 25, 2009 to December 9, 2009. This time
period was chosen specifically to capture travel
and shopping patterns associated with the long
Thanksgiving weekend.
Participants were not required to download an
application onto their phones, but instead lo-
cation data was requested and acquired auto-
matically via the Sprint network. Cadio’s servers
transmit a request for GPS data from an opted-
in Sprint handset, and the request is forwarded
to the mobile network via an aggregator. Sprint
initiates a network-based request to activate the
GPS hardware on the handset. Once the hand-
set acquires a latitude-longitude fix, the data is
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5. :: Using location-based services to increase consumer engagement ::
3.
Benefits of Marketing
using GPS-Based Mobile
Consumer Analytics
The study revealed that GPS location data can within store premises, might consider expand-
deliver actionable insights that inform brand ing their menu to include foods items beyond
decision-making: snacks. Smaller retailers may benefit by partner-
ing with nearby restaurants in driving comple-
Increase the value of mentary traffic between stores.
a marketing panel
The panel revealed that participants who dined
out had a lower tendency to engage in fitness
Brands can append their existing marketing
activities than those who did not. Conversely,
panels with inferences from mobile consumer
the average frequency of fitness activities for
analytics to understand the travel patterns, pref-
individuals who went to quick-serve coffee or
erences and lifestyles of their customers, and to doughnut locations was 50% higher compared
determine how often they are near store loca- to those that did not visit such locations.
tions. Brands can also determine where consum-
The data also unveiled a link between shopping
ers shop (including whether near home or work),
and behavioral preferences. For instance, par-
and what days of the week and times of day they
ticipants who visited Whole Foods were twice as
go shopping. They can establish the lifestyle pat- likely to engage in fitness related activities com-
terns and brand affinities of their customers to pared to individuals who shopped elsewhere.
create offers and marketing messaging that are Additionally, half of the participants who vis-
most likely to resonate and improve consumer ited Whole Foods also frequented other grocery
engagement. stores during the study.
During the study we discovered that the pan- An obvious application of this insight would be
elists who preferred Dunkin Donuts were 33%
for Whole Foods Market to create co-marketing
more likely to dine out than those panelists that
programs with gyms or yoga studios to increase
preferred Starbucks. Conversely, participants
who went to a Wal-Mart were 60% more likely to acquisition rates; similar to the retailer and res-
dine out compared to Target customers. taurant example above. Such joint marketing
programs that offer complementary services/
Adding onto the behavior of shopping prefer-
products are not new. However, mobile market-
ence and dining out, of the Target customers
ing tactics can further enhance such programs by
who dined out, approximately 25% of Target cus-
tomers went to a restaurant prior to going to Tar- improving the relevancy for targeted consumer
get and an additional 25% of customers went to segments. Our experience shows that delivery
a restaurant after going to Target. of offers via a mobile device is more impactful
because users are more likely to acknowledge
Armed with this information, retailers like Tar- such messages.
get and Wal-Mart, who have snack food options
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6. :: Using location-based services to increase consumer engagement ::
Strengthen the value
of existing customers
Advertisers can send offers to customers at the
optimal time for them to respond based on their Saturday 31.8% Sunday 36.4%
location/proximity to a store location, knowing
when they are likely to shop, and what they like
to buy. This makes the offer more relevant to
consumers.
By leveraging location information from exist-
ing customers, retailers with retention programs
Friday 13.6% Monday 2.3%
(i.e., loyalty cards) can create programs that focus
on increasing the recency, frequency or spend Thursday 2.3% Tuesday 6.8%
among the customer base. When personal and Wednesday 6.8%
work travel patterns are included in the mix we
are able to help brands select offer expiration
Obtain competitive
dates, or limited-time incentives. Furthermore,
advertisers can determine which stores consum- information
ers prefer in their areas and provide higher in-
Advertisers can understand which competitors
centives for consumers to travel to farther loca-
are in the vicinity of customers’ homes and of-
tions if sales are down.
