Cambridge personality research general presentation feb 2012
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Ad Targeting using Personality Data Evidence and Theory 2011-12 stephen@mypersonality. org
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The ideas and evidence behind targeting online ads based on the personality match between audience and product.
Transcript of Cambridge personality research general presentation feb 2012
Ad Targeting using Personality DataEvidence and [email protected]
Cambridge Personality Research Personality and behavioural data >6.5
mn individuals Model for predicting behaviours,
preferences and individual traits Online tool: www.preferencestool.com In use with global media agencies World leader in research
people and their actions are inter -connected in a Giant Global graph
People
Searches
Workplaces
Products / Services
Websites
Emails
Likes
to describe an individual’s location is to predict her traits and behaviour
tools we use for describing people
100 dimensions of mapped behaviour exclusively from Cambridge University Research models
personality mapping standard – the “big 5” trait dimensions
openness conscientiousness extroversion agreeableness neuroticism
social demographics
technique
Matrix of > 35 million connections between objects behaviours & people
Extract >100 best components of patterning
Any 25 of our components explain enough variance to make a reliable prediction
accuracy
We predict which of these two people is connected with BMW.
Our accuracy is 93%Accuracy for other variables between 67 and 93 %
relevancewe gather data across the websearches browsing logs tweets shopping records mobile sensors Facebook profile
model applicable in all situations
targeting by psycho-demographics personalise
search results add user descriptors demographic
and personality predictions user understanding
value in ad targeting Value proven in Facebook ad targeting
Best personality-based groups are stable and emerge early in campaigns
Method integrated to ad-serving platforms Personality-based target groups score CTR
up to 100% higher than Agency methods Conversions can rise by 45% CPA can be more than halved
example: CTR (food brand)
1
2
3
0.06%
0.10%
0.12%
0.12%
0.13%
0.19%
CTR: Preference vs Agency
Preference keywords: CTR
Agency's keywords CTR
CTR
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A leading Agency’s Facebook fanning campaign compared its in-house keyword generation system against personality-based keyword lists generated by Cambridge Personality Research Preference Tool in a trial of 3.5 mn impressions December 2011. Keyword lists were generated for 3 campaign themes 1. Family, 2. Cooking, 3. Online Shopping. Taking Click Through Rate CTR as the metric, Cambridge Personality keywords outperformed agency by between 30 and 100%. Enough to double the brand audience.
example: CPA (food brand)
A
B
C
1.92
1.08
0.89
0.80
0.82
0.51
Cost per Action: Preference vs Agency
preference agency
$ per Social Action
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A leading Agency’s Facebook campaign compared its in-house keyword generation system against personality-based keyword lists generated by Cambridge Personality Research Preference Tool across 3.5 mn impressions in December 2011. Keyword lists were generated for 3 campaign themes A. Family, B. Cooking, C. Online Shopping. Taking Costs per Social Action as the metric, Cambridge Personality keywords outperformed the Agency keywords by between 24 and 58%. Enough to double the campaign ROI
example: conversions (insurance brand)
1
2
3
0.19
0.18
0.18
0.35
0.33
0.32
Conversion rates: Agency vs Preference (3 top-performing segments)
PreferenceAgency
conversion rate: clicked, then entered competition
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A leading Agency’s Facebook competition-entry campaign compared its in-house keyword generation system against personality-based keyword lists generated by Cambridge Personality Research Preference Tool in a full campaign of 42 mn impressions in November 2011. The top three performing segments of each method are compared. Taking conversion as the metric, target groups defined by Personality using the Preference Tool outperformed target groups defined by the Agency by an average of 45%. Note that CPM was, however, 30 % higher on average for these top-performing groups.
current applications predict business-critical behaviour
likeliness to repay credit card debt quantify personality of brands, products,
competitors and audiences brand insight - positioning and media strategy
recommender engines and apps if you like this music, you’ll probably like this
[music, or other product eg car] ad targeting
preference tool - insights
preference tool - matches
preference tool – adjust profile
thankyouto find out more – [email protected]
www.preferencestool.comTake the free demo: U- demo P- demo
www.cambridgepersonality.com
