Voted "Best overall presentation from Heroconf London 2017" “Google doesn’t understand your business, so better pick the winner yourself” – that’s how most PPC professionals approach ad testing. Rotating your ads and waiting for statistical significance has been accepted as the best practice approach for years. The problem: It doesn’t work. Statistical significance sounds fantastic, but with regards to AdWords, it’s nonsense. This presentation looks at two things: Why the best practice approach can’t possibly work – and how it actually doesn’t. To this end, it includes exclusive data on a large number of ad tests that didn’t go as you would’ve expected. This presentation covers * Why statistical significance has no place in ad testing * What actually happens if you follow the industry best practice * Why simpler approaches can actually lead to better results

1. @bloomarty
Debunking Ad Testing
Martin Röttgerding
Head of SEM, Bloofusion Germany
Logo Here
voted “Best Overall Heroconf Presentation”
– THANK YOU!!!

2. @bloomarty
Learner Outcomes
• Ad testing best practices don‘t work
• What actually happens when you follow best practices
• What you should be doing instead

3. @bloomarty
Additional Slide
• To explain what was said in the presentation, I added a few slides like this one
• I plan to write about all of this in greater detail on my blog, PPC-Epiphany.com
• Additional data will also be covered on my blog
• … hopefully soon …

4. @bloomarty@bloomarty
Martin Röttgerding
• Head of SEM @ Bloofusion Germany
• Blogger @ PPC-Epiphany.com
• Judge @ SEMY (German Search Awards)
• Dad @ Home
Who’s Talking?

5. @bloomarty
First off: No Worries
• I’m not a mathematician.
• This is not a math lecture.
• I brought some data, though.
iStock.com/digitalgenetics

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In the Beginning: Optimize for Clicks
% Served Impressions Clicks CTR
Ad 1 96% 12,323 594 4.82%
Ad 2 4% 536 37 6.90%

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Alternative Approaches
• Gut feeling
• Rules („wait 100 clicks, then decide“)
• Statistical Significance (usually: 95%)

8. Statistical Significance in a Nutshell
0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16%
CTR
Ad 1
Impressions Clicks
Ad 1 200 10
Ad 2 200 20
Ad 2

9. Statistical Significance in a Nutshell
0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16%
CTR
Ad 1
Impressions Clicks
Ad 1 200 10
Ad 2 200 20
Ad 2

10. Statistical Significance in a Nutshell
0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16%
CTR
Ad 1
Impressions Clicks
Ad 1 200 10
Ad 2 200 20
Ad 2

11. Statistical Significance in a Nutshell
0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16%
CTR
Impressions Clicks
Ad 1 2000 100
Ad 2 2000 200
Ad 1 Ad 2

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Pros and Cons
• You have the power.
• You know what to do.
• You look good.
• It doesn‘t work.

13. Waiting for Significance
Problem #1

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Additional Slide
• Alternative: just watch https://www.youtube.com/watch?v=s_E0CR01laQ
(30 seconds)

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Is it significant yet?
no
no
no
no
no
no
no no
no yes
„We are 95% certain that this ad is better than the other one.“

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An Experiment
• 576 ad pairs
• Rotated evenly
• Left untouched for 12 months

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Analyzing the Data
• Script to evaluate the data
• Calculate level of significance for each day
• Visualization:
– Ad 1 reaches statistical significance (95%)
– Ad 2 reaches statistical significance (95%)

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The Result (a small part)
statistically significant
no longer significant
still significant…
waiting for significance

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The Result (zoomed out)

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The Result (zoomed out)

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Results
• Most tests reached a significance level of 95% at some point
Minimum total Impressions Tests to reach significance Still significant in the end
1,000 55% 13%
10,000 62% 12%
100,000 81% 11%

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Additional Slide: The Twist
• These were actually 576 A/A tests
• With enough time and data you can almost always find a point where one ad is
significantly better than the other
• Just don‘t take „no“ for an answer and stop when you get the „yes“
• … which is precisely our industry‘s best practice approach to ad testing

25. Not Looking At All The Pieces
Problem #2

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So this is what we see …
Impressions Clicks CTR
Ad 1 2,000 200 10%
Ad 2 3,000 240 8%

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How we tend to think of CTR
CTR
Your Ad

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What drives CTR?
CTR
Ad
Network
(Google vs. Search Partners)

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Search Partners?

30. Search Partners

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Additional Slide
• You can actually target search partner sites like eBay
• For how to do this, read
https://www.ppc-epiphany.com/2012/04/02/targeting-search-partners/
• However, CTR and conversion rate on sites like eBay are abysmal, so this probably
won‘t be worth your time
• Search partners are often profitable, but your priority in ad testing should be Google

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Segmented by Network
Impressions Clicks CTR
Ad 1 2,000 200 10%
Google
Search Partners
Ad 2 3,000 240 8%
Google
Search Partners

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Segmented by Network
Impressions Clicks CTR
Ad 1 2,000 200 10%
Google 1,000 180 18%
Search Partners 1,000 20 2%
Ad 2 3,000 240 8%
Google 1,000 220 22%
Search Partners 2,000 20 1%

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Impressions Clicks CTR
Ad 1 2,000 200 10%
Google 1,000 180 18%
Search Partners 1,000 20 2%
Ad 2 3,000 240 8%
Google 1,000 220 22%
Search Partners 2,000 20 1%
Also possible …

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Impressions Clicks CTR
Ad 1 2,000 200 10%
Google 1,000 180 18%
Search Partners 1,000 20 2%
Ad 2 3,000 270 9%
Google 1,000 220 22%
Search Partners 2,000 50 2.5%
Also possible …

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How common is this?
Based on a study of 6,500 ad pairs, compared with an AdWords Script
• Overall winner loses on Google • Overall winner loses on
Google & Search Partners
32.74%
12.23%