fices, where consumers spend their time, and
An advertiser with shopping pattern information most importantly, which customers visit com-
from its customers is able to tailor its messaging petitor stores. This can help a brand determine
based on the times in which their customer seg- where they should open new locations, or on the
ments choose to shop. flip side, potentially close unsuccessful locations
During the study, the data showed that close to (due to the competition’s footprint). Recommen-
70% of all visits to big-footprint retail locations dations derived from mobile consumer analytics
took place on Saturdays or Sundays; surprisingly, can also help determine the right time for a high
only 11% of visits took place on Black Friday. Con- value special offer or promotion, to de-incentiv-
versely, 25% of the people from this study chose ize customers from patronizing a competitor’s
to shop on the Sunday following Thanksgiving. store. If an advertiser wants to drive awareness or
Participants got a late start on the weekends, as gain competitive share, it could determine where
shopping commenced after 2pm on Saturdays, its prospects are traveling so they aren’t wasting
and close to 1pm on Sundays. They also only vis- marketing spend on existing customers.
ited two stores on average each Weekend day. As an example, an advertiser like McDonald’s
who has aggressively introduced their McCafe
The research also showed that Sears shoppers did
not visit any other department store. In contrast,
menu items might use competitive location
individuals who visited department stores other data to understand consumer habits relating to
than Sears always split between multiple nation- morning versus afternoon visits to other cafes.
al department store chains. In addition, if the data shows that segments of
customers visit multiple coffee destinations in
Armed with this type of insight, for retailers the morning, McDonald’s can ultimately deter-
whose customers display higher loyalty com- mine whether consumers visit their restaurants
pared to their other segments, it would be ben- for food purchases versus coffee purchases (as-
eficial for them to reward these customers above suming in this example the data shows the other
and beyond the typical rewards milestones. visits being Dunkin Donuts or Starbucks).
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7. :: Using location-based services to increase consumer engagement ::
We found that about 50% of Starbucks custom- Travel frequency – During the study we found
ers visited Dunkin Donuts locations. However, if that on average, the most on-the-move group
an individual visited Dunkin Donuts there was was from New York (New Yorkers spent 80% of
a 67% chance they would visit Starbucks. There- their time in 2.3 zip codes), followed by Chicago
fore, it appears that the volunteers in this study (2.1 zip codes), and those from Boston (1.5 zip
preferred the Starbuck’s product more so than codes). On average, commute times were 20%
Dunkin Donuts –as the increased visit frequency longer for participants who lived in or near Chi-
was 13% higher. cago than for those who lived in or near New York
City (median 72 minutes versus 60 minutes).
With this level of insight, among the questions
those competitors could consider: is the quality
of coffee better? How is my product mix com-
pared to my competitor? How important are the
customer experience factors contributing to in-
creased frequency?
Use as a Media
Planning Tool
Understanding consumer travel and work pat-
terns is crucial to creating the optimal media mix
(either for outdoor, digital out of home, or radio
advertising). Brands should determine precisely
when and where customers are traveling via car
for radio or out-of-home advertising (what roads Massachusetts participants were most likely to
they travel, what time of day, etc.). Using work travel long-distance (defined as trips of more
schedules can determine when target consum- than 100 miles in each direction) during the
study, but New Yorkers were most likely to travel
ers are likely to be watching television or using
long-distance for business purposes (midweek
the Internet. If out of the home or office, brands
trips were classified as business-related, and
can extend their message frequency via mobile travel during the Thanksgiving holiday period as
advertising. vacation-oriented). Further, when New Yorkers
traveled long-distance, those trips were shorter
80 10 than trips taken by Massachusetts or Illinois
Average Commute Distance (miles)
residents. As a consequence, New Yorkers were
Average Commute Time (minutes)
9.4 more likely to travel long distance by ground
64 72 8
8.5 rather than by air.
