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Online PR Show Spring 2022 Measuring Link Building You're Doing it Wrong-2.pdf
The document discusses how link building metrics are often measured incorrectly by focusing too much on domain-level metrics like domain authority rather than page-level metrics or actual outcomes. It recommends focusing on the underlying mechanism of PageRank by considering the quality and number of incoming links, measuring links in phases from initial prospects to long-term outcomes, and prioritizing concrete metrics like referral traffic and rankings over domain-level proxies. This will provide a more accurate picture of how individual links contribute to search performance.
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Online PR Show Spring 2022 Measuring Link Building You're Doing it Wrong-2.pdf
- 1. Measuring Link Building: You’reDoing It Wrong Tom Capper Moz @THCapper
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- 11. @THCapper @THCapper Agenda Why we buildlinks Why we use these metrics
- 12. @THCapper @THCapper Agenda Why we buildlinks Why we use these metrics Better measurement
- 13. @THCapper @THCapper Agenda Why we buildlinks Why we use these metrics Better measurement What to do next
- 14. @THCapper @THCapper Agenda Why we buildlinks Why we use these metrics Better measurement What to do next
- 15. @THCapper @THCapper Hold that thought &imagine it’s 1998
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- 17. @THCapper Ancient history People navigatedthe web with links
- 18. @THCapper Ancient history People navigatedthe web with links Links, therefore, were a proxy for popularity
- 19. @THCapper Ancient history People navigatedthe web with links Links, therefore, were a proxy for popularity This is Google’s main insight & why they won
- 20. @THCapper Ancient history People navigatedthe web with links Links, therefore, were a proxy for popularity This is Google’s main insight & why they won* *gross oversimplification
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- 23. @THCapper Is it stilltrue? We still use links, but they’re on SERPs and feeds
- 24. @THCapper Is it stilltrue? We still use links, but they’re on SERPs and feeds Google has better data on popularity anyway
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- 26. @THCapper Doesn’t matter Core methodologystill underpins how Google works
- 27. @THCapper Doesn’t matter Core methodologystill underpins how Google works Albeit more nuanced
- 28. @THCapper Doesn’t matter Core methodologystill underpins how Google works Albeit more nuanced Albeit with more layers on top
- 29. @THCapper AKA Link equity 🙂 Linkflow 🙁 Link juice 🤮 Linking strength 🤔
- 30. @THCapper @THCapper So how doesit work?
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- 32. @THCapper @THCapper A proxy forpopularity
- 33. @THCapper PageRank A Imagine this isthe internet.
- 34. @THCapper PageRank A Imagine this isthe internet. What is the probability a random browser is on this page?
- 35. @THCapper PageRank A Imagine this isthe internet. What is the probability a random browser is on this page? = 1/n Where n is the number of pages on the web.
- 36. @THCapper PageRank A 0.85*A For thatvalue of A: What about the one page it links to?
- 37. @THCapper PageRank A 0.85*A For thatvalue of A: What about the one page it links to? 0.15*A
- 38. @THCapper PageRank A 0.85*A For thatvalue of 0.85*A: What if A links to two pages?
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- 41. @THCapper Key features ofPageRank Domain agnostic
- 42. @THCapper Key features ofPageRank Domain agnostic Sensitive to obscurity of linking page
- 43. @THCapper Key features ofPageRank Domain agnostic Sensitive to obscurity of linking page Sensitive to number of links
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- 48. @THCapper Link building KPIs LRDs #of Links # of Links over x DA
- 49. @THCapper Link building KPIs LRDs #of Links # of Links over x DA # of dofollow / non syndicate links
- 50. @THCapper Link building KPIs LRDs #of Links # of Links over x DA # of dofollow / non syndicate links DA
- 51. @THCapper Link building KPIs LRDs #of Links # of Links over x DA # of dofollow / non syndicate links DA Features of PageRank Domain agnostic Sensitive to obscurity of linking page Sensitive to number of links
- 52. @THCapper @THCapper Takeaway 1: Focus onthe Mechanism
- 53. @THCapper @THCapper Takeaway 1: Focus onthe Mechanism Aka caring about the linking page, not just the linking site
