This document provides tips and techniques for summarizing and presenting SEO data using Excel pivot tables and dashboards. It discusses how to categorize keywords and URLs, estimate traffic from rankings, analyze competitors in search results, and merge keyword and site analytics data. Preparing raw data in separate sheets and using calculated fields, pivot tables, slicers and graphs allows creating interactive reports and dashboards to analyze topics, locations, keywords and site performance over time.

1. Sam Partland
Analysis, Insights & Reporting

2. About Me – Sam Partland
• 12 years digital marketing experience
• Lead generation & affiliate marketing for various
niches
• Covered all aspects of digital marketing for small
businesses through my own business
• Have worked agency side and in-house, and
currently a growth marketer at Airtasker

3. Whilst agency side, I got bored of the repetitiveness
Copy and pasting over and over
Individually analysing keywords and
mapping data
Worst of all – monthly reporting

4. 16 hours of work every month generating 3-page PDFs
Comments, SEO visits & rankings, SEM traffic & spend data across 20 hotels.
Great fun!

5. So I worked out how to automate it with a button!
And saved 12 hours a month.
Google analytics, ranking data, & SEM data
exported into a single Excel file.
One button would;
- Cycle each hotel
- Merge SEO & SEM Data
- Integrated comments
- Generates 20 PDFs

6. I then worked out how to take a list of keywords

7. And efficiently group them into related topics / categories
Car
Truck
Van

8. Which had me thinking, what else could I optimise or do better?
Keyword dashboards
Competitive overviews
Ranking reports Opportunity analysis
Combining analytics &
ranking data
Keyword mapping
Search market
overview

9. Why is any of this important?
Analysis, Insights & Knowledge Forecasting & Reporting

10. The basics

11. Preparing your data
• Separate sheet with a RAW table full of the data you need
• One month / keyword per row in most cases
• New column for anything you want to filter the data by

12. A KeywordRAW & SERPsRAW will create almost anything!
KeywordRAW

13. A KeywordRAW & SerpsRAW will create almost anything!
KeywordRAW
SerpsRAW

14. Efficiently Categorise & Classify keywords in bulk
The Magical Formula:

15. How the magical categorisation formula works
1. Find One
of These

16. How the magical categorisation formula works
1. Find One
of These
2. In Here

17. How the magical categorisation formula works
1. Find One
of These
2. In Here
3. Then Use
Matching
Category

18. How the magical categorisation formula works
1. Find One
of These
2. In Here
3. Then Use
Matching
Category
4. In Here

19. And we get thousands of keywords categorised in seconds

21. And we can also apply this to URLs

22. Pivot tables present your data in a digestible manner
When you update the RAW, you can ‘refresh’ your pivot table.
• Easily filter
• Apply styling / formats
• Calculated Fields
• Power graphs

23. Slicing & filtering will let you analyse your data based on the categories
A ‘slicer’ will do this most efficiently
…and they’re prettier.

24. Use a default, or create custom table & slicer designs
Match your clients’ colours and they’ll love you!
It will take time to setup, but once done you
can keep re-using!

25. Estimate traffic using a CTR model
This model ‘guesses’ what
clicks a site will receive.
Whilst not extremely
accurate, it does allow us
to set a benchmark for
comparison.
Rank 1: 33.6% of searches
Rank 7: 2.1% of searches
Rank 16: 0.9% of searches

26. How the traffic estimation works
1. Find The
Rank

27. How the traffic estimation works
1. Find The
Rank
2. In Here

28. How the traffic estimation works
1. Find The
Rank
2. In Here
3. Then Multiply
Search Volume

29. How the traffic estimation works
1. Find The
Rank
2. In Here
3. Then Multiply
Search Volume
4. By The
Matching
Approx. CTR

30. How the traffic estimation works
1. Find The
Rank
2. In Here
3. Then Multiply
Search Volume
4. By The
Matching
Approx. CTR
Rank 1 CTR: 33.6%
480 Volume x 0.336 = 161 Visits

31. Putting it all to use..

32. Faster Keyword Mapping
Leverage categorisation to automate keyword mapping.
You will need;
• Categorised keywords & URLs

