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Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
Optimising the Facebook Stack for Earned Media
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Optimising the Facebook Stack for Earned Media

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  • 1. Optimising the Facebook StackMat MorrisonThursday October 6, 2011Draft for Chinwag Insight: Facebook Marketing
  • 2. How people use Facebook Ignore,   Login  to   View   Leave   Like  or   Facebook   Newsfeed   Facebook   Comment   1
  • 3. How people use a Facebook Page (Client 1) ∑uwd e e e edges e EdgeRank See  Brand   See/Don’t   Ignore,   Post  in   See   Like  Page   Like  or   News   Future   Comment   Feed   Posts   Like source First exposure Responders Ongoing Exposure 0.6% 11% 36% 99% 0.6% attributed to Estimate Comments + Likes DAU “on Page” Likes Total Fans DAU 2
  • 4. How people use a Facebook Page (Client 2) ∑uwd e e e edges e EdgeRank See  Brand   See/Don’t   Ignore,   Post  in   See   Like  Page   Like  or   News   Future   Comment   Feed   Posts   Like source First exposure Responders Ongoing Exposure 1.4% 21% 60% 99% 60% in-Ad unit Estimate Comments + Likes DAU 0.5% attributed to Total Fans DAU 3 “on Page” Likes
  • 5. Most people don’t visit the Page (Client 1) All Fans 100% 470K MAU 53% 250K DAU 11% 52K Daily Page Visits (Unique) 0.3% 1.4K 4
  • 6. Most people don’t visit the Page (Client 2) All Fans 100% 56.7K MAU 99.7% 56.4K DAU 21.3% 12K Daily Page Visits (Unique) 2.1% 1.2K 5
  • 7. Response Windows (Client 1) 50%   •  80% of responses within 3 hours. 91.4%   •  90% within 6 hours 40%   30%   20%   10%   0%   0   6   12   18   24   30   36   42   48   Elapsed  Hours   %age  responses   cumulaNve   6
  • 8. Response Windows (Client 2) 35% •  70% of response within 3 hours •  85% within 6 hours 30% 25% 84% 20% 69% 15% 10% 5% 0% 0 6 12 18 24 30 36 42 48 % response cumulative 7
  • 9. Activity by hour and day (Client 2) Posts by hour Posts by day 50 60 45 40 50 35 40 30 25 30 20 15 20 10 10 5 - 0 0 6 12 18 Mon Thu Sun 8
  • 10. How fan growth Affects Daily Active Users (Client 1) 90 600 11.60 Thousands Thousands 80 11.40 500 11.20 70 y = 1.6541x - 10.598 11.00 R² = 0.59878 60 400 10.80 ln(DAU) 50 DAU Fans 300 10.60 40 10.40 30 200 10.20 20 100 10.00 10 9.80 12.50 12.60 12.70 12.80 12.90 13.00 13.10 13.20 0 0 ln(Fans) Feb Mar Apr May Jun Jul Aug 1% increase in fans leads to 1.65% increase in DAU 9 (0.35% increase in MAU)
  • 11. ImpacT of PosT FreqUency 10
  • 12. What’s the impact of Post Frequency? Count of Post Frequency Weekly Post Frequency Trend 25   90 40% 80 20   70 60 27% 15   50 23% 40 10   30 20 7% 5   10 3% 0 0 1 2 3 4 0   Posts Per Day Feb   Mar   Apr   May   Jun   Jul   Aug  
  • 13. Impressions grow strongly inline with post frequency 3500 15.5 Thousands y = 1.108x + 11.63 21 15 3000 R² = 0.94383 14.5 2500 17 17 14 ln(7-day rolling imps) 2000 13.5 12 1500 13 12.5 1000 4 12 500 11.5 0 11 Jan Feb Mar Apr May Jun Jul 0 0.5 1 1.5 2 2.5 3 3.5 7-day rolling imps 7-day rolling posts ln(7-day rolling posts) 12
  • 14. Reach grows with post frequency 25%   -1.4 -1.6 20%   y = 0.4005x - 2.3461 -1.8 R² = 0.5301 15%   -2 ln(reach) 10%   -2.2 -2.4 5%   -2.6 0%   -2.8 Posts   Reach   0 0.5 ln(posts) 1 1.5 13
  • 15. ..while unsubscribes increase 250 7.5 y = 0.4594x + 5.5239 R² = 0.57793 200 7 ln(7-day rolling unsubs) 150 6.5 100 6 5.5 50 5 0 0 0.5 1 1.5 2 2.5 3 3.5 Posts Daily Unsubs ln(7-day rolling posts) 14
  • 16. ImpacT of Fan GroWTh 15
  • 17. Active Users increase with fan growth: Daily Reacharound 20% (Client 2) DAU  vs  Fan  Growth   Fan  Reach  vs  Fan  Growth   20000   60%   70,899 70,899 18000   50%   16000   14000   51,508 51,508 40%   12000   Reach   DAU   10000   30%   8000   20%   6000   19,857 19,857 4000   10%   2000   2,051 2,051 0   0%   Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   DAU   Fans   reach   Fans   16
  • 18. Unsubscribes grow strongly in line with active users(Client 2) 700   7 y = 1.0593x - 5.1934 600   6 R² = 0.93978 500   5 400   Ln(Unsubs) 4 300   3 200   2 100   1 0   0 Jan   Feb   Mar   Apr   May   5 6 7 8 9 10 11 12 7-­‐day  Unsubs   WAU   ln(WAU) 17
  • 19. So unsubscribes grow strongly inline with fan growth(Client 1) 250   5.5 y = 2.2197x - 24.016 R² = 0.50316 467,512 5 200   4.5 ln(unsubscribes) 150   288,631 4 100   3.5 50   3 0   2.5 Feb   Mar   Apr   May   Jun   Jul   Aug   12.5 12.6 12.7 12.8 12.9 13 13.1 13.2 Daily  Unlikes   Fans   ln(fans) 18

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