You are exposed to 2,000 - 3,000 ads every day.
How many do you actually pay attention to?
Data analytics personalized for your customers
The Problem
Companies are misallocating resources advertising to individuals not in their target demographic.
Growing Trends
Big Data
More companies are looking to gather and apply data
64% of consumers use mobile payment as their preferred method
Digital Wallets
The Solution
Targeted Demographic
Gather detailed data: emotion, vision retention
Meaningful Metrics
Machine
Learning
Data analytics personalized for your customers
Appendix
Server Costs
Softwares
Using Microsoft Azure face detection API, AWS Database storage, and square reader SDK
Use the database storage system to store metric data, ads, target market profiles
Use square reader SDK in order to display the ads onto the system
<!--FIRST IMAGE-->
connect to Microsoft Azure face detection --> determine demographic
encrypt taken image
extract face detection information into company target market profile
store data onto AWS Database
remove image
choose ad to be shown from array
based on matched target market profile
if user's demographic characteristics == target market profile
display ad to user
<!--SECOND IMAGE-->
connect to Microsoft Azure face detection --> determine emotion and eye ball tracking
encrypt taken image
extract face detection information
store data onto AWS Database
remove image
analyze data from database
calculate metrics (emotions, age, sex)
if face detection data outputs positive reaction
add to positive counter
else if face detection data outputs negative reaction
add to negative counter
else
add to neutral counter
display data metrics into dashboard for companies to see the progress of their ads
create bar graph for age, emotional reaction
create pie chart for sex
create single bar for eye retention