Linkedin ADS boosted by Behavioral Science

Copyright © SAS Institute Inc. All rights reserved.
Behavioral Messaging: Analysis of
results
June 2020 – Davide Cortellino

How Behavioral Economics Can Improve SAS Marketing
Main concepts
• Behavioral Economics helps us understand why so-called
“rational people” like us make decisions the way we do.
• Kahneman and Tversky (founding fathers) of behavioral economics
identified and classified groups of behavioral heuristics and biases.
• Heuristics are rule-of-thumb, simple mental shortcuts that we
often use to make decisions. When we are faced with decisions that
are simply too complex for us to wrap our heads around, we tend
to focus on one aspect of them and ignore the others.
• Heuristics work great for us most of the time, but sometime they
result in errors called cognitive biases. An applied example:
PRIMING effect:
o When exposed to certain stimuli, such as words or images,
your future perceptions and decisions will be influenced by
what might seem irrelevant items – Teacher example

The content delivery process
Where we have experimented the Behavioral methodology
Content
Creation
Content
promotion
Landing page
Content
Consumption
Feedback
process
Increase the clickthrough rate

Experiment: Analytics Series Episodes
Resume of the experiment design
Generate
Mindstate
Profile
Behavioral
activation
brief

Episodes : Analytics Series
Limits of the study
• The behavioral methodology were initially developed for “training” type of content -> For business
reason it was changed last minute to “product showcase” training
• The design was implemented for a specific technical segment: “Data Scientists” -> Due to the nature
of the new content we were forced to apply the design to other type of audience too with different
level of technical knowledge
• No professional copywriter AND User designer involved // Ads layout not tested
• Limited budget has not always allowed to reach the necessary statistical power for the test
• Limited budget, resources and time have not allowed to implement a multivariate test to study in
isolation the effect Behavioral components individually or in combination -> Aggregated effect
significance

Behavioral science applied
Nudge/Heuristics
Social proof
Scarcity
Visual depiction effect
Present bias Von Restorff effect
Illusion of control

The layout visual processing
How ads in this specific layout are processed
https://www.orbitmedia.com/blog/neuromarketing-web-design/
The ads are processed in
the following order:
1. Image
2. Copywrite
3. Action Button
4. “Details”

The control groups
How we assessed the effect of the behavioral methodology
Control Measures
1. Control groups in
the experiments
Results with
statistical
significance
2. Average
clickthrough rates
achieved in SAS
3. Average
clickthrough rate
achieved in Linkedin

Outcomes
1. Control group in the experiments
Episode Subject/Pro
duct
Target audience Behavioral components Control group Results Insights/Derivations
- Ep.3 v.1 Augmented
Analytics
Technical
Generic + Semi-
Technical
Generic
- Visual Depiction effect
- Von Restorff effect
image/button
- Illusion of
control/Empowerment
copywriting
- Social proof
reinforcement
- Present bias button
Classical SAS ads:
- Descriptive copywrite of the
product
- No image
- Corporative colors
- Present bias
- 48.7% increase in clickthrough rate
- Exists a significative association between applying
the BE design and increasing the click rate
- The evidence of the test is weak, as if replicated it
would stand true in 57% of the cases
- There is evidence of an effect however a further test with a bigger
sample would be necessary to make the conclusion significative
- Ep.3 v.2 Augmented
Analytics
Technical
Generic + Semi-
Technical
Generic
- Visual Personification
effect
- Illusion of
control/Empowerment
copywriting
- Social proof
reinforcement
- Scarcity bias button
Classical SAS ads:
- Descriptive copywrite of the
product
- No image
- Present bias
- 5.4 % decrease in clickthrough rate
- The behavioral design and the control group does
not show a significative difference in click rates
- The lack of significative difference between test and control
suggest this specific configuration does not trigger an emotional
response.
- As the image component is the first to be visually processed there
are hints that images related to the users using the tool does not
work as attention capturing elements.
-Ep. 4 Automated
Machine
Learning
Quantitative
background
audience
- Scarcity/Empowerment
copywriting
- Social proof
reinforcement
Partial BE ads:
- Empowering copywriting
- Present bias
- 53% increase clickthrough rate
- The behavioral design has 1.53 chance to generate a
click than the control
- The evidence of the test is strong, as if replicated it
- Using this behavioral design seems a safe bet to increase the chance to
boost clickthrough performance for machine learning related topics

