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Online Marketing under Pressure
   How to work smarter, not harder in
        Free2Play online games
Structure

•   Who is Oliver Kern
•   Why is Online Marketing under pressure
•   What is big data
•   How can this help
•   How can I apply this to my small data




2
Who is Oliver Kern?




    http://bit.ly/oliverkern
3
Why is Online Marketing under pressure?

                  2011      vs. 2010                 2011     vs. 2010
                             revenues                          revenues

      $ 2,571,000,000           +3%       € 473,000,000          +13%
     P2P              F2P               P2P             F2P

           53%   47%                          42%   58%


                             players                           players

           39,400,000           +3%           8,700,000          +11%
                             payers                            payers

           22,300,000           +6%           4,500,000          +13%
                            $ / month                         € / month

             $ 9.61              -3%           € 8.76             +1%

            2011 vs 2010                  2011 vs 2010
            F2P spending                  F2P spending
                +24%                          +14%
                                                                          © NewZoo, 2011




4
Why is Online Marketing under pressure?
Why is Online Marketing under pressure?




6
Why is Online Marketing under pressure?

Until today…

• It’s becoming more and more challenging to
  find affordable traffic sources
• Data has not (really) worked for you
• You have been focussing on key traffic sources
  and tried to optimize the ROI


7
Why is Online Marketing under pressure?

What to do?

1. Get a deep understanding of your user types

2. Use the benefits of online advertising

3. Diversify channel mix


8
In the world of marketing, targeting is king.

 And in the world of targeting, data rules!



 9
What is big data?

In IT, big data consists of datasets that grow so
large that they become awkward to work with
on-hand/manual data management tools.

Difficulties include capture, storage, search,
sharing, analytics, and visualizing




10
What is big data?

     Data Infrastructure                                      Insights & Analysis
                                                               Media Performance
                                Gamer iQU                      Audience Insight
          1st   Party Data                                     Audience Forecasting
                             Data Management
                                 Platform
     - Behavioral Data
     - Conversion Events
     - Appended Data                                             Decisioning
                                     Rules Engine
                                   Segment Builder             Ad Optimization
                                Predictive Optimization
                                                               LP Optimization
          3rd Party Data
                             Secure and Private Environment
                                                               Media Optimization
      - Numerous 3rd party
                                                               Bidding Optimization
        data relationships




11
So how



     can   big data
             help?



12
In the World of targeting, data rules

          This is Mae Santos,
          she is Australian, lives in the Netherlands and
          loves playing Thirst of Night (kabam).

          Thirst of Night (MMORTS)
          Target audience (2 properties): male, 18-38

          What did the ad look like that brought
          her into the game?




13
In the World of targeting, data rules



               She viewed the ad on yahoo.co.au from the Netherlands
               Her sign-up time was 1.1 minutes
               She completed tutorial in 6.8 minutes
               Her first payment was after 27 days
               …




14
If demographic- and geo-targeting are
 not good enough anymore….

 …how else do you build meaningful
 segments to target?


15
How to build meaningful segments
How to build meaningful segments
How to build meaningful segments
How to build meaningful segments
How to build meaningful segments
How to build meaningful segments
How to build meaningful segments
How to build meaningful segments
How to build meaningful segments
The look-a-like Strategy
I only have “small” data.
        Where can I start?




26
5 steps to improve targeting
Step 1: Create ads for 4 Segments plus a control group (broad appeal)




                               Control Group
5 steps to improve targeting
Step 2: Verify Segments




28
5 steps to improve targeting
Step 3: Track behavior

advert        CPM     CTR       registration-rate return-rate   CPRU     CPPU*
Killer1         $2,50     0,33%            17,95%     32,14%      $13,13       $87,54
control1        $2,50     0,42%            14,05%     20,03%      $21,15      $141,01

Achiever1       $2,50     0,65%           12,80%      44,90%       $6,74       $44,96
control1        $2,50     0,42%           14,05%      20,03%      $21,15      $141,01

Explorer1       $2,50     0,20%           18,65%      18,18%      $37,81      $252,08
control1        $2,50     0,42%           14,05%      20,03%      $21,15      $141,01

Socializer1     $2,50     0,17%           19,25%      14,17%      $55,55      $370,31
control1        $2,50     0,42%           14,05%      20,03%      $21,15      $141,01

*CPPU calculated with 15% conversion from active user


29
5 steps to improve targeting
Step 4: Evaluate Segments




                            1.61       3.13

                                   1

                            0.38       0.56




30
5 steps to improve targeting
Step 5: Find look-a-like media




                                 13% registration rate
                                 45% return rate
                                 15% customer rate*




                                 18% registration rate
                                 32% return rate
                                 15% customer rate*


31
What to do?

1. Get a deep understanding of your user types
     (who is playing and how do they behave)
2. Use the benefits of online advertising
     (target and measure)
3. Diversify channel mix
     (find appropriate targets across all archetypes)

