Interpreting Quick Summary Report Data

The Quick Summary Report offers a compressed view of the most important ranking factors for each keyword.  Like the Summary Report, the Quick Summary Report combines Datalines into groups for more accurate data and easier reading.  The style of grouping depends on the grouping method defined on the Reports -> General tab

For this discussion, we will assume that the grouping method was set to "range" and 5 Datalines.

The first column of the Quick Summary Report shows the keyword.  The following 3 columns are User fields, which are entered during the job setup.  In our example, the first User field lists the searches per month.  The second User field lists the Overture 2nd place max bid price.  The third User field is blank as nothing was passed through.

The next field is labeled "Group Range".  Custom URLs are always listed first and represented by alpha characters.  The first Custom URL is represented as "a"; the second as "b" and so forth.  In our example, two home pages from two sample websites were included in SE ANALYST's setup.

Each metric in the following columns is the summary of hundreds of calculations.  Each row represents the metrics for that Group Range

Quick Summary Report

Keyword

User1

User2

User3

Group

Weighted Averages

Grand

Range

Title %

Body %

Backlinks

PR

Score

 

 

 

 

 

 

 

 

 

 

email spam filter

990

2.09

 

a

0

0.2

214

3.65

20.3

b

0

1.2

34

4.26

16.3

 1-5

3.3

0.7

771

4.03

26.8

 6-10

0.6

0.3

787

3.95

25.6

 11-15

0

1

161

4.24

20.1

 16-20

0

1

1871

4.11

29.5

spam filtering

990

0.75

 

a

0

0.2

85

3.25

15.5

b

0

1

33

4.26

16.1

 1-5

10

0.4

678

3.56

22.5

 6-10

10

0.6

2091

4.5

29.6

 11-15

7.3

1.1

205

4.84

24.5

 16-20

0

0.2

1202

4.55

31.2

email retention

930

0.2

 

a

0

0

61

3.23

13.5

b

0

0.9

29

4.12

15.3

 1-5

25.3

1.1

16

2.43

10.9

 6-10

14

0.7

1

2.69

6.1

 11-15

5.7

1

1

2.5

5.2

 16-20

15

0.4

1

2.68

6.4

employee monitoring
outside the workplace

870

0

 

a

0

0.2

71

3.64

16

b

0

0.1

28

4.01

14.1

 1-5

0

0.3

17

3.48

8.8

 6-10

0

0.2

3

2.02

3.9

 11-15

0

0.2

3

2.44

4.2

 16-20

0

0.2

6

2.27

4.8


One of the first metrics that should be examined, is the Backlinks metric.  If your website is like most, then the greatest number of external backlinks (links from other websites) are linking to the home page.  If competition shows lots of backlinks, then your home page has the best chance of success.  Website interior pages that do not have external backlinks may never possess enough "organic strength" to compete.

There are exceptions, however.  If the Title % and/or Body% metrics are exceptionally weak, then a well optimized interior page with strong PageRank may possess enough "organic strength" to compete. 


The second most important metrics are the Title and Body %.  These metrics are more easily controlled and are known as "on-page factors".  The Title % is a strong indicator of the focus of the ranking page.  Higher keyword densities in the Title (greater Title % values) mean that fewer keywords can be optimized successfully. 

Consider this Title % calculation example.

Title: "Email spam filter | email retention"

Phrase

Broad

Part

Weighting

100

60

40

% weighting

50%

30%

20%

Keywords      

Title %

email spam filter

0.33

0.33

0.80

43%

email retention

0.25

0.25

0.60

32%

See Keyword Density Analysis for more information on density calculations.

Adding one more keyword like "employee monitoring" reduces each keyword Title % significantly.

Title: "Email spam filter | email retention | employee monitoring"
         

Phrase

Broad

Part

 

Weighting

100

60

40

 

% weighting

50%

30%

20%

 
Keywords      

Title %

email spam filter

0.20

0.20

0.43

25%

email retention

0.17

0.17

0.29

19%

employee monitoring

0.17

0.17

0.29

19%

Body % densities can be enhanced by increasing the frequency of the keyword in the body content.  Best practices include:

  • Bolding keyword text
  • Putting keywords in H1 tags (headline font size)
  • Adding Alt tags to images that include keywords
  • etc.