Outcomes
Episode Subject/Pro
duct
- Ep.5 v1. Black Box
Machine
Learning
Quantitative
background
- Theoretical image
neutral color
button
- Illusion of
control/Empowerment
copywriting
- Social proof
reinforcement
Partial BE ads:
- Empowering copywrite
- No image
- Present bias
- 0% increase in clickthrough rate
- Does not exists a significative association between
applying the BE design and increasing the click rate
- The lack of a significative effect could highlight how images
explaining the theory behind the content are too complex to
process during the scrolling, creating confusion in the user
- The hypothesis is that the remaining effect are neutralized by the
complex image
- Ep.5 v2. Black Box
Machine
Learning
Quantitative
background
- Visual depiction effect
button
- Illusion of
control/Empowerment
copywriting
- Social proof
reinforcement
Partial BE ads:
- Empowering copywrite
- No image
- Present bias
- 23% increase in clickthrough rate
- Despite the increase in the rate does not exists
enough evidence to determine a significative
association between applying the BE design and
increasing the click rate
- A random effect can’t be excluded in generating this click rate
increase
- A bigger sample set is necessary to investigate further if a
significative association can be detected statistically
-Ep. 6 v1 Machine
Learning &
NLP
Quantitative
background
audience
button/image
- Empowerment
copywriting
- Social proof
reinforcement
Partial BE ads:
- Present bias
- No Image
- The behavioral design has 2.12 chance to generate a
click than the control
- Using this behavioral design seems a safe bet to increase the chance to
boost clickthrough performance for machine learning related topics

Outcomes
Episo
de
Subject/Prod
uct
-Ep. 6
v2
Machine
Learning &
NLP
Marketing no
tech /semi-tech
audience +
Customer related
audience
button/image
- Empowerment
copywriting
- Social proof
reinforcement
Partial BE ads:
- Present bias
- No Image
- 17.4% increase clickthrough rate
- Does not exists a significative association between
applying the BE design and increasing the click rate
- The hypothesis is that the response has been mainly related to semi-
tech profiles
- The behavioral quant oriented design seems not working properly for
not quant profile
- The strong quantitative subject highlight the importance of detailed
targeting
- SAS content can not be promoted indiscriminately within all profiles
-Ep. 7
v1
Machine
Learning &
Forecast
Quant audience - Visual Depiction effect
button
- Empowerment
copywriting
- Social proof
reinforcement
Partial BE ads:
- Present bias
- No image
- Von Resorff colors
- Does not exists a significative difference highlighting an
association between applying the BE design and
increasing the click rate
- This is the only case where three elements of a behavioral design has
been applied in the control group too
- So this can be considered an experiment where two different level of
intensity in terms of behavioral components are benchmarked
- Despite the increasing clickthrough rate, the effect is not strong
enough to exclude a random effect
- Being the depiction effect of the image the principal difference in the
two ADS, there are hints to suggest that this component alone is not
able to generate an additive effect in combination with the remaining
components
-Ep. 7
v2
Machine
Learning &
Forecast
Forecasting/Dema
nd Planning
audience
button
- Empowerment
copywriting
- Social proof
reinforcement
Partial BE ads:
- Present bias
- No image
- Von Resorff colors
- 375% decrease clickthrough rate
- The lighter behavioral design triggered a significant
effect in boosting click performance
would stand true in 82% of cases
- It seems that the visual depiction effect of the tool does not work with
Demand Planning roles, which maybe include different levels of
quantitative savy roles
- Also, the technical empowering narrative in the lighted behavioral
version could have faced the same bareer of the point above
- Therefore it seems a safe bet that a lighter behavioral design would
work significatively better for a Demand Planning oriented audience

Outcomes
2. Average clickthrough rates achieved in SAS
• Average CTR Iberia 0.42%
• Average CTR Spain 0.4%
• Average CTR Portugal 0.73%
• Average CTR EDN 0.26%