33. Start with a raw table that has categorised keywords & landing pages
Merging both allow you to use a single pivot table

34. Pivot by category structure, then add URLs & Keywords
LocationCategory URL Keyword

35. Copy paste this out of the pivot table
Drag down the URLs & remove blanks

36. Search Market Overview
The search market overview is going to show you what
categories / locations get searched, and the top keywords.
You will need;
• Keywords with search volume
• Categorisation setup & applied

37. Start with pivots for anything you want volume graphs for

38. Then create separate pivot tables for the top categories
Include their keywords with volumes

39. Then just join it all together, and clean it up!
We get an overview of the top categories,
locations & keywords within a niche.

40. Keyword Dashboard
Reports aren’t always the best way to present data, and are best
avoided where possible!
You should try using dashboards.
You will need:
• Categorised keyword data
• Search volumes

41. Empower clients to pull their own insights
Through the use of Pivot Tables & Slicers, you can send a client
an interactive document.

42. Setup categorised overviews with the keywords (or subcategories) below
Expanded to the keywords within by clicking the ‘+’

43. You can also slice the data to filter by other categories
Truck
4WD

44. The best way to present keyword data to a client

45. You could look at the top locations for van hire keywords

46. Then see the top keywords for Melbourne van hire

47. Competitive Landscape
The competitive landscape document will show who the top
players are in your categories.
You will need;
• Top 10 (or 20) domains ranking for a keyword set
• Estimated traffic formula applied.

48. Create a pivot table & graph for the top domains
Use estimated traffic to weigh them up against each other.

49. Then add separate pivot tables for top sites per category

50. Once put together, we get an overview of top competitors within a niche
This will assist in setting your performance
goals, as you now know who ranks where.

51. And you could even add a category slicer to the graph

52. And you could even add a category slicer to the graph

53. And you could even add a category slicer to the graph

54. Opportunity Analysis
An opportunity analysis will allow you to identify key categories
of interest for your client.
You will need:
• Categorised keyword data
• Search volumes
• Rankings

55. Split your data into the categories you want

56. And use two calculated fields / metrics
‘If #1’ – ‘Search Volume’ x ‘#1 CTR’ (0.336)

57. And use two calculated fields / metrics
‘If #1’ = ‘Search Volume’ x ‘#1 CTR’ (0.336)
‘%Share of #1’ = ‘Est Traffic’ / ‘If #1’)

58. And then just piece it together

59. Another way to look at opportunity
This is how you could value up step change increase of rank.

60. Ranking Snapshot
A ranking snapshot is ideal as a once off, or initial, report to
show where a website stands.
You will need:
• Categorised keyword data
• Search volumes
• Rankings

61. Create a pivot table that filters to clients Est Traffic
And add a calculated field for % Share of #1.
% Share of #1 = 'Est. Traffic‘ / '#1‘
Where ‘#1’ is the estimated traffic for #1 (Volume * 0.336)

62. Then split out categorised keywords with their rankings

63. Piece together and we get a good performance overview
This also roughly touches on how they
are performing compared to how #1
would be performing.

64. Weighted Rankings
Not all keywords are equal.
An ‘average rank’ treats them like they are.

65. At a quick glance, this report is not showing anything positive

66. Individual keywords actually show some positive movement though
But the graph still points south! 

67. Using ‘Est. Traffic’ / ‘Volume’ we can get a weighted market share
Since the highest volume terms still increased in rank, the overall market share
movement was actually positive.

68. Good way to show ranking movement, and cover all bases
Could also just show ‘estimated
traffic’ instead of market share.
However, that doesn’t help
understand the potential.

69. Onedrive
OneDrive allows you to present your data, in an online
dashboard.
Don’t send your client a file, send them a link!

70. Save your data to onedrive
There is an approx. 5MB file limit for
this to work, but that will handle a lot
of data still.

71. Then just create a sharing link

72. You can now share the link with anyone and view in the browser

73. Custom SERP Analysis
Analyse the top ranking websites for a large keyword set in Bulk.
You will need;
• Top 10 (or 20) domains ranking for a keyword set
• Estimated traffic formula applied.

