2. Sense Networks Overview
• Founded in 2006 by world-class MIT and Columbia
Computer Scientists interested in understanding human
behavior through location information
• Proprietary technology and deep expertise in geospatial and
temporal analysis to deliver unique insights, trends and
intelligence based on behavior patterns
• Team of 16, based in New York and San Francisco, funded
by Intel Capital and Javelin Ventures
World’s Most Intriguing 2009 Excellence Award 2009 Cool Vendor 2009 Company to 2009 AlwaysOn
Startups Watch Award Award
2
3. Location-Based Services and Mobile Advertising: For Years,
Focused on Simple Proximity-based Coupons
• Maybe some context like the weather or day of week
• No personalization – ads based either on opt-in lists from
retailers or mass marketing
=>
3 Proprietary & Confidential
4. A Better Way: Use The Best Context Available – Current and
Historical Location Information
• Existing targeting: context from mobile content consumption
• What about location history? Best predictor of behavior and
how we interact with the real world
4 Proprietary & Confidential
5. Location History Can Drive Much Better Recommendations and
Mobile Advertisements
Segment:
Health & Fitness
=>
Young Adult
Outdoorsy
. . . A Different Ad
Location History: Parks
and Recreational Areas
+
Current Context:
Location, Weather,
Time-of-Day, User
“Mode” (e.g. shopping
or commuting)
=
5 Proprietary & Confidential
6. Sense Networks Has Built a High-Capacity Platform for
Extracting Intelligence From Location Data and Summarizing It
MacroSense Software Platform
Information Output
Data Reduction
Input Locations
Segmentation
Extract Info
Normalize
Prediction
Clean and
We can extract Proprietary
thousands of location algorithms to
“features” from tens of summarize all
millions of users and this information
tens of millions of more efficiently
points-of-interest (“jpeg for data”)
6 Proprietary & Confidential
7. Example: A Mobile User’s Location Data and Call Activity Can
Be Abstracted to Commercial, Advertising Exposure . . .
Flow Call Activity Demographics, Commercial,
Ad Exposure
Week FLO FLO … FLO2 SIC SIC … SIC DEM DEM … DEM
Hour 1 2 0 1 2 97 1 2 78
1 .03 .31 .14 .03 .05 .41 .11 .04 .01
2 .14 .34 .02 .04 .05 .52 .01 .01 .00
…
168 .07 .34 .51 .02 .06 .48 .02 .01 .00
7 Proprietary & Confidential
8. . . . And Compacted Into A “Location DNA” for Each User . . .
DNA User 1 DNA User 2
Time of Day, Day of Week
Category of Commercial Exposure Category of Commercial Exposure
(i.e. restaurants, schools, golf (i.e. restaurants, schools, golf
courses) courses)
8 Proprietary & Confidential
9. . . . To Create Segments – All From Anonymous Location Data
Nightlife Profiles, Primary Clusters
How often do they go out each
day of the week?
Where do they hang out?
What is the avg age of most
people in the neighborhoods
they spend time in?
How racially diverse are the
neighborhoods they spend
time in?
Are the places they spend
time in rich neighborhoods
or poor neighborhoods?
“Young & Edgy”
•Out every night in young,
racially diverse, low income
neighborhoods
“Weekend Mole” “Mature Homebody”
•Out occasionally on •Rarely goes out, typically
weeknights, typically middle- spends nights in mature,
aged, Latino, middle-income white, higher income
neighborhoods neighborhoods
9 9 Proprietary & Confidential
10. Location-Based Segments Proven to Drive User Behavior
• Example: Using data from a mobile location app, we predicted
new places that users would go based on their “tribe”
• If we gave users 500 recommendations, 20% were acted on
User Response To Sense’s Top Recommendations
20%
15%
10% 20% Sense Networks
Baseline
5%
8%
5% 0% 1% 4%
0%
50 100 500
We examined 30k users and 5k points of interest. If users were presented with 50, 100, or 500 place recommendations they had not previously visited, what % of those
would they visit and check in? For 100 Sense recommendations, 8% were acted upon by users. For 500 Sense recommendations, 20% were acted upon.
10 Proprietary & Confidential
11. Contact Info
1123 Broadway (between 25th and 26th Streets)
Suite 817
New York, NY 10010
+1 646 758 6227
Mikki Nasch, EVP Business Development: mikki@sensenetworks.com, +1 646-845-9859
Christine Lemke, COO: christine@sensenworks.com, +1 917-284-8384
David Petersen, CEO: david@sensenetworks.com, +1 415-336-3948
11 Proprietary & Confidential