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Quick Win: Ignore Search Partners
• Well…

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What drives CTR?
CTR
Ad
Network
(Google vs. Search Partners)
Slot
(top vs. other)

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Same Thing with Slots
• Overall winner loses in the top slot • Overall winner loses on top & other
18.46%
6.30%
Based on a study of 6,500 ad pairs, compared with an AdWords Script

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What drives CTR?
CTR
Ad
Device
Ad positionNetwork
(Google vs. Search Partners)
Slot
(top vs. other)

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CTR by avg. Position (Google top)
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0
Avg. Pos. CTR

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Exact Positions‘ CTR‘s (Google top)
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0
Avg. Pos. CTR Exact Pos. CTR
18.05%
13.64%
12.05%
10.09%

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Interpolated CTR‘s
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0
Avg. Pos. CTR Exact Pos. CTR interpolated Exact Pos. CTR
18.05%
13.64%
12.05%
10.09%

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What Happens at the Impression Level …
• Most impression-level data is hidden from us
• How would you assess the following scenarios?

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Scenario 1
Your ad
User clicks on this ad
… and never scrolls down

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Scenario 2
Your ad
user clicks on your ad
… and on all other ads as well

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Scenario 3
user clicks on your ad
… after spending 35 seconds
reading all search results
Your ad

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Additional Slide
• What did these three scenarios say about the performance of your ad?
• Actually, don‘t bother
• As search marketers, all we see is what‘s on the next slide

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How would you evaluate these?
• 3 impressions
• 2 clicks
• CTR: 67%

50. Ignoring Feedback
Problem #3

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What drives CTR?
CTR
Ad
Slot
(top vs. other) Device
Ad positionNetwork
(Google vs. Search Partners)
Ad Auction
Ad ranking

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CTR
The Position Feedback
• Positive feedback
• No loop:
position effects do not affect QS
Ad position
Ad Auction
Ad rankingHigher CTR
Higher
Quality
Score
Better
Position
Higher CTR

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The Impressions Feedback

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Additional Slide
• I probably shouldn‘t repeat what I said there ...

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The Impressions Feedback
• Negative feedback:
• No loop:
low relevance impressions
evaluated separately
Higher CTR
Higher
Quality
Score
More less
relevant
impressions
Lower CTR
CTR
Ad Ad Auction

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CTR Feedback
CTR
Ad
Slot
(top vs. other) Device
Ad positionNetwork
(Google vs. Search Partners)
Ad Auction
Ad ranking
mostly invisible

57. Thinking You Are Better
Motivated Than Google
Problem #4

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Google doesn‘t
understand my
business Google
doesn‘t care
Ad testing isn‘t
important enough for
Google to get it right

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The AdWords Business Model
„How much would you give us if we gave you the click?“
„How much would you give us if we showed your ad?“
Sell ad clicks
Sell ad impressions
Convert bids
No control over clicks
Advertisers want clicks

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The Ad Auction
• 𝐴𝑑 𝑅𝑎𝑛𝑘 = 𝐶𝑃𝐶 ∗ 𝑄𝑢𝑎𝑙𝑖𝑡𝑦 𝑆𝑐𝑜𝑟𝑒
• = 𝐶𝑃𝐶 ∗ 𝐶𝑇𝑅
• =
𝐶𝑜𝑠𝑡
𝐶𝑙𝑖𝑐𝑘𝑠
∗
𝐶𝑙𝑖𝑐𝑘𝑠
𝐼𝑚𝑝𝑟𝑒𝑠𝑠𝑖𝑜𝑛
• =
𝐶𝑜𝑠𝑡
𝐼𝑚𝑝𝑟𝑒𝑠𝑠𝑖𝑜𝑛
= „How much would you give us if we showed your ad?“

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Getting CTR wrong …

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Additional Slide
• Quality Score is basically CTR
• Google needs to know CTR to calculate cost-per-impression bids
• Based on this, Google can maximize their revenue from showing ads
• Getting CTR wrong means leaving money on the table – this adds up
• Google is well-motivated to get CTR (and therefore ad testing) right

63. The Concept Itself
Problem #5

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Conflicting Mindsets
Have a dedicated ad for everything.
Find the best ad and use only that.
[keywords]
?
?
?
?
?
?
?
?

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Example: Search History
• Have they searched for this before?
• Did they interact with ads?
• Did they interact with organic results?
• Have they seen our ad before?

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Example: Personality
• Do they take their time to read the entire ad?
• How do they respond to
– discounts
– reassurances
– testimonials

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Testing for Things We Can‘t See?
• Manually: Impossible
• Otherwise:

68. What Should We Do Instead?
So…

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New Mindset
• You don‘t have control over ad testing. Let it go.
• There can be multiple winners.
• Use Google‘s optimized ad rotation by default.

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Let the Machines Do Their Job
• Google is well motivated
• Google is really good with data and algorithms[citation needed]
• Let Google decide which ads to show

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Know Google‘s Limits
• CTR & conversion rate
• Historical data
• Semantics

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Know Your Strengths
• Provide meaningful ads
• Focus on the big stuff

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Keep an Eye on the Machines
• If necessary, force data collection
• Rotate at adgroup level
• Consider the cost of even rotation
• Alternative: Add the ad again
iStock.com/RichVintage

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To Sum Up…
• No more micromanaging ad tests
• Focus on messaging and supervising the machines
• Your job just became more interesting – congrats!

75. @bloomarty
Thank You!
• Agency Blog: Die Internetkapitäne
• Advanced AdWords Blog: PPC-Epiphany.com
@bloomarty
Martin Röttgerding
Head of SEA
BloofusionGermany GmbH
martin@bloofusion.de