32
Thank You!

E: oliver.kern@iqu.com
T: @freewebgames




33

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Casual Connect iQU.com

  • 1. Online Marketing under Pressure How to work smarter, not harder in Free2Play online games
  • 2. Structure • Who is Oliver Kern • Why is Online Marketing under pressure • What is big data • How can this help • How can I apply this to my small data 2
  • 3. Who is Oliver Kern? http://bit.ly/oliverkern 3
  • 4. Why is Online Marketing under pressure? 2011 vs. 2010 2011 vs. 2010 revenues revenues $ 2,571,000,000 +3% € 473,000,000 +13% P2P F2P P2P F2P 53% 47% 42% 58% players players 39,400,000 +3% 8,700,000 +11% payers payers 22,300,000 +6% 4,500,000 +13% $ / month € / month $ 9.61 -3% € 8.76 +1% 2011 vs 2010 2011 vs 2010 F2P spending F2P spending +24% +14% © NewZoo, 2011 4
  • 5. Why is Online Marketing under pressure?
  • 6. Why is Online Marketing under pressure? 6
  • 7. Why is Online Marketing under pressure? Until today… • It’s becoming more and more challenging to find affordable traffic sources • Data has not (really) worked for you • You have been focussing on key traffic sources and tried to optimize the ROI 7
  • 8. Why is Online Marketing under pressure? What to do? 1. Get a deep understanding of your user types 2. Use the benefits of online advertising 3. Diversify channel mix 8
  • 9. In the world of marketing, targeting is king. And in the world of targeting, data rules! 9
  • 10. What is big data? In IT, big data consists of datasets that grow so large that they become awkward to work with on-hand/manual data management tools. Difficulties include capture, storage, search, sharing, analytics, and visualizing 10
  • 11. What is big data? Data Infrastructure Insights & Analysis Media Performance Gamer iQU Audience Insight 1st Party Data Audience Forecasting Data Management Platform - Behavioral Data - Conversion Events - Appended Data Decisioning Rules Engine Segment Builder Ad Optimization Predictive Optimization LP Optimization 3rd Party Data Secure and Private Environment Media Optimization - Numerous 3rd party Bidding Optimization data relationships 11
  • 12. So how can big data help? 12
  • 13. In the World of targeting, data rules This is Mae Santos, she is Australian, lives in the Netherlands and loves playing Thirst of Night (kabam). Thirst of Night (MMORTS) Target audience (2 properties): male, 18-38 What did the ad look like that brought her into the game? 13
  • 14. In the World of targeting, data rules She viewed the ad on yahoo.co.au from the Netherlands Her sign-up time was 1.1 minutes She completed tutorial in 6.8 minutes Her first payment was after 27 days … 14
  • 15. If demographic- and geo-targeting are not good enough anymore…. …how else do you build meaningful segments to target? 15
  • 16. How to build meaningful segments
  • 17. How to build meaningful segments
  • 18. How to build meaningful segments
  • 19. How to build meaningful segments
  • 20. How to build meaningful segments
  • 21. How to build meaningful segments
  • 22. How to build meaningful segments
  • 23. How to build meaningful segments
  • 24. How to build meaningful segments
  • 26. I only have “small” data. Where can I start? 26
  • 27. 5 steps to improve targeting Step 1: Create ads for 4 Segments plus a control group (broad appeal) Control Group
  • 28. 5 steps to improve targeting Step 2: Verify Segments 28
  • 29. 5 steps to improve targeting Step 3: Track behavior advert CPM CTR registration-rate return-rate CPRU CPPU* Killer1 $2,50 0,33% 17,95% 32,14% $13,13 $87,54 control1 $2,50 0,42% 14,05% 20,03% $21,15 $141,01 Achiever1 $2,50 0,65% 12,80% 44,90% $6,74 $44,96 control1 $2,50 0,42% 14,05% 20,03% $21,15 $141,01 Explorer1 $2,50 0,20% 18,65% 18,18% $37,81 $252,08 control1 $2,50 0,42% 14,05% 20,03% $21,15 $141,01 Socializer1 $2,50 0,17% 19,25% 14,17% $55,55 $370,31 control1 $2,50 0,42% 14,05% 20,03% $21,15 $141,01 *CPPU calculated with 15% conversion from active user 29
  • 30. 5 steps to improve targeting Step 4: Evaluate Segments 1.61 3.13 1 0.38 0.56 30
  • 31. 5 steps to improve targeting Step 5: Find look-a-like media 13% registration rate 45% return rate 15% customer rate* 18% registration rate 32% return rate 15% customer rate* 31
  • 32. What to do? 1. Get a deep understanding of your user types (who is playing and how do they behave) 2. Use the benefits of online advertising (target and measure) 3. Diversify channel mix (find appropriate targets across all archetypes) 32