The document discusses the principles of performing an investigation into issues with PPC accounts. It outlines a root cause analysis (RCA) process involving defining the problem, limiting the scope, and investigating through before/after analysis and comparing impacted vs non-impacted campaigns. The goal is to identify the root cause rather than just addressing symptoms. Key steps include understanding the trigger, problem definition, asking questions, and using data visualization and filters to find the "smoking gun".

1. PPC Principles of
Investigation:
la checklist vincente per
analizzare un account
#WMF2020 | Gianluca Binelli | @ktzstyle

2. Who am I?

3. Former advisor for Google’s
own equity fund Capital G.
Say hello…
Gianluca
Voted 2nd Most Influential
PPC Person in 2019.
Binelli
Ex-Googler

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Box?

5. We are the best* scientific
performance marketing agency...
* we are the best according to our mums and now that we’ve won an award as the Best small PPC agency in Europe, it’s official: mums are always right.

6. ...a complex way to say that we
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8. ...building

9. PPC Principles of
Investigation

10. What is an investigation?
The process of answering to
the question “Why”

11. When are we investigating?

12. The approach: split the metric
you want to analyze into the
variables that explain it

13. In other words...
PROBLEM

14. RCA
● Root cause analysis (RCA)
● The root cause analysis process tries to find the source of
an issue, as opposed to simply addressing the symptoms.

15. Step #0: Trigger
0

16. Step #0: Trigger
● This is the part when you realize you have a problem
● It can be triggered by a customer email
● Or even better by one of your automation alerts

17. Step #0: Trigger

18. Step #1: Problem definition
1

19. Step #1: Problem definition
● This is the part where you try to describe the problem
● Making sure you are delimiting the characteristics
○ what is the metric impacted
○ what dates
○ are there other metrics?

20. Step #1: Problem definition
● Something is
wrong, we get less
sales
● Something is
wrong, starting
last Monday we
noticed a sharp
decrease in Sales.
● Something is wrong,
starting last Monday
we noticed a sharp
decrease in Sales.
● Google Ads is the
only channel impacted
● The problem is limited
to the UK
😃
😞 😐

21. Trick #1: Ask questions
to define the problem

22. #1. Ask questions to define the problem
Example: reduction in conversions

23. Is the problem happening also to
other Channels (Free, Paid traffic)?

24. Is the problem limited to Google
Ads or also other Paid Channels?

25. Is the problem limited to one
Country / Google Ads account?

26. Is the problem limited to one
campaign type (eg Search)?

27. When did the problem start?

28. Did something happen on the
client side?

29. Trick #2: Limiting the
scope of the issue

30. #2. Limiting the scope of the issue
● Visually look at the graph to see if there are variations in
the metrics impacted on a specific date
● Focus on higher spending (or converting campaigns). If
the problem is impacting the entire business chances
are the top campaigns are impacted

31. Example: the problem is concentrated
on a specific date

32. Example: the problem starts slowly

33. #2. Limiting the scope of the issue
● Try to see if the problem is affecting only a portion of the
account:
○ a certain campaign type (eg. Shopping only)
○ a certain geography
○ a certain device

34. Example: the issue is in Texas

35. Step #2: Identify the root of the problem
2

36. Revenue
Revenue = Conversions * Average Order Value

37. CPA
CPA = Costs/Conversions

38. ROAS
ROAS = Revenue/Costs

39. Conversions
Conversions = Clicks * CR

40. Clicks
Clicks = Impressions * CTR

41. Costs
Costs = Clicks * CPC

42. Impressions
Impressions = f (Impression Share, Queries in the market)

43. CTR
CTR = Clicks / Impressions
CTR = f (avg position)

44. Connecting all together

45. Investigation Flow Chart

46. Step #3: Investigation
3

47. Approach 1: Before/After analysis
● Video - Customize your tables and charts in Google Ads

48. Approach 1: Before/After analysis
● Compare dates to see when the performance
decreased:
○ If the problem is concentrated in time (2 weeks
before / after the event)
○ If the problem is not concentrated in time (2 weeks
that are clearly affected by the problem vs 2 weeks
when the problem did not exist)

49. Data Comparison

50. Data Comparison

51. Finding the smoking gun
Check Account
History

52. Approach 2: Impacted/Not
impacted campaigns
Use filters to
compare
impacted
campaigns
versus not
impacted

53. If it looks like a and it smells
like a , probably it is
not a stone

54. Conclusions

55. Root Cause Analysis Flowchart
Rimm-Kaufman’s (now Merkle)
dossier 3.2 2012

56. Root Cause Analysis Flowchart
Frameworks for Insights &
Impact - Wijnand Meijer -
HeroConf London 2018

57. gianluca@boosterboxdigital.com
www.boosterboxdigital.com