- 54. @THCapper @THCapper Agenda Why we buildlinks Why we use these metrics Better measurement What to do next
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- 56. @THCapper Domain level metrics(e.g. DA)
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- 58. @THCapper Domain level metrics(e.g. DA) All things being equal, how well will a page on this domain rank? “ ”
- 59. @THCapper Domain level metrics(e.g. DA) − PAGErank − Indifferent to link specifics − Wrong question
- 60. @THCapper Domain level metrics(e.g. DA) − PAGErank − Indifferent to link specifics − Wrong question + Available beforehand + Google ambiguity + Trained on rankings + Universally understood
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- 62. @THCapper Top party games2022 Spin the bottle
- 63. @THCapper Top party games2022 Spin the bottle Truth or dare
- 64. @THCapper Top party games2022 Spin the bottle Truth or dare Guess the DA
- 65. @THCapper Domain level metrics(e.g. DA) − PAGErank − Indifferent to link specifics − Wrong question + Available beforehand + Google ambiguity + Trained on rankings + Universally understood
- 66. @THCapper Page level metrics(e.g. PA)
- 67. @THCapper Page level metrics(e.g. PA) − Wait for page to be crawled − Somewhat domain sensitive
- 68. @THCapper Page level metrics(e.g. PA) − Wait for page to be crawled − Somewhat domain sensitive + Much closer to value of link
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- 70. @THCapper Outcome metrics (e.g.rankings, revenue)
- 71. @THCapper Outcome metrics (e.g.rankings, revenue) − Causation vs correlation − Effect of individual link lost in noise
- 72. @THCapper Outcome metrics (e.g.rankings, revenue) − Causation vs correlation − Effect of individual link lost in noise + Obvious commercial relevance
- 73. @THCapper Analytics metrics (impressions,referring traffic)
- 74. @THCapper Analytics metrics (impressions,referring traffic) − Access issues − Wait for data
- 75. @THCapper Analytics metrics (impressions,referring traffic) − Access issues − Wait for data + Google’s holy grail + Captures non-SEO value + Captures relevance
- 76. @THCapper @THCapper Agenda Why we buildlinks Why we use these metrics Better measurement What to do next
- 77. @THCapper The challenge The precision& nuance of referral traffic and The ubiquity and availability of domain metrics
- 78. @THCapper The challenge + Availablebeforehand + Google ambiguity + Trained on rankings + Universally understood + Google’s holy grail + Captures non-SEO value + Captures relevance
- 79. @THCapper Metrics for Links Fast| Slow Actual Indicative
- 80. @THCapper Metrics for Links Actual Indicative DA SpamScore # of links Fast | Slow
- 81. @THCapper Metrics for Links Actual Indicative DA SpamScore Reach # of links Fast | Slow
- 82. @THCapper Metrics for Links Actual Indicative DA SpamScore PA Reach # of links Fast | Slow
- 83. @THCapper Metrics for Links Actual Indicative DA SpamScore PA Reach Referral Traffic # of links Fast | Slow
- 84. @THCapper Metrics for Links Actual Indicative DA SpamScore PA Reach Referral Traffic Rankings # of links Fast | Slow
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- 86. @THCapper Actual Indicative DA Spam Score PA Reach Referral Traffic Rankings Metricsfor Links Prospecting # of links Fast | Slow
- 87. @THCapper Actual Indicative DA Spam Score PA Reach Referral Traffic Rankings Metricsfor Links # of links Prospecting Reporting Fast | Slow
- 88. @THCapper Actual Indicative DA Spam Score PA Reach Referral Traffic Rankings Metricsfor Links # of links Prospecting Reporting Post Mortem Fast | Slow
- 89. @THCapper Ideal world The precision& nuance of referral traffic and The ubiquity and availability of domain metrics
- 90. @THCapper @THCapper Agenda Why we buildlinks Why we use these metrics Better measurement What to do next
- 91. @THCapper 1. Focus onthe mechanism
- 92. @THCapper 1. Focus onthe mechanism A 0.85* A/2 0.85* A/2
- 93. @THCapper 2. Measure inphases
- 94. @THCapper 2. Measure inphases Actual Indicative DA Spam Score PA Reach Referral Traffic Rankings # of links Prospecting Reporting Post Mortem Fast | Slow
- 95. @THCapper 3. Learn fromconcrete metrics
- 96. @THCapper 3. Learn fromconcrete metrics Actual Indicative DA Spam Score PA Reach Referral Traffic Rankings # of links Prospecting Reporting Post Mortem Fast | Slow
- 97. @THCapper 3. Learn fromconcrete metrics Actual Indicative Referral Traffic Rankings Prospecting Reporting Post Mortem Fast | Slow
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