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6-7, NOVEMBER 2019
How to Predict Your
Quality Score before
you have your first
impression
Gianluca Binelli
Booster Box
1
What do we do?
What do we do?
Scientific Performance
Marketing Agency
Who am I?
4
● 14y experience in online advertising
● 6.5y at Google between Dublin, NYC & London
● Managed Quarterly $XXM in advertising for Google as
part of the SEM in-house team that promotes
Google’s products (in FB, Bing, Google, Linkedin etc)
● Advisor for Google’s own equity fund Capital G
5
6
GoogleAdvertiser
User
@speakerwww.smxl.it #SMXL19 7
@speakerwww.smxl.it #SMXL19
Ad Rank depends on
Quality Score
Bid
Ad Formats & Extensions
8
@speakerwww.smxl.it #SMXL19
Quality Score is important
• Who appears in the auction
• How the ads are ranked
• Actual CPC
9
@speakerwww.smxl.it #SMXL19
Higher Quality Score =
Lower Cost per Click
10
Lower Quality Score =
Higher Cost per Click
@speakerwww.smxl.it #SMXL19
Factors impacting Quality Score
1. Expected Click Through Rate
2. Ad Relevance
3. Landing Page Experience
11@KTZSTYLE
@speakerwww.smxl.it #SMXL19
Not equally weighted (Google 2010)
https://www.youtube.com/watch?v=qwuUe5kq_O8
12@KTZSTYLE
@speakerwww.smxl.it #SMXL19
Not equally weighted (adAlysis 2019)
13
https://searchengineland.com/reverse-engine
ering-adwords-quality-score-factors-244192
@speakerwww.smxl.it #SMXL19
We can only view quality score at keyword
level
14@KTZSTYLE
@speakerwww.smxl.it #SMXL19
We can see if our QS has changed over time
and why
15@KTZSTYLE
@speakerwww.smxl.it #SMXL19
Normally this would take a few months
16@KTZSTYLE
@speakerwww.smxl.it #SMXL19 17
Here, increasing our Ad Relevance raised our
QS
@KTZSTYLE
@speakerwww.smxl.it #SMXL19
OK, so how we can predict the quality score?
18
@speakerwww.smxl.it #SMXL19
Let’s start by the easy part
1. Expected Click Through Rate
2. Ad Relevance
3. Landing Page Experience
19@KTZSTYLE
@speakerwww.smxl.it #SMXL19
Landing Page experience
20
https://support.google.com/google-ads/answe
r/2404197?hl=en
@speakerwww.smxl.it #SMXL19
Increase site speed
21
@speakerwww.smxl.it #SMXL19
Let’s start by the easy part
1. Expected Click Through Rate
2. Ad Relevance
3. Landing Page Experience
22@KTZSTYLE
@speakerwww.smxl.it #SMXL19
Keywords to ad relations? Measure it!
1) Import Ads Report & Keywords Report
23
@speakerwww.smxl.it #SMXL19
Keywords to ad relations? Measure it!
1) Import Ads Report & Keywords Report
2) Measure presence of Keywords in each ad
24
@speakerwww.smxl.it #SMXL19
Keywords to ad relations? Measure it!
1) Import Ads Report & Keywords Report
2) Measure presence of Keywords in each ad
3) Bonus:
• Exclude Stop Words
25
@speakerwww.smxl.it #SMXL19
Keywords to ad relations? Measure it!
1) Import Ads Report & Keywords Report
2) Measure presence of Keywords in each ad
3) Bonus:
• Exclude Stop Words
• In SKAG there is a binary relationship between Ads and
Keywords (you can compute the Score at both levels - it will be
easier on Ad)
• In SKAG you can compute it only at Keyword level (need to
weight it by impressions)
26
@speakerwww.smxl.it #SMXL19
A simplified example: is the KW in the copy?
In order to quickly check it in a spreadsheet similar to the one above (KW - Ad Copy in various
fields), we just have to use the following formula (taking row 2 as an example):
• regexmatch(lower(arrayformula(substitute(concatenate(C2:I2)," ",""))),".*"&substitute(B2," ","")&".*")
This formula returns “True” if the whole Keyword is contained in the AdCopy.
27
@speakerwww.smxl.it #SMXL19
Let’s start by the easy part
1. Expected Click Through Rate
2. Ad Relevance
3. Landing Page Experience
28@KTZSTYLE
@speakerwww.smxl.it #SMXL19
Expected Click-through rate
1) We are running tests all the time, we have a list of best
practices
2) How can you check if the list of best practices is a good
explanation of CTR? Conjoint Analysis!
29@KTZSTYLE
@speakerwww.smxl.it #SMXL19
Conjoint analysis
'Conjoint analysis' is a
survey-based statistical
technique used in market
research that helps determine
how people value different
attributes (feature, function,
benefits) that make up an
individual product or service
30
http://www.mit.edu/~hauser/Papers/NoteonC
onjointAnalysis.pdf
@speakerwww.smxl.it #SMXL19
In our world
Features: elements of the ads
User opinion: clicks
31
@speakerwww.smxl.it #SMXL19
How does it work?
1) We input a set of elements we want to analyze
2) Run Conjoint
3) See how each elements impacts on CTR
32
@speakerwww.smxl.it #SMXL19
Set of
elements to
test
33
@speakerwww.smxl.it #SMXL19
Limits
1) Ignores that Ad Position impacts CTR
2) Ignores Ad Relevancy
3) Limited to explain CTR given the initial set of elements
34
@speakerwww.smxl.it #SMXL19 35@KTZSTYLE@KTZSTYLE
Output Example
21
@speakerwww.smxl.it #SMXL19 36
Impacts positively Impacts negatively
@KTZSTYLE
Output Example
@speakerwww.smxl.it #SMXL19
Scripts Bonanza
gitlab.com/boosterbox-public/
37
6-7, NOVEMBER 2019
How to Predict Your
Quality Score before
you have your first
impression
Gianluca Binelli
Booster Box
38

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