Outcomes
3. Average clickthrough rate achieved in Linkedin
• The average CTR across all of LinkedIn sponsored content ads is about 0.39% and you can expect to pay around $7 to $11 per click,
especially in North America.
• https://www.socialmediaexaminer.com/how-to-analyze-linkedin-ad-
performance/#:~:text=%231%3A%20Performance%20Benchmarks%20for%20LinkedIn%20Sponsored%20Content&text=The%20average
%20CTR%20across%20all,click%2C%20especially%20in%20North%20America.
https://blog.adstage.io/linkedin-cpm-cpc-ctr-benchmarks-q1-
2019-archive

Episode 3
Profiles
• Audience: Data Analyst, Insight Analyst, Risk Analyst, Marketing Analyst,
Fraud Analyst, Actuarial, CRM Analyst, CRM Manager, Insight Manager,
Marketing Manager, BI Specialist, BI Analyst, BI Manager, IT Manager, Risk
Manager, Fraud Manager, Data Visualization Analyst, Data Visualization
Manager, Business Analyst, Operation Analyst, Operation Manager,
Marketing Director, Risk Director, Reporting Analyst, Reporting Manager,
Data Scientist.

Episode 3 - v.1
Analysis of results: Analyst segment
Tested effects:
- Image: Image actual user view with strong
colors contrast
- Nudge: Orange button with action verbing
- Heuristic: Social proof below main message
- Product: “Masterclass” offering – (admitting it
was product showcase)
- Content: Analytics
- Copywrite: Empowerment
Result: 48.7% increase in clickthrough rate
Statistical test: There is evidence that the above
combination of heuristics, nudge and behavioral
communication generate a statistical significant
result respect to the classical SAS ad
Limited power: The total number of impressions
assigned to the test group does not allow to accept
the effect as strong one, as it will hold true only in
57% of the cases

Episode 3 – v.2
Tested effects:
- Image: Portrait of user using the tool
- Nudge: Orange button with scarcity call
- Product: “Masterclass” offering – (admitting it was
product showcase)
- Content: Analytics
- Copywrite: Empowerment
Result: 5.4% decrease in clickthrough rate
Statistical test: There no is statistical evidence that the
above combination of heuristics, nudge and behavioral
communication generate a significative change in click rates
than a classical SAS ad

Episode 4 – Targeting
Profiles
• Audience: Data Scientist, Data Science Analyst, Data Science Manager,
Quantitative Analyst, Statisticians, Econometricians, Machine Learning
expert, Machine Learning Engineer, Economist, Statistical Analyst (and all
levels of seniority).

Episode 4 – Ads
Analysis of results: DS segment
• Tested effects:
- Image: Image actual user view with NO strong colors
contrast
- Nudge: Orange button with scarcity call
- Product: “Masterclass” offering – (admitting it was
product showcase)
- Content: Machine Learning
- Copywriting: Scarcity + Empowerment
• Result: 53% increase clickthrough rate
• Statistical test: There is evidence of a significative effect
in the test groups in terms of click rate
• Power: These conclusion hold true in 75% of cases,
offering a solid enough conclusion to the significance of
the effect
• The chances of generate a click are 1.53 times higher
using this behavioral design
• Insight: The difference could have been generated by
the usage of a visual-depiction imagery, messaging
based on scarcity and empowerment AND scarcity
button.

Profiles
expert, Machine Learning Engineer, Economist, Statistical Analyst, Data
Engineer (and all levels of seniority), Data Analyst, Data Manager, Insight
analyst.

Episode 5 – Ads1
Tested effects:
- Image: Theoretical construct
- Nudge: Orange button with scarcity
call
- Heuristic: Social proof below main
message
- Product: “Masterclass” offering –
(admitting it was product showcase)
- Copywriting: Empowerment
Result: 0% increase clickthrough rate
Statistical test: There is no evidence of a
significative effect in the test groups in
terms of click rate

Episode 5 – Ads2
Tested effects:
- Image: Image actual user view
with NO strong colors contrast
- Nudge: Orange button with
scarcity call
- Heuristic: Social proof below
main message
- Product: “Masterclass” offering –
(admitting it was product
showcase)
Result: 23% increase clickthrough
rate
Statistical test: There is no evidence
of a significative effect in the test
groups in terms of click rate

Profiles
Engineer (and all levels of seniority), Data Analyst, Data Manager, Insight
analyst.