74. Add anything URL / Domain specific to your SERPraw for comparison
I’m going to use Page Titles

75. We can now see the top ranking page titles by category
You don’t always need to be
different.

76. Clicking each of the slicers reveals the top titles per category
Bus
Truck

77. Better yet though – you could analyse any metrics for YOUR serps

78. Analyse keywords in bulk for
ranking potential

79. Build a list of sites that you think you are your closest competition
Check the top sites list
And build a table in your
SERPs ranking raw file

80. Give each ranking domain their score
By using a vlookup to the domain table
=IFERROR(VLOOKUP([@Domain],Competitors,2,0),0)

81. Then each keyword gets a total score
Using a SUMIF that matches the keyword from Serps RAW to Keyword Raw.
=SUMIF(serpraw[Keyword],[@Keyword],serpraw[Domain score?])

82. Pivoting this, we see estimated traffic by that ‘rankability’ score

83. And most importantly – the low scoring keywords

84. Why’d they get a low score?
- International keywords
- Niche / to targeted
Filtering by a score
under 2…
- Some complete scraps that
slipped through

85. I love this type of keyword analysis
• Removes junky keywords from your research
• Removes ‘dictionary’ keywords
• Filters our keywords that might prove too difficult
• Highlights international / niche keywords
Let Google tell you what to try target based on your competitors.

86. Google Analytics
Exporting your Google Analytics data allows you to expand upon
it, analyse it, and present it how you would like to.
You also don’t need to train a client on how to use GA to be able
to see their performance.

87. Create a GA custom report, and export the data you want to analyse
This month-by-month report has been split out channel.

88. Create a GA custom report, and export the data you want to analyse
This month-by-month report has been split out channel.
Insert Month, and Year to analyse YoY data.

89. Insert pivot tables for each metric

90. Setup a ‘current’ and ‘previous’ pivot table
Two slicers are setup to select a month (or period) for the report,
and a comparison month (or period).
These control pivot tables with the
associated metrics.

91. Great Google Analytics overview
Using a slicer, you can generate channel
specific reports, and create a small set of
easily-updated pages for the report.
Once data is updated, all you need to do is
press the new date!

92. Automate your comments based on increases / declines
The comments are even being auto-magically generated based on
whether a metric has increased or decreased.
Add a personal touch to the comment, and you’ve saved yourself a
bit of time each month.

93. Merging analytics & ranking
performance

94. Have your analytics and ranking data merged in one RAW
1.
1. Separate between traffic / rankings

95. Have your analytics and ranking data merged in one RAW
1.
1. Separate between traffic / rankings
2. Keyword or landing page
2.

96. Have your analytics and ranking data merged in one RAW
1.
1. Separate between traffic / rankings
2. Keyword or landing page
3. Same category columns to collate data
2. 3.

97. Have your analytics and ranking data merged in one RAW
1.
1. Separate between traffic / rankings
2. Keyword or landing page
3. Same category columns to collate data
4. Any visitor metrics
2. 3. 4.

98. Have your analytics and ranking data merged in one RAW
1.
1. Separate between traffic / rankings
2. Keyword or landing page
3. Same category columns to collate data
4. Any visitor metrics
5. Ranking & estimated visitor data by month
2. 3. 4. 5.

99. Create pivot tables for Rankings, Est Traffic, Visits, & Conversions
You will need a separate table for anything that you want to
have a separate graph for.

100. Create a graph from each table

101. Add your category slicers

102. Clean it up to have an organic performance dashboard
Category or location
performance insights
Confirm whether ranking
movement is impacting visits
on a landing page level

103. So by clicking ‘car’ & ‘Melbourne’ we can filter the report
And can see Melbourne was
the reason for the June spike

104. With a full use case being a dashboard I built agency side

105. So, we’ve covered
• Keyword & URL categorisation and what to do with it
• Presenting various forms of SEO data ‘prettily’
• Leveraging dashboards rather than always using reports
• Analysing the SERPs to determine what is ranking
• Merging keywords & landing page performance

106. Thanks! 
seoinexcel.com/dmss
sam_partland
linkedin.com/in/sampartland/