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…din alta perspectiva

the SERP

I don’t excel at much. What I do excel at is the ability to spend a whole lot of brain cycles on a SERP Scoring algorithm for my SERP checker that, in the end, will provide, at best, a cursory glance at a ’score’ for all 3 major search engines.
SERP Scoring Algorithm
I need help from the community to code-up a new SERP Score algorithm.  Now at first glance, this problem looks easy, similar to a chemisty experiment where you are given 65 milliliters of a 50% solution and 120 ml of a 30% solution then asked, “What is the strength of the final solution?” It’s a basic algebraic equation.  However, the results/scores are, well, bullshit after page 1, and I need some feedback.

I use some made-up terminology in this piece that you should know:

1.  SERPrint:   Your SERP footprint.  I represent this by displaying your numeric position on each search engine in this order:  Google, Yahoo, Bing.  Example: “1,25,0″ would indicate page 1, position 1 for Google, Page 3, position 5 for Yahoo (#25), and no ranking for The Bingers.  A 1,1,1 would indicate top SERP on all engines.

2.  Search Engine Weight (SEw):  The weight of the search engine corresponding to the usage percentage for all searches as reported by comScore March 2010 U.S. Core Search Rankings.   This is the first piece of the formula.

3. Page Weight (Pw):  Using the AOL SERP CTR Study metrics of “90% Page 1, 10% Page 2″ we can conclude that the pattern repeats past Page 2 into deeper pages.

The Factors

There are 3 factors to consider for a cursory SERP score in the context of the search engine’s given results.

1.  Search Engine Weight:  More volume = more weight.

2.  SERP Position:   From 1-10, where does your listing show?

3.  Page Weight:  How many pages within the search results does your indexed listing appear?

Search Engine Weight (SEw)

SERP Scoring AlgorithmUsing comScore data, we assign the weight of each search engine according to its search volume.

Google:  65.4
Yahoo:  16.8
Bing:  11.5

Observing the Obvious Highlight Moment:  6.3% is spread across the other engines.

SERP Position / Weight (SERPw)

For a given page, how far down in the list is your SERP. Assign weight based on AOL SERP Score data.

AOL SERP CTR Study

We need a big sample to determine the CTR on a given page for a SERP. We’ll be using AOL’s SERP CTR study to get the dispersement %.

Total Searches: 9,038,794
Total Clicks: 4,926,623

% of clicks

    • Click Rank1: 2,075,765 42.13%
    • Click Rank2: 586,100 11.90%
    • Click Rank3: 418,643 8.50%
    • Click Rank4: 298,532 6.06%
    • Click Rank5: 242,169 4.92%
    • Click Rank6: 199,541 4.05%
    • Click Rank7: 168,080 3.41%
    • Click Rank8: 148,489 3.01%
    • Click Rank9: 140,356 2.85%
    • Click Rank10: 147,551 2.99%

Page Weight  (Pw)

How deep within the results does your SERP appear? We use the AOL SERP CTR Study to conclude that it’s 90/10 across the board.

AOL SERP CTR Study – Page Depth

  • 1st page: 4,425,226 89.82%
  • 2nd page: 501,397 10.18%

Based on that, we assign a page-weight coefficient or multiplier (if !1, 10x)
serp page weight coeff
Observing the Obvious:  1 in 100 searches go to Page 3.  1 in 100 million searches go to Page 10?

Sample Scoring

Using different algorithms, here are some sample SERPrints and their corresponding scores.  Which score do you think properly reflects that SERPs rankings?

Algo A = (SEw + SERPw) x Pw

Algo B = SEw x SERPw x Pw

This raw score is then multiplied by a coefficient to produce a 100-point system.   We get the coefficient by first calculating a {1,1,1} SERPrint then by dividing out the raw score by 100 to get the coefficient.  For A, it was 0.45425958 and for B, it was .025331969.

Sample Values

Let’s use the {2,3,15} again.

The first ordinal: 2 on Google

Algo A = (SEw + SERPw) x Pw

SEw = 65.4

SERPw = 11.9

Pw = 1

Total RAW Score For #2 Google (Algo A) = 107.53

Algo B = SEw x SERPw x Pw

Total RAW Score For #2 Google (Algo B) = 778.26

Example 1

{2,3,15}

Algo A = 47.45
Algo B =  24.78
Example 2

{1,0,50}

Algo A = 48.86
Algo B =  69.69

Example 3

{70,2,1}

Algo A = 37.41
Algo B =  17.18

Assumptions

Here are the assumptions that I used for this:

  • The 6.3% left over from other search engines in SEw is irrelevant so discard it.   I teetered on this one and wanted to spread out the 6.3% proportionately across all the 3 to account for the searches but decided against it.
  • People click the same way on any search engine, keyword, regardless of sex, gender, mood, or medium.  This could play a factor since more ‘desperate’ keywords might see deeper checks: “How to cure gonorrhea” or “How to hide a body”
  • People usually display 10 results per page.
  • This score does not factor in ‘keyword volume’.   While this is, by far, one of the most important factors to a true ‘SERP SCORE’, it’s outside the scope of this piece.
  • Who cares about SERP scoring?  It’s just another useless statistic that means nothing. I get it.

What method would you use to calculate a SERP score?  How would you factor in KEYWORD VOLUME?

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