Client
AdEmotion provides a SaaS service to digital agencies looking to increase conversion through tailored, personalized creative.
Project
BETTER FACEBOOK ADS RETARGETING PERFORMANCE
Client
AdEmotion
General info
Project
DLabs.AI developed an AI tool that reviews how specific target groups use Facebook. The algorithm analyzes the social network to glean information around what type of imagery a user group prefers. Then, it leverages the insights to deliver a hyper-specific look across different websites.
About the project
Problem
Creativity doesn’t account for the preferences of the individual user. This leads to brands delivering the wrong aesthetic to target groups and so failing to capture their interest.
Solution
An AI tool that analyzes the aesthetic preferences of different user groups, using psychological profiling to determine the correlation in preferences based on Big-5 theory.
Results
The tool links target group details to keywords, using predictive algorithms to determine the psychological traits of a particular group, then producing a creative brief per segment.
Project duration
12 months
Technologies used
Python
Django
Pandas
Docker
Nltk
Angular
Nginx
Scikit - Learn
The path to success
Step 1: Data collection
Create a survey to determine the psychological traits of a given user
Use Facebook data (inc. posts, likes, shares) to enhance findings
Step 2: Data integration
By combining insights around user behavior on Facebook with personality models based on the Big-5 theory, we devised a custom classification methodology
We based the methodology on levels of neuroticism, extraversion, openness to experience, agreeableness, and diligence
We added data points that assessed aesthetic preferences, helping understand both the user’s psychological traits and the kind of creative content they enjoy (e.g., abstract, organic elements, people, symmetry, abstraction, etc.)
See it in action
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