Media > Data
GEOMETRY OGILVY JAPAN, Tokyo / IBM / 2020
Awards:
Overview
Credits
Why is this work relevant for Media?
With the "Second Life" platform, IBM was able to bring the functioning algorithm to convention centers, recruitment offices and exhibition halls to give immediate results using real-time data.
The use of this of these kind of events area proved to be a revelation to many as the individual data was cross-referenced with the occupational data to find unexpected, but fitting matches on the spot.
Background
Japan now has the world oldest population with more than 1 in 4 citizens over 65. And with life expectancy at 85, retirees are looking at 20+ years of feeling lonely and unproductive.
IBM wanted to put their technological prowess to work, in order to begin to find answers to how seniors could live more productive, happier lives in their later years.
The objective was to meaningfully demonstrate IBM's AI abilities; in a tangible way that would bring the foreign company closer to the Japanese people.
Describe the creative idea / insights
To help seniors find their calling after retirement, we wanted to use IBM's tech prowess and AI expertise.
The idea was to create an algorithm that could learn to understand the unique personality traits of individuals. Then, by cross-referencing that data with professional occupation-based data we could see what kinds of positions might be right and satisfying to those seniors.
The unique aspect of the algorithm was how it identified personality traits with specificity, leading to possibilities in their future that participants might not have thought of themselves.
Describe the strategy
We worked with senior organizations, retirement centers and recruited online as well to find seniors interested in finding a more stimulating future.
Fortunately, we found hundreds of seniors who had no fame or fortune. These typical aged Japanese participants more often than not discovered they had interests outside of their occupation through IBM technology, which led to more fruitful occupational suggestions.
The youngest group we had as participants were verging on retirement, in their mid-60s, but the oldest were in their mid-90s.
Describe the execution
After thousands of seniors were recruited, they answered simple questions via their voice, as Watson's AI analyzed and drew connections between a databank of occupations and characteristics, and those participants' personalities.
The IBM algorithm cross-referenced occupational data with participants' traits via Watson's deep personality cognitive analytics.
The platform has so far helped over 43,000 seniors find a fulfilling path they otherwise wouldn't have identified.
List the results
The campaign gained over US$3MM in media attention and 46 million impressions—quite a large number for a B2B effort—while helping over 43,000 seniors find passions they never may have been able to identify.
Describe the use of data, or how the data enhanced the work
This project was unique in that Watson gathered occupational data from thousands of job titles, then gathered individual personality data by using both IBM personality index API and additional data retrieving personalized software, including voice analyzation. It then cross-referenced the two sets of data to find a series of occupational matches.
Watson's deep personality cognitive analytics provided results to seniors helping them find a fulfilling path they otherwise wouldn't have been able to identify.
The campaign gained over US$3MM in media attention and 46 million impressions—large numbers for a B2B effort—while helping over 43,000 seniors find a passion they never may have been able to identify.
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