Episode 6 – Ads1
Analysis of results: DS segment
Tested effects:
- Image: Image actual user view with strong
colors contrast
- Nudge: Orange button with action call
- Product: “Class” offering – (admitting it was
product showcase)
The chances of generate a click are 2.12 times
higher using this behavioral design
Statistical test: There is evidence of a
significative effect in the test groups in terms
of click rate
Power: These conclusion hold true in 96% of
cases, offering a solid conclusion to the
significance of the effect

Profiles
• Audience: Customer Service Manager, Customer Service Director,
Marketing Manager, Marketing Director, Business analyst, Reporting
Manager, Reporting Director, Business Intelligence Manager, Business
Intelligence Director, Customer Service Director, IT Manager, IT Director,
CRM Manager, CRM Director, Loyalty Manager, Loyalty Director,
Complaint Manager, Complaint Director, Brand Manager, Brand Director

Episode 6 – Ads2
Analysis of results: Business User segment
Tested effects:
- Image: Image actual user view
with strong colors contrast
- Nudge: Orange button with action
call
message
- Product: “Class” offering –
showcase)
Result: 17.4% increase clickthrough
rate
Statistical test: There is no evidence
of a significative effect in the test

Profiles
Engineer, Data Analyst, Data Manager, Insight analyst, Demand Planner,
Planificador Demanda, Actuarial, Forecasting Analyst, Economist, Risk
analyst, Financial Analyst, Actuarial, Economist – (All levels of seniority).

Episode 7 – Ads2
Analysis of results: Aggregated technical audience
Tested effects:
- Image: Image actual user
view with no colors contrast
- Nudge: Orange button with
action call
- Heuristic: Social proof
below main message
showcase)
Result: 26% increase
clickthrough rate
Statistical test: There is no
statistical evidence of a
significative effect in the test

Profiles
• Audience: Econometricians, Demand Planner, Planificador Demanda,
Forecasting Analyst– (All levels of seniority).

Episode 7 – Ads2
Analysis of results: Sectorial technical audience
Tested effects:
- Image: Image actual user view with
strong colors contrast
- Nudge: Orange button with action
call
message
(admitting it was product showcase)
keeping only an arousal color and a
short empowering phrase
The chances of generate a click are 4.76
times higher using the limited
behavioral design
Statistical test: There is evidence of a
significative effect in the control groups
in terms of click rate
Power: These conclusion hold true in
82% of cases, offering a solid conclusion
to the significance of the effect

Outcome vs Linkedin general CTR stats
• The average CTR in Linkedin is 0.39%
• CTRs between 0.35% and <1% are considered in the industry as good
performing ADS
• ADS with a CTR >=1% are considered high performing ADS
Test performances
• 3 over 9 ads reach CTR above 1% -> Identified three high performing design to
use in further campaigns
• 5 ads over 9 reach CTR>0.39% -> Hints that the behavioral designs are associated
to higher CTR than the average AD on Linkedin
Outcome vs SAS ADS performance
SAS standard ADS average performances 2020:
• Average CTR Iberia 0.42%
• Average CTR Spain 0.4%
• Average CTR Portugal 0.73%
• Average CTR EDN Europe 0.26%
Test performances
• All the ADS have reported CTR performances significatively above the European average
• 7 ads over 9 have reported CTR performance significatively above Spain and European
averages
• 4 ads over 9 have reported CTR performances significatively above Portugal average
Outcomes vs Control Group
• Two behavioral designs ADS triggered significative click increase than the classic
SAS ADS control groups (+53%, +22 visitors and +111%, +32 visitors) -> Strong
design to use in next campaigns
• One lighter version of a behavioral designs demonstrated to be more effective with
a target audience related to Demand planning (+375%, +18 visitors) -> Strong
design for ads targeting this specific audience
• Three behavioral designs generated stronger click performance than control groups
(+26%, +23% and +26%). However, these performance haven’t been strong enough
to exclude randomness. Therefore further tests will be needed.
Behavioral Marketing Methodology
Experiment objectives
• Increase the clickthrough rates of SAS ads
• By employing behavioral science methodologies
Net effects
• Increase the ROI per money spent
• By landing more target audience on SAS data subscription page than a
classical SAS ads
Experiment design
• 5 episodes with a test group receiving one or two versions behavioral designed
ads
• And a control group receiving a classical SAS ad or a lighet behavioral designed
AD

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