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@bloomarty
Debunking Ad Testing
Martin Röttgerding
Head of SEM, Bloofusion Germany
Logo Here
voted “Best Overall Heroconf Presentation”
– THANK YOU!!!
@bloomarty
Learner Outcomes
• Ad testing best practices don‘t work
• What actually happens when you follow best practices
• What you should be doing instead
@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 …
@bloomarty@bloomarty
Martin Röttgerding
• Head of SEM @ Bloofusion Germany
• Blogger @ PPC-Epiphany.com
• Judge @ SEMY (German Search Awards)
• Dad @ Home
Who’s Talking?
@bloomarty
First off: No Worries
• I’m not a mathematician.
• This is not a math lecture.
• I brought some data, though.
iStock.com/digitalgenetics
@bloomarty
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%
@bloomarty
Alternative Approaches
• Gut feeling
• Rules („wait 100 clicks, then decide“)
• Statistical Significance (usually: 95%)
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
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
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
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
@bloomarty
Pros and Cons
• You have the power.
• You know what to do.
• You look good.
• It doesn‘t work.
Waiting for Significance
Problem #1
@bloomarty
@bloomarty
@bloomarty
Additional Slide
• Alternative: just watch https://www.youtube.com/watch?v=s_E0CR01laQ
(30 seconds)
@bloomarty
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.“
@bloomarty
An Experiment
• 576 ad pairs
• Rotated evenly
• Left untouched for 12 months
@bloomarty
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%)
@bloomarty
The Result (a small part)
statistically significant
no longer significant
still significant…
waiting for significance
@bloomarty
The Result (zoomed out)
@bloomarty
The Result (zoomed out)
@bloomarty
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%
@bloomarty
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
Not Looking At All The Pieces
Problem #2
@bloomarty
So this is what we see …
Impressions Clicks CTR
Ad 1 2,000 200 10%
Ad 2 3,000 240 8%
@bloomarty
How we tend to think of CTR
CTR
Your Ad
@bloomarty
What drives CTR?
CTR
Ad
Network
(Google vs. Search Partners)
@bloomarty
Search Partners?
Search Partners
@bloomarty
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
@bloomarty
Segmented by Network
Impressions Clicks CTR
Ad 1 2,000 200 10%
Google
Search Partners
Ad 2 3,000 240 8%
Google
Search Partners
@bloomarty
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%
@bloomarty
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 …
@bloomarty
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 …
@bloomarty
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%
@bloomarty
Quick Win: Ignore Search Partners
• Well…
@bloomarty
What drives CTR?
CTR
Ad
Network
(Google vs. Search Partners)
Slot
(top vs. other)
@bloomarty
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
@bloomarty
What drives CTR?
CTR
Ad
Device
Ad positionNetwork
(Google vs. Search Partners)
Slot
(top vs. other)
@bloomarty
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
@bloomarty
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%
@bloomarty
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%
@bloomarty
What Happens at the Impression Level …
• Most impression-level data is hidden from us
• How would you assess the following scenarios?
@bloomarty
Scenario 1
Your ad
User clicks on this ad
… and never scrolls down
@bloomarty
Scenario 2
Your ad
user clicks on your ad
… and on all other ads as well
@bloomarty
Scenario 3
user clicks on your ad
… after spending 35 seconds
reading all search results
Your ad
@bloomarty
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
@bloomarty
How would you evaluate these?
• 3 impressions
• 2 clicks
• CTR: 67%
Ignoring Feedback
Problem #3
@bloomarty
What drives CTR?
CTR
Ad
Slot
(top vs. other) Device
Ad positionNetwork
(Google vs. Search Partners)
Ad Auction
Ad ranking
@bloomarty
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
@bloomarty
The Impressions Feedback
@bloomarty
Additional Slide
• I probably shouldn‘t repeat what I said there ...
@bloomarty
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
@bloomarty
CTR Feedback
CTR
Ad
Slot
(top vs. other) Device
Ad positionNetwork
(Google vs. Search Partners)
Ad Auction
Ad ranking
mostly invisible
Thinking You Are Better
Motivated Than Google
Problem #4
@bloomarty
Google doesn‘t
understand my
business Google
doesn‘t care
Ad testing isn‘t
important enough for
Google to get it right
@bloomarty
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
@bloomarty
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?“
@bloomarty
Getting CTR wrong …
@bloomarty
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
The Concept Itself
Problem #5
@bloomarty
Conflicting Mindsets
Have a dedicated ad for everything.
Find the best ad and use only that.
[keywords]
?
?
?
?
?
?
?
?
@bloomarty
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?
@bloomarty
Example: Personality
• Do they take their time to read the entire ad?
• How do they respond to
– discounts
– reassurances
– testimonials
@bloomarty
Testing for Things We Can‘t See?
• Manually: Impossible
• Otherwise:
What Should We Do Instead?
So…
@bloomarty
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.
@bloomarty
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
@bloomarty
Know Google‘s Limits
• CTR & conversion rate
• Historical data
• Semantics
@bloomarty
Know Your Strengths
• Provide meaningful ads
• Focus on the big stuff
@bloomarty
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
@bloomarty
To Sum Up…
• No more micromanaging ad tests
• Focus on messaging and supervising the machines
• Your job just became more interesting – congrats!
@bloomarty
Thank You!
• Agency Blog: Die Internetkapitäne
• Advanced AdWords Blog: PPC-Epiphany.com
@bloomarty
Martin Röttgerding
Head of SEA
BloofusionGermany GmbH
martin@bloofusion.de

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