The final metric to consider is Google PageRank.  PageRank is a measure of how inter-connected a website page is FROM other website pages on the internet.  Website pages possessing higher PageRank are able to more effectively compete for a keyword 'spaces' without as much page optimization (Title/Body %) or Backlinks.

Generally speaking, PageRank is passed through Backlinks.  External Backlinks (links located on other websites) pass PageRank to other website pages (most often to the home page).  Then, links on a home page pass PageRank to interior pages throughout the website.

In some cases, external Backlinks point to interior pages.  In this case, it is the interior page that receives PageRank value.

If higher PageRank is necessary to compete for a keywords 'space', then a link building campaign may be appropriate.  This is particularly effective for home pages.  To increase the PageRank of interior website pages, make sure there is a link from the home page.  Then consider reducing the number of extraneous links on the home page so that more of the available home page PageRank is passed to specific interior pages.


In some cases, SE ANALYST produces score values that appear to be anomalies.  Consider this Quick Summary Report example.

Quick Summary

Keyword User1 User2 User3 Group Weighted Averages Grand
Range Title % Body % Backlinks PR Score
school internet filter 600 0.21   a 3.3 0.9 154 3.1 18.2
 1-5 3.6 0.3 18 3.1 7.9
 6-10 7.7 0.5 3 2.2 4.7
 11-15 20.9 0.4 27 2.4 11
 16-20 3.6 0.4 0 3 5.3
internet filter 3210 3.48   a 22.3 3 534 3.8 30.6
 1-5 24.3 1.5 395 4.3 26.2
 6-10 7.4 0.3 413 3.9 20.5
 11-15 26.7 1.7 143 4.2 21.9
 16-20 27.1 1.5 171 4.3 23.8

The Grand Score value produced for "school internet filter" for a Custom URL ("a") appears to be very strong relative to other competitors.  But, rankings for the Custom URL are very poor for this keyword.

On close examination, metric strength for "school internet filter" is coming from another keyword: "internet filter".  The Summary Report shows that both on-page KDA metrics and Backlink metrics are coming from the Parts metric. 

 

 

 

 

 

 

 

 

Filter configuration

Filter Number

3

4

5

Minimum PR

0

0

0

Unique IP

Class-C IP

Max Links on Pg

No Max

Keyword Found

Part

Broad

Phrase

Body (x-anchor)

No

No

No

Head

No

No

No

Anchor

yes

yes

yes

 

 

 

 

 

 

 

 

 

 

 

 

 

Body (KDA) %

Title (KDA) %

Backlink Filters (Blinks)

 

 

Phrase

Broad

Parts

Phrase

Broad

Parts

F3

F4

F5

Keyword

Group

avg

avg

avg

avg

avg

avg

mid

mid

mid

school internet filter

a

0

0

12.6

0

0

66.7

161

0

0

Although these Parts metrics are contributing significant strength, and account for the high Grand Score value, the term "school" is not mentioned on the page or in any backlinks.  SE ANALYST's higher Grand Score value shows that there is considerable opportunity in this keyword space.  Simply mentioning the term "school" somewhere on the page a few times will positively affect rankings for "school internet filter".

Occasionally, this same condition shows up in grouped Datalines.  Such conditions are more prevalent for keywords with more terms.  Notice the 11-15 Group Range Grand Score value for "school internet filter".  The score value of 11 is greater than the Grand Score value for the 1-5 Group Range. Again, an examination of the Summary Report shows that much of the Grand Score value is coming from Parts metrics which artificially inflates the Grand Score value.


To determine the Grand Score value for a website page that possesses different metrics than current conditions, download SE ANALYST's Excel Template http://www.seanalyst.com/SEATemplates/SEANALYST-Template-Rev-01.xlt. The last tab of the spreadsheet is a working example that shows metric changes that would produce stronger search engine rankings.