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Building the Data-Driven Brand

      Digiday Data Marketing Summit
                Sam Yagan
       Co-Founder & CEO, OkCupid
      President, Match Media Group
          @samyagan, @okcupid
ABOUT OKCUPID


                2
OkCupid Background

• Leading online dating site,
  launched in 2004
• Exclusively organic growth
• 10,000,000+ registered
  users
• 500,000,000+ messages
  sent each year
• Acquired by Match.com


        Our brand has become synonymous with data.
        “The Google of online dating” – Boston Globe
                                                       3
4 Math Majors Started a Dating Site?

• Fundamental belief in data.
• Why do people date online?
• What kinds of data can we collect?




                                          4
The Three Uses of Data
• User experience (making better matches)
• Marketing (PR)
• Sales (targeting ads more effectively)



 The combination can build a powerful brand.



                                               5
Modeling the Offline Dating Decision Process




                                           6
A Unique View Into Consumers
• Sure, Amazon has deep purchase data
• And Facebook has deep social data
• Dating sites – and especially OkCupid – have
  –   Demographic data
  –   Psychographic data
  –   Lifestyle data
  –   Consumption data

            Whom would you share your most
                 personal info with?
                                                 7
What Are We Optimizing?
• What’s our definition of success?
  – A 3-way.
• Key elements:
  – Distribution of messages
  – Recipient’s interest in the message
  – Keeping reply rates high




                                          8
OKTRENDS --
HTTP://BLOG.OKCUPID.OCM

                          9
We have data. Now what?
• Goal: Use data to build our brand
  – Leverage our data
  – Create buzz
  – Engage authentically
• First we tried traditional PR
• Then we started blogging…



                                      10
Did It Work?
Launch of OkCupid’s
blog, OkTrends




                                 11
ABOUT MATCH MEDIA GROUP


                          12
Largest Group of Dating Sites
• Powerful combination
  of reach, depth, and
  data.
• Not only use data to
  target campaigns…
• But also to turn data
  into the campaign itself.




                                      13
DonQ’s Campaign Created Data




                           14
The Data on Singles




                  15
CASE STUDY:
A TOP-25 INTERNET RETAILER

                             16
The Retailer’s Core Customer
• Female
• Between 25 – 45 years old
• In these zip codes:




                                   17
Ok, Cupid?
• This retailer had many data sources
  – Ad agency
  – Customer surveys
  – Focus groups
  – Market research


• We analyzed the 490,439 active OkCupid
  members that fit these criteria.

                                           18
How She Describes Herself:




                         19
Her Male Counterpart




                   20
What’s Top of Mind: Age
• 25-45 is pretty broad!
• Retailer especially interested in older women
• So we explored the impact of age




                                                  21
Her Preferences by Age




                     22
His Preferences by age




                     23
Women Seeking Men




                24
Men Seeking (Younger) Women




                          25
Men Seeking (Older) Women




                        26
Attractiveness is Exponential




                            27
She is More Positive




                   28
She’s Also More Sex-Positive




                           29
Age vs. Attractiveness: Who Wins?
250x


200x


150x


100x


 50x


  0x
       1.0 1.2 1.4 1.6 1.82.0 2.22.4 2.62.8 3.03.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0
                                  attractiveness rating




                                                                                         30
Attractiveness Wins
                Interest from Males by Attractiveness Quartiles
14


12


10


 8
                                                                                                                        top quartile
 6                                                                                                                      2nd quartile
                                                                                                                        3rd quartile
 4                                                                                                                      bottom quartile


 2


 0
     23   24   25   26   27   28   29   30   31   32   33   34   35   36   37   38   39   40   41   42   43   44   45

                                                  the woman's age


                                                                                                                                       31
The Older Mass Retail Shopper
• She is competing (for men, possibly jobs) with women
  much, much younger than herself.
• Perhaps counter-intuitively, she is much more confident than
  her younger competition.
• She has two weapons: her attitude & her looks.
• This should influence communication and merchandising.




                                                                 32
HUMAN NATURE


               33
Do You Spend More $ on Clothes or Food?




                                      34
iPhone “Autobiography”




                     35
Android “Autobiography”




                      36
Blackberry “Autobiography”




                         37
“We just paid a market research
  firm $250k to tell us that.”




                                  38
Men’s Ratings of Women’s Looks
6%

5%

4%

3%

2%

1%

0%
     1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0




                                                                                                                                                             39
Men’s Messaging to Women
6%



5%



4%



3%



2%



1%



0%
     1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0




                                                                                                                                                             40
Women’s Ratings of Men’s Looks
8%


7%


6%


5%


4%


3%


2%


1%


0%
     1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0




                                                                                                                                                             41
Women’s Messaging to Men
8%


7%


6%


5%


4%


3%


2%


1%


0%
     1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0




                                                                                                                                                             42
Is that an iPhone in Your Pocket…?




      43
DATING TIPS


              44
Say Something Interesting




                        45
Avoid the Superficial




                    46
Ladies: How to Dress for Success




                               47
A Typical First Date




                  48
Do My Date & I Have Long-Term Potential?
 1. Do you like horror movies?



 2. Have you ever traveled
    around a foreign
    country, alone?



 3. Wouldn’t it be fun to chuck
    it all and go live on a
    sailboat?

                                       49
What Else Can We Learn?
                   Men                              Women

1.   In a certain light, wouldn't   1.   Do you like the taste of beer?
     nuclear war be exciting?

2.   Assuming you were in the
     position to do so, would you
     launch nuclear weapons under
     any circumstances?

