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Stop Headaches With Merged Data Content Scoring

Stop Headaches With Merged Data Content Scoring

Learn how to create a consistent content scoring system that measures content against business performance. Have a look, then contact me if you have any questions.

Ian Lurie

October 18, 2024
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  1. .

  2. 0 200000 400000 0 70000 140000 Jan-22 Nov-22 Sep-23 Jul-24

    Site Performance, Clients A and B Site A Conversions Site B Conversions Client A Stops Client B Stops
  3. On 70% of projects, stopping or limiting content programs reduced

    overall performance against business goals.* *Based on client data, and no, I can’t share
  4. 0 60 120 0 70000 140000 Jan-22 Sep-22 May-23 Jan-24

    Sep-24 Site Performance vs. Scores, Client A Site A Conversions Site A Scores
  5. 0 60 120 0 210000 420000 Jan-22 Sep-22 May-23 Jan-24

    Sep-24 Site Performance vs. Scores, Client B Site B Conversions Site B Scores
  6. The basic requirements - Screamingfrog spider - Google search console

    access - Google analytics access - Pagespeed insights
  7. Steps 1. Crawl and segment 2. Grab other data 3.

    Merge 4. Score 5. test and apply
  8. I use unique page views, but it’s up to you

    Not just from organic search!!!!
  9. search console clicks impressions ctr URL analytics pageviews visits conversions

    time on page URL properties fk score link score moz pa rendered perc time v read segment URL Or SQL
  10. =IF(Q79="","",( IFERROR((PERCENTRANK.EXC(C:C,C79) * INDEX(weights!$B$1:$B$99, MATCH("fk score", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(D:D,D79)

    * INDEX(weights!$B$1:$B$99, MATCH("time on page vs read time", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(E:E,E79) * INDEX(weights!$B$1:$B$99, MATCH("link score", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(F:F,F79) * -1 * INDEX(weights!$B$1:$B$99, MATCH("rendered percent", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(G:G,G79) * INDEX(weights!$B$1:$B$99, MATCH("gsc clicks", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(H:H,H79) * INDEX(weights!$B$1:$B$99, MATCH("gsc impressions", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(I:I,I79) * INDEX(weights!$B$1:$B$99, MATCH("gsc ctr", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(J:J,J79) * INDEX(weights!$B$1:$B$99, MATCH("gsc position", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(K:K,K79) * INDEX(weights!$B$1:$B$99, MATCH("cwv score", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(L:L,L79)*-1 * INDEX(weights!$B$1:$B$99, MATCH("ttfb", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(M:M,M79) * INDEX(weights!$B$1:$B$99, MATCH("moz pa", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(N:N,N79) * INDEX(weights!$B$1:$B$99, MATCH("moz linking domains", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(O:O,O79) * INDEX(weights!$B$1:$B$99, MATCH("semrush keywords", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(P:P,P79) * INDEX(weights!$B$1:$B$99, MATCH("unique pageviews", weights!$A$1:$A$99, 0))),0) + IFERROR((PERCENTRANK.EXC(Q:Q,Q79) * INDEX(weights!$B$1:$B$99, MATCH("conversion rate", weights!$A$1:$A$99, 0))),0) ))
  11. 0 60 120 0 210000 420000 Jan-22 Sep-22 May-23 Jan-24

    Sep-24 Traffic vs. Scores Site B Visits Site B Scores Score over time Prove the model
  12. Before you do that, take a closer look. If it’s

    decent content, maybe another channel will do? Email? Social?
  13. This is solid stuff Add it to the list for

    later updates Or update it now in your spare time
  14. (Pssst) Use ScreamingFrog, ChatGPT to find related content at scale

    https://ianlurie.me/ipullrank-embeddings Mike King (use with caution, because AI)
  15. 0 60 120 0 210000 420000 Jan-22 Sep-22 May-23 Jan-24

    Sep-24 Traffic vs. Scores Since You Cut Budget (Again) Site B Conversions Site B Scores
  16. 0 60 120 0 210000 420000 Jan-22 Sep-22 May-23 Jan-24

    Sep-24 Traffic vs. Scores Since You Changed Your Mind (Again) Site B Conversions Site B Scores
  17. 0 60 120 0 210000 420000 Jan-22 Sep-22 May-23 Jan-24

    Sep-24 Traffic vs. Scores Since You Reduced Informational Content Efforts Site B Conversions Site B Scores
  18. 0 60 120 0 210000 420000 Jan-22 Sep-22 May-23 Jan-24

    Sep-24 Traffic vs. Scores Since You Reduced Commercial Content Efforts Site B Conversions Site B Scores