60
48 6 Armed with work and travel data, advertisers can
implement creative integrated media executions
32 4 that begin with traditional and mobile media
(during commuting times in the morning); on the
16 2 PC-based Web (during office hours), and back to
mobile media (when traveling). Additionally, deter-
mining store “impressions” (i.e., how many target
0 0
consumers pass a brand location) and frequency
Illinois New York
(i.e., how often a target consumer passes a brand
Commute time (minutes) Commute distance (miles) location) can also improve marketing programs.
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8. :: Using location-based services to increase consumer engagement ::
4.
By appending mobile consumer analytics to cus-
tomer profiles, travel-related advertisers can de-
termine when and what types of offers to make
Brand
(especially for leisure travel). For example, if a
consumer travels for business every other Mon-
day, provide a weekend discount/incentive for
the weekend after he travels for business so as
not to interfere with his work schedule. Travel-re-
Challenges
lated brands can also make travel easier by pro-
viding local guide content and travel directions. In order to gain access to location data, adver-
Consumer shopping patterns can be determined tisers must keep consumers at the core of this
by work hours and days at the office. During the initiative; the program’s success starts and stops
study, we found that people in New York were with them. To successfully create programs that
more than twice as likely to work past 7pm com- provide location data, advertisers must consider
pared to people in Boston and Chicago. Restau- the factors below:
rant advertisers can use this data to deliver ads
at times of the day or week that match consumer Incentivizing consumers to
habits. For example, a fast food restaurant chain continuously share GPS data
could use mobile location data to engage con-
sumers only if they are leaving work after 7:30pm GPS information is sensitive in regards to pri-
and normally drive within 0.5 miles of a restau- vacy, and consumers have a variety of different
rant location. perspectives on whether and how this data can
reasonably be shared. Younger consumers who
Digital Advertising Effectiveness are technology-engaged, and who use social
Measurement networking sites such as Facebook, Twitter and
Foursquare to name a few, are generally most
Measuring the effectiveness of digital out of likely to share their GPS data with brands in re-
home advertising has traditionally been chal- turn for appropriate incentives. Other demo-
lenging. However, with consumer travel pattern graphics may be more sensitive, in which case
information in areas where out of home place- it may be necessary to offer more attractive in-
ments are located, mobile consumer analytics centives or higher-value rewards to encourage
can now be used to accurately measure the ef- participant opt-in. Some experimentation with
fect of advertising in driving foot traffic to tar- incentive structures may be necessary to define
geted stores. By measuring consumer behav- an optimal approach that will adequately secure
ior before and after exposure to a (mobile) ad, the participation of all required demographic
a retailer can precisely assess how many more segments.
people are visiting a store because of a new
campaign. Brands can use this data to measure Safeguarding
return on investment –the real-world equivalent privacy
of online “cost per click” metrics.
Brands should comply with the CTIA’s Guidelines
for Location-Based Services in order to guaran-
tee consumer rights and a defined minimum
level of privacy control. Specifically, consumers
must have the opportunity to opt-out of GPS
data sharing at any time, and inferences derived
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9. :: Using location-based services to increase consumer engagement ::
from mobile consumer analytics must be appro- tion needed to develop a LBS mobile advertis-
priately safeguarded through the use of modern ing program.
encryption and firewall technologies.
Step 2
Technology Identify questions of interest
limitations
Advertisers should reference Section II above to
Technology can be a barrier for LBS marketing determine the types of actionable insights that
initiatives. Programs in less urban areas may be they wish to receive from a mobile consumer
more successful as there will be fewer challenges analytics program.
to collecting data in areas without tall buildings
or signal-blocking concrete. Step 3
Another challenge for marketers involves sorting Choose project parameters
through the massive amount of data to deter-
mine which data points are relevant to their mar- In collaboration with partners such as Mobext
keting efforts. Stringing together the GPS paths and Cadio, advertisers should select the follow-
of thousands of participants, overlaying time of ing parameters:
day, day of week, as well as targeting advertising • Program duration (number of weeks
by content, quickly becomes a large task. It will or months)
be important for marketers to have a defined fo- • Desired sample size (determined by
cus for this type of program. required statistical significance)
• Geographies of interest (suburban or
semi-urban areas are more GPS-friendly
5.
