mobile attribution for data-driven marketers

MOBILE ATTRIBUTION
FOR DATA-DRIVEN
MARKETERS
2016 REPORT
HOW FOOT TRAFFIC
ATTRIBUTION WORKS
WHY IS IT SO HARD TO CALCULATE
MOBILE ADVERTISING ROI?
Historically, there has been a glaring problem in measuring mobile advertising ROI. For years, Mary Meeker’s
famous slide—which depicts the gap between the time consumers spend on mobile devices and the amount
of money advertisers spend on mobile media—has highlighted the need for better measurement in mobile.
(See graph below for depiction of Mary Meeker's slide.) The cookie-less mobile ecosystem paired with relatively
low levels of mobile commerce means brands are left wanting when it comes to measuring mobile advertising
ROI. As the adage goes, what can’t be measured, shouldn’t be bought. Thus, the “Meeker Gap.”
While the ultimate goal for brands is to tie campaign dollars directly to a specific transaction, the data
standards, technology, and scale are still lacking in order to close the loop at this level of granularity. To
address the Meeker Gap, advertisers have begun using mobile location data to measure foot traffic and evaluate
the effectiveness of mobile advertising. While using foot traffic as a metric has improved marketers' ability
to measure ROI, it is important to understand the methodologies and data behind attribution measurement.
The goals of this paper are to:
•
Explain current in-market approaches to measuring foot traffic
•
Clarify the pros and cons of each measurement approach
•
Provide a list of questions to consider when choosing a measurement provider
MEEKER GAP GRAPH
Percent of Time Spent in Media vs. Percent of Advertising Spend, USA, 2014
Time Spent
50%
Ad Spend
40%
30%
20%
$25B+
Opportunity
10%
0%
Print
Radio
TV
Internet
Mobile
twitter @Thinknear
1
HOW FOOT TRAFFIC
ATTRIBUTION WORKS
Foot traffic attribution goes by many names, with most in-market solutions referencing visitation rates and
lift rates. Ultimately, all attribution tools seek to identify how many incremental consumers visit specific
businesses as a result of seeing a mobile ad. The word “incremental” is important to remember, because in
any given population, there are people who would naturally visit a business regardless of seeing an ad or not.
A true measure of ROI must be based on consumers who visit a business specifically because they see an ad
on their mobile device.
An important factor of all foot traffic measurement solutions is that they leverage an “exposed and control”
methodology. The exposed group consists of consumers who have seen a mobile ad for the business. In
contrast, the control group includes consumers who have not seen the ad. These two mutually exclusive
groups are used in measuring incremental lift from a mobile ad campaign. The incremental lift is calculated
by comparing the percentage of consumers in the exposed group who visited the store to the percentage of
consumers in the control group who visited the store. If the percentage in the exposed group is higher than
the control group, then the campaign drove a lift in the number of consumers visiting a store—assuming all
other performance drivers are equal.
HOW STORE VISITATION LIFT IS CALCULATED
Percent of
Exposed
Store Visits
Control Group
Percent of
Control
Store Visits
Percent of Control
Store Visits
No Ads but Activity Monitored
Percent Lift in
Store Visitation
from Mobile Ads
Target
Audience
Exposed Group
Comparison of Store
Visitation Rates
Ads Served and Activity Monitored
twitter @Thinknear
2
AUCTION VS. PANEL APPROACHES
While every measurement solution uses the exposed and control methodology to determine lift, how the data
is collected—and the accuracy of that data—can vary drastically. Today, there are two main approaches in
the market to measure foot traffic: the mobile auction-based approach and the mobile consumer panel
approach.
MOBILE AUCTION-BASED APPROACH
In a programmatic world, measurement providers typically have access to hundreds of billions of mobile
consumer data points each month. These data points are generated whenever a mobile user interacts with
an app, and that app requests an ad from a mobile programmatic platform. Along with the ad request, the
app publisher also sends a piece of location data. Auction-based measurement providers typically “listen”
to these ad requests to identify whether or not a user is at a targeted location when the ad request is sent.
If they are, a visit to that location is counted. Solution providers then perform a match to see which mobile
users were exposed to an ad as part of the campaign they have been tasked to measure.
Pros of the Auction-Based Approach
•
The number of mobile consumers covered in an auction-based approach is typically much larger
than in the panel approach.
•
An auction-based approach can typically mirror the demographics of a specific campaign.
Cons of the Auction-Based Approach
•
Most of the user’s real world activity is not recorded. The auction-based approach only captures
location data when a user happens to have an app open, and that app sends out an ad request.
•
Measurement providers do not have a direct relationship with mobile publishers. Therefore, these
providers do not have control over the accuracy of data being sent in an ad request. The true
location of a user can vary significantly from the stated location in the ad request, which means
visits to a store might be recorded when, in fact, there was no visit.
twitter @Thinknear
3
MOBILE CONSUMER PANEL APPROACH
Most marketers are familiar with the Nielsen Set Top Box panel. A representative sample of consumers installs
the Set Top Box to record which TV shows they watch. Their viewing activity is then used to approximate the
viewing activity for the rest of America. Mobile consumer panels for foot traffic work the same way. An
attribution measurement provider creates a large audience of mobile consumers who agree to have their
location tracked in an “always-on” fashion, creating a panel of mobile users. Using a smartphone’s GPS or
other location services, the measurement provider monitors user activity and measures who does and does
not visit a specific store. Using the mobile device’s unique ID, users can then be tracked back to a mobile
ad campaign to determine which users did or did not see an ad.
