The document discusses how consumer data is changing from the past era of disconnected surveys and ratings to the current landscape where individuals generate and share vast amounts of passive, behavioral, and social data through their online and mobile activities. It describes how this data, if consumers opt-in and companies handle it responsibly, can be used to provide more personalized and satisfying experiences for consumers through relevant recommendations, offers, and rewards tailored to their interests and behaviors.

1. Consumer Data:
Can I get satisfaction?
Rick Orr
Founder, Tabbedout
@orrrick

2. What I Do
 Founder of Tabbedout (Austin)
 Mobile payment for bars &
restaurants
 Available at >1100 locations in
48 states
 Integrated with 75% of POS
(Micros, Aloha, etc.)

3. Changing Landscape of Data
The Mad Men Era - Nielsen ratings, surveys
and disconnected loyalty programs that
governed how brands & merchants
marketed to consumers
Times are a changin’ – What we share, what
others can see and how we are marketed
to is transforming at a break-neck pace

4. Passive Data
Everyone is generating data
 Phone carriers know your patterns
 Searching, tagging and pinning
 Twitter pipe

5. Behavioral Data
Everyone is doing
 Online & on-premise engagement
 Online / mobile payments & loyalty
 Check-ins & passbook passes

6. Social Graph Data
Everyone is sharing
 ‘Allow’ apps (FB, LinkedIn, 4sq, etc.)
 Geo-tracking (tags, posts, check-ins)
 Interests (likes, pins, comments, reviews)

7. You Generate A Lot of Data
…but today it’s largely disjointed
Passive
Behavioral
Social

8. What About Privacy & Security?
 Always provide the option to opt-in
 Only opt-in to companies you trust –
checkout privacy policy
 Be mindful of who has your most sensitive
data – financial, identity (SSN), etc.

9. Data Can Bring You Satisfaction
 Brands and merchants will invest in you the
more they know about you
 Relevant savings and rewards for what you
actually like
 Geographically relevant offers when you
actually want them

11. What the World Sees
Height: 5’9 8” | Weight: 178 lbs
Eyes: Brown | Hair: Brown
Race: White | Age: 35
City: Austin, TX | Occupation: Software

12. Most Likely Superhero Name

13. Quiz Show
Free Beer if You Get All 3 Correct

14. Audience Quiz:
Which brand should focus on me today?
A)
B)
C)

15. Audience Quiz:
Which type beer do I drink ~75% of my tabs?
A)
B)
C)

16. Audience Quiz:
On a Wednesday in November what do I eat?
A)
B)
C)

17. What I Share

18. What I Share
{ “orrrick” :
{
“social” : [
{
“source” : “Instagram”,
“date” : “03/07/13 20:41:04”,
“hashtag” : “Ford”,
},
{ “source” : “LinkedIn”,
“date” : “03/07/13 22:21:34”,
“article” : “IBM”,
},
{ “source” : “Spotify”,
“date” : “03/10/13 07:21:34”,
“artist” : “Wilco”,
},
{ “source” : “Twitter”,
“date” : “03/08/13 20:45:35”,
“product” : “Beer”,
“type” : “IPA”,
}
]
}
}

19. Polvo’s Mexican Restaurant

20. Polvo’s Data
{ “orrrick” :
{
“behavioral” : [
{
“source” : “Tabbedout”,
“date” : “11/21/12 20:41:14”,
“food” : “Fajitas”,
“type” : “Chicken”,
“drink” : “Mexican Martini”,
“category” : “Premium Tequila”,
“tip” : “$5.00”,
“price” : “$26.14”,
}
]
}
}

21. Torchy’s Tacos

22. Torchy’s Data
{ “orrrick” :
{
“behavioral” : [
{
“source” : “Torchys”,
“date” : “03/09/13 08:11:24”,
“auth” : “Facebook Connect”,
“food” : “Tacos”,
“type” : “Breakfast”,
“tip” : “$5.00”,
“price” : “$16.14”,
}
]
}
}

23. My Cleaners

24. Dry Cleaner Data
{ “orrrick” :
{
“behavioral” : [
{
“source” : “Capitol Cleaners”,
“date” : “03/09/13 08:01:24”,
“items” : “Shirts”,
“quantity” : “5”,
“price” : “$21.13”,
}
]
}
}

25. Starbucks

26. Ooops!
Geographically
relevant and
timely marketing
Way off the mark
– wasted
impression

27. Torchy’s Data
{ “orrrick” :
{
“behavioral” : [
{
“source” : “Starbucks Congress Ave”,
“date” : “03/09/13 09:21:12”,
“drink” : “Coffee”,
“size” : “Grande”,
“price” : “$3.25”,
}
]
}
}

28. West 6th’s View of Me

29. Happy Hour Data
{ “orrrick” :
{
“behavioral” : [
{
“date: : “10/09/12 20:11:11”,
“venue” : “Brew Exchange”,
“beer” : “Lagunitas IPA”,
“price” : “$4.00”,
}
.
.
.
.
]
}
}

30. Audience Quiz:
Which brand should focus on me today?
A)
B)
C)

31. Audience Quiz:
Which type beer do I drink ~75% of my tabs?
A)
B)
C)

32. Audience Quiz:
On a Wednesday in November what do I eat?
A)
B)
C)

33. Future, Data Aggregation:
Steve Watt – Big Data Strategy, CTO Office at Red Hat

34. You Stay ‘Glassy’ Planet Earth
5:22 PM
ALERT for DOGWOOD
Fireman’s 4 Special - $2 off
AYC Happy hour in 8 minutes
Playing - ‘Shot in the Arm’ by Wilco
Based on
Tabbedout, onTap, Calendar, Eventbrite, Spotify

35. Summary
 You are sharing already, will you opt-in?
 Companies handling consumer data must
behave responsibly
- Securely stored
- Sanitized and anonymized
 Data can yield greater customer satisfaction
- ‘Genius’-like recommendations
- Contextual deals
- Free Beer!

36. Thank You