12. @THCapper
Link building KPIs Link building objectives
LRDs
# of Links
# of Links over x DA
# of dofollow / non
syndicate links
DA
Rankings(in order to achieve…)
13. @THCapper
Link building KPIs Link building objectives
LRDs
# of Links
# of Links over x DA
# of dofollow / non
syndicate links
DA
Rankings(in order to achieve…)
Traffic(in order to achieve…)
14. @THCapper
Link building KPIs Link building objectives
LRDs
# of Links
# of Links over x DA
# of dofollow / non
syndicate links
DA
Rankings(in order to achieve…)
Traffic(in order to achieve…)
Revenue
15. @THCapper
Link building KPIs
Rankings(in order to achieve…)
Traffic(in order to achieve…)
Revenue
Link building objectives
LRDs
# of Links
# of Links over x DA
# of dofollow / non
syndicate links
DA
?=
37. @THCapper
Ancient history
People navigatee the web with
links
Links, therefore, were a proxy
for popularity
This is Google’s main insight &
why they won*
*gross oversimplification
52. @THCapper
PageRank
A
Imagine this is the internet.
What is the probability a random browser is on this page?
= 1/n
Where n is the number of
pages on the internet.
65. @THCapper
Link building KPIs
LRDs
# of Links
# of Links over x DA
# of dofollow / non
syndicate links
DA
Features of PageRank
Proxy for traffic
Domain agnostic
Sensitive to obscurity of
linking page
Sensitive to number of
links
80. @THCapper
Outcome metrics (e.g. rankings, revenue)
− Causation vs
correlation
− Effect of individual
link lost in noise
+ Obvious commercial
relevance
117. @THCapper
2. Measure in phases
Fast | Slow
Actual
Indicative
DA
Spam Score
PA
Reach
Referral Traffic
Rankings
Prospecting Reporting Post Mortem
# of links
121. @THCapper
4. Learn from concrete metrics
Fast | Slow
Actual
Indicative
DA
Spam Score
PA
Reach
Referral Traffic
Rankings
Prospecting Reporting Post Mortem
# of links
122. @THCapper
4. Learn from concrete metrics
Fast | Slow
Actual
Indicative
Referral Traffic
Rankings
Prospecting Reporting Post Mortem