2016 Place Conf: Location - It's about Who not Where -- Audiences & Attribution

Observe @ ScaleSeptember 2016

Behavioral Data @ ScaleThe Location Opportunity

©2016 Sense360. www.sense360.com

Our Phones Are Getting Smarter

Fingerprint scanner

Gyroscope

Accelerometer

Magnometer

Barometer GPS

Wifi Ambient Light Sensor

BluetoothMicrophone

Camera


The Challenge Is Turning Data Into True Context

“Running Outside”

“Working Out”

“At Bar”


Goals Of The Workshop


1. Open the Black Box – What really happens and how it works

2. Opportunities – How To Use This Data

Open The Black Box


How We See Location


How Machines See Location


• Lat/Long: 41.865706, -87.765510

• Nearby:• Subway – 10M• McDonald’s – 12M• US Army Recruiting – 16M• Fiesta Grill – 18M• HR Block – 26M• Little Cesars Pizza – 34M• Advance Auto Part – 62M• …• ...

So How Is Better Accuracy Achieved?


ShapeFilesMultiple Pulls

Other Sensors Location Context User History

Opportunities With The Data


Insights


Goal: Use behavioral data to find the opportunities that drive the business.

How: 1) Panel of users who share GPS & Sensor data

2) Intelligence firm matches raw data with POI to create a history of location visits. Further context is added.

3) Intelligence firm aggregates data across users.

4) Data Analyst analyze underlying data to answer specific questions or to do an open-ended exploration

Example


Compared to Starbucks

Vs.

Planning


Goal: Use behavioral data to plan and optimize campaign tactics

How: 1) Panel of users who share GPS & Sensor data

2) Intelligence firm matches raw data with POI to create a history of location visits. Further context is added.

3) Intelligence firm aggregates data across users and provides DMA optimizations for the key levers

4) Agency takes national strategy and optimized recommendations to their publishers, who execute more efficient localized campaigns.

Example


True Trade Area

Optimal Day Parting Actual Competitive Set

Customer Base

Chipotle in Dallas, TX

60% of all trips

are less than

3 miles

Chipotle Traffic By Hour (Dallas)

Caucasian, 66%

Hispanic, 16%

Asian, 8%

Other, 3%

African American, 8%

Chipotle Customers By Ethnicity (Dallas)

7.3% Overlap

5.0 % Overlap

4.8% Overlap

Targeting


Goal: Use location to find in-the-moment audiences

How: 1) Ad Network looks for impressions on the ad exchanges or in their network that include a lat/long.

2) The lat/long is matched with a POI (using black-box magic).

3) If the POI represents a location of interest, the network bids on the impression and shows an ad.-------------------------------------------------------------------------------------------------

Goal: Use location to find audiences based on past behavior

How: 4) The POI is assigned to the user’s profile5) Users with past visits matching audience criteria are targeted with ads, regardless of current location

Measurement


Goal: Understand if a marketing activity drove lift

How: Several Methodologies

1) Panel is cross-checked for users who were exposed to an ad. Their store visits are tracked and compared a control group to determine lift. (Example: Placed)

2) Network shows an impression and stores UserID. Scans exchanges for location-data implying that user went into a store of interest. (Example: PlaceIQ)

3) Panel is used to determine a baseline visitation rate and are monitored before and after marketing event to determine lift. (Example: Sense360).

Example


Chick-Fil-A: Cow Appreciation DayJuly 12, 2016

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

0.0%5.0%

10.0%15.0%20.0%25.0%30.0%35.0%40.0%

QSR Market Share

Chick-Fil-A Visits QSR Visits

What happened?

Chick-Fil-A New vs. Existing CustomersJuly 12th

Existing New

Call 310-845-6047 oremail me [email protected]

Eli Portnoy

Thank you!

mailto:[email protected]

Privacy By Design

Safeguards to keep users data safe.

Sense360 only works with location data collected with user consent.

Sensor data is never combined with PII data.

Pro-active obfuscation of data that can be used to reverse engineer who the person is

Reporting & Data shared is always anonymous and in aggregate


Marketing

2016 Place Conf: Location - It's about Who not Where -- Audiences & Attribution