Pros of the Panel Approach
•
Since data collection is “always on,” data for each user on the panel is more complete, including
both coverage and duration of visit metrics.
•
Data accuracy and quality is typically higher because the measurement provider controls how the
location data is gathered.
Cons of the Panel Approach
•
Depending on how the panel was built, demographics of the panel may not be representative of
the campaign’s target audience.
•
Some panels incentivize panelists, contributing to the demographic skewing of data.
SUMMARY COMPARISON OF ATTRIBUTION APPROACHES
Auction-Based Approach
Consumer Panel Approach
"Always On" Data Completeness
No; data only collected
during active app usage
Yes; data collected in the
background
Data Accuracy
Low quality data from
exchange publishers
High quality SDK-based data
Transparent Attribution Model
No
Varies by provider
Incentivized Audience
No
Varies by provider
Demographic Make-up
Matches U.S. population
Panels typically incentivized,
but varies by provider
Dwell Time Verification
No
Yes
twitter @Thinknear
4
ADDITIONAL FACTORS
IMPACTING MEASUREMENT
DATA ACCURACY
It is well documented (see Thinknear’s Location Score Index) that location data quality in the programmatic
mobile ecosystem is inaccurate if not filtered properly. If a mobile user’s location data is inaccurate, then a
measurement provider might incorrectly record the user as visiting a certain location when, in reality, the user
could be located miles away. Data accuracy is hugely important, and marketers looking to measure foot traffic
should clearly understand what types of data are used by any solution provider.
MEASURING MULTI-CHANNEL CAMPAIGNS
If the same cross-channel ad campaign is running simultaneously with multiple vendors, it will be difficult
for any measurement vendor to determine which specific campaign influenced foot traffic. Concurrent campaigns
make it difficult to compare one vendor versus another. When measuring foot traffic, be sure to isolate specific
markets and media spend to ensure "clean" results.
SEPARATION OF MEDIA & MEASUREMENT
Many mobile advertising partners offer marketers both media and measurement services. Most marketers
typically prefer to purchase media and measurement solutions from different vendors, but in the case of foot
traffic attribution, there are arguments to be made for both independent and non-independent vendors. At a
minimum, ad partners should have an “ethical wall” between their measurement and media tools. That said,
optimization is important to performance, and providers who offer both media and measurement are often
better suited to optimize throughout a campaign to drive better lift in foot traffic. Buyers simply need to be
aware of what they are buying.
SCALE & TRANSPARENCY
Advertisers evaluating foot traffic measurement providers should understand the scale of the data being used
to measure foot traffic lift. Every measurement provider can easily provide a count of how many mobile users
were included in the exposed and control groups for a particular campaign. For instance, some campaigns
will have great results with hundreds or thousands of users in the matched groups. However, other campaigns
will only have a few users, which makes it difficult to measure incremental foot traffic. It is critical for marketers
to have transparency into how measurement providers are attributing foot traffic. This level of transparency
not only ensures a high level of data quality but also allows marketers to be better informed about campaign
performance.
twitter @Thinknear
5
KEY QUESTIONS TO ASK A
MEASUREMENT PROVIDER
When deciding on an attribution measurement provider, it is key to have complete transparency in terms of
data source, data accuracy, and demographic makeup. Below is a list of eight questions for you to ask
prospective measurement providers.
1. Is your attribution data based on ad calls at a point in time (auction approach), or do you have “always
on” location data (panel approach)?
2. Is the attribution audience incentivized in any way to participate, and is it demographically representative
of my campaign’s target audience?
3. If an auction approach is used, do you have a process for filtering the data for accuracy?
4. How do you ensure the accuracy of the data being used in your attribution calculations?
5. Can campaigns be optimized for foot traffic while the campaign is running?
6. How transparent is the methodology to report store visitation?
7. What are the primary metrics reported in measuring foot traffic lift?
8. How many mobile users are included in the control and exposed groups?
THE FUTURE OF MOBILE
ATTRIBUTION
For brick and mortar advertisers, foot traffic attribution presents an opportunity to greatly enhance the ability
to measure mobile ROI. While the perfect solution of tying a mobile campaign to a consumer purchase has
yet to be developed, the current methodology for measuring foot traffic significantly increases the marketer’s
understanding of mobile campaign performance. With the vast majority of all transactions still happening
in-store, getting consumers through the front door indicates purchase intent, which is one step closer along
the path to purchase. Over time, we expect existing solutions to continue to improve and new solutions to
come to market. We encourage any brick and mortar marketer to engage with measurement providers,
understand the data, and push for more transparency and effectiveness in the measurement of foot traffic.
twitter @Thinknear
6
ATLANTA
BOSTON
CHICAGO
DALLAS
DETROIT
LOS ANGELES
NEW YORK
SAN FRANCISCO
SILICON VALLEY
ABOUT THINKNEAR
Thinknear is a location technology company and full-service mobile advertising
platform focused on delivering amazing advertising campaigns for agencies, brands
and consumers. Thinknear’s platform delivers the accuracy, scale and technology
required to effectively leverage mobile location data to power better consumer
experiences. In mobile, accuracy matters, and as a division of Telenav, Thinknear
leverages exclusive access to over 15 years of proprietary location data. To learn
more, please visit www.thinknear.com and follow @thinknear on Twitter and Instagram.
WANT MORE?
INDUSTRY REPORTS
CASE STUDIES
WHITE PAPERS
INFOGRAPHICS
Visit thinknear.com or email [email protected]
Copyright © 2015 Thinknear by Telenav.
Copyright © 2015 Thinknear by Telenav.