than densely urban environments)
Step 4
Brand Determine incentive structure
and secure consumer opt-ins
Application Leveraging GPS data through a LBS program
Process
starts and ends with the consumer. Brands must
obtain explicit opt-in permission both for con-
sumers to share their GPS data with a firm such
as Cadio and for consumers to agree to receive
Once advertisers’ address the challenges, they marketing messages via their mobile device or
need to create a framework for their LBS pro- through another channel. In order to increase
gram. As such, advertisers are recommended to the probability of customer opt-in, incentives
follow the steps outlined below: or rewards for individuals must be offered. The
form of currency varies based on the type of pro-
Step 1 gram, the targeted demographic segments, and
the program’s duration.
Partnering with the right provider
Providers of mobile consumer analytics technol- Currency types include:
ogies, such as Cadio, and agencies, like Mobext, • Cash reward
can help advertisers create the backend founda- • Loyalty points
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10. :: Using location-based services to increase consumer engagement ::
6.
• Free merchandise
• Discounts and coupons
• Customer recognition
• Customer preferential treatment conclusion
Advertisers should start their LBS marketing pro-
grams with existing marketing panels (with con-
sumers who have already opted in to share their
Deep data mining of GPS traces
information). Appending inferences derived from mobile phones provides new
from mobile consumer analytics to existing cus- types of inferences that are robust
tomer profiles will allow advertisers to iron out and reliable.
any kinks, and also capture valuable location-
based inferences with which to build improved Advertisers can use mobile consumer analyt-
segmentation profiles. ics to uncover both lifestyle-relevant and com-
Advertisers can obtain opt-in consent via any merce-relevant characteristics of existing seg-
channel –including Web-based sign-up, text mentations, helping advertisers engage in more
message opt-in or consent via a smart phone effective conversations with existing consumers.
application. Brands that already have retention- Mobile consumer analytics can also bring Inter-
based programs, such as points-based loyalty net-style click through metrics to the real world.
cards, may find it convenient to simply offer bo- Now it is possible to build a bridge between
nus points to those who register, as an incentive digital ad exposure and real-world offline con-
to participate. sumer behaviors.
Step 5
Activate
During the program, GPS data is acquired and
processed and actionable inferences are derived
accordingly. Depending on the scope of the an-
alytics, results may become available in real-time
or after the end of the data-sharing period.
Step 6
Close the loop
Mobile consumer analytics provides actionable
insight into the effectiveness of each digital ad-
vertising campaign. Return on investment data
can help guide strategic decision-making to op-
timize the marketing mix and engage in more
relevant conversations with the consumer.
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11. About Mobext
www.mobext.com
Mobext is a specialized mobile marketing agen-
cy operating within the Havas Digital family of
agencies. With offices in Europe and the Ameri-
cas, Mobext is recognized as an agency leader
in bringing brands to engage within the mobile
channel. Its core offering includes mobile strat-
egy, consumer activation and media. Its roster
of clients are globally recognized brands rang-
ing from many sectors including automotive, fi-
nance, retail, entertainment and consumer pack-
aged goods companies.
About Cadio
www.cadiomobile.com
Cadio, Inc., headquartered in Cambridge, MA,
is a pioneer in the emerging field of GPS-based
mobile consumer analytics. Cadio’s proprietary
consumer analytics engine processes semi-con-
tinuous streams of GPS data to generate action-
able inferences about consumer interests, habits
and behaviors. Cadio’s approach protects con-
sumer privacy while maximizing value for brands
and advertisers.
101 Huntington Avenue - Boston, MA 02199
www.mobext.com :: www.mobext.mobi