3.   Could you imagine yourself
     killing someone?


          Will You Have Sex on the First Date?
                                                                          50
51
Building the Data-Driven Brand

      Digiday Data Marketing Summit
                Sam Yagan
       Co-Founder & CEO, OkCupid
      President, Match Media Group
          @samyagan, @okcupid

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DMS: OkCupid: Building the Data-Driven Brand

  • 1. Building the Data-Driven Brand Digiday Data Marketing Summit Sam Yagan Co-Founder & CEO, OkCupid President, Match Media Group @samyagan, @okcupid
  • 3. OkCupid Background • Leading online dating site, launched in 2004 • Exclusively organic growth • 10,000,000+ registered users • 500,000,000+ messages sent each year • Acquired by Match.com Our brand has become synonymous with data. “The Google of online dating” – Boston Globe 3
  • 4. 4 Math Majors Started a Dating Site? • Fundamental belief in data. • Why do people date online? • What kinds of data can we collect? 4
  • 5. The Three Uses of Data • User experience (making better matches) • Marketing (PR) • Sales (targeting ads more effectively) The combination can build a powerful brand. 5
  • 6. Modeling the Offline Dating Decision Process 6
  • 7. A Unique View Into Consumers • Sure, Amazon has deep purchase data • And Facebook has deep social data • Dating sites – and especially OkCupid – have – Demographic data – Psychographic data – Lifestyle data – Consumption data Whom would you share your most personal info with? 7
  • 8. What Are We Optimizing? • What’s our definition of success? – A 3-way. • Key elements: – Distribution of messages – Recipient’s interest in the message – Keeping reply rates high 8
  • 10. We have data. Now what? • Goal: Use data to build our brand – Leverage our data – Create buzz – Engage authentically • First we tried traditional PR • Then we started blogging… 10
  • 11. Did It Work? Launch of OkCupid’s blog, OkTrends 11
  • 12. ABOUT MATCH MEDIA GROUP 12
  • 13. Largest Group of Dating Sites • Powerful combination of reach, depth, and data. • Not only use data to target campaigns… • But also to turn data into the campaign itself. 13
  • 15. The Data on Singles 15
  • 16. CASE STUDY: A TOP-25 INTERNET RETAILER 16
  • 17. The Retailer’s Core Customer • Female • Between 25 – 45 years old • In these zip codes: 17
  • 18. Ok, Cupid? • This retailer had many data sources – Ad agency – Customer surveys – Focus groups – Market research • We analyzed the 490,439 active OkCupid members that fit these criteria. 18
  • 19. How She Describes Herself: 19
  • 21. What’s Top of Mind: Age • 25-45 is pretty broad! • Retailer especially interested in older women • So we explored the impact of age 21
  • 28. She is More Positive 28
  • 29. She’s Also More Sex-Positive 29
  • 30. Age vs. Attractiveness: Who Wins? 250x 200x 150x 100x 50x 0x 1.0 1.2 1.4 1.6 1.82.0 2.22.4 2.62.8 3.03.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 attractiveness rating 30
  • 31. Attractiveness Wins Interest from Males by Attractiveness Quartiles 14 12 10 8 top quartile 6 2nd quartile 3rd quartile 4 bottom quartile 2 0 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 the woman's age 31
  • 32. The Older Mass Retail Shopper • She is competing (for men, possibly jobs) with women much, much younger than herself. • Perhaps counter-intuitively, she is much more confident than her younger competition. • She has two weapons: her attitude & her looks. • This should influence communication and merchandising. 32
  • 34. Do You Spend More $ on Clothes or Food? 34
  • 38. “We just paid a market research firm $250k to tell us that.” 38
  • 39. Men’s Ratings of Women’s Looks 6% 5% 4% 3% 2% 1% 0% 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0 39
  • 40. Men’s Messaging to Women 6% 5% 4% 3% 2% 1% 0% 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0 40
  • 41. Women’s Ratings of Men’s Looks 8% 7% 6% 5% 4% 3% 2% 1% 0% 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0 41
  • 42. Women’s Messaging to Men 8% 7% 6% 5% 4% 3% 2% 1% 0% 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0 42
  • 43. Is that an iPhone in Your Pocket…? 43
  • 47. Ladies: How to Dress for Success 47
  • 48. A Typical First Date 48
  • 49. Do My Date & I Have Long-Term Potential? 1. Do you like horror movies? 2. Have you ever traveled around a foreign country, alone? 3. Wouldn’t it be fun to chuck it all and go live on a sailboat? 49
  • 50. What Else Can We Learn? Men Women 1. In a certain light, wouldn't 1. Do you like the taste of beer? nuclear war be exciting? 2. Assuming you were in the position to do so, would you launch nuclear weapons under any circumstances? 3. Could you imagine yourself killing someone? Will You Have Sex on the First Date? 50
  • 51. 51
  • 52. Building the Data-Driven Brand Digiday Data Marketing Summit Sam Yagan Co-Founder & CEO, OkCupid President, Match Media Group @samyagan, @okcupid