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