NEW ORLEANS: BlackRock, the asset management company, is making use of “precision empathy” as it seeks to connect with its target audience in compelling ways.
Frank Cooper III, BlackRock’s senior managing director/global chief marketing officer, discussed this subject at the 2018 Collision conference in New Orleans.
And he referenced a platform developed with Enigma – a data-management and intelligence firm – that can sift, sort, and segment data to help BlackRock better understand the individual needs of current and potential customers.
“We’re creating this platform that we’re calling ‘precision empathy’,” said Cooper. (For more, read WARC’s in-depth report: BlackRock seeks “precision empathy” in marketing.)
“And the idea of ‘precision empathy’ is simple: It's ‘Can we use data and machine learning in ways that minimize human bias but still allow for human input?’”
Given it manages over $6 trillion in assets, BlackRock is an undoubted expert at making sense of extremely large numbers. But Cooper believes that fusing big data with smart software could thus humanize its brand.
“And the way in which we’re doing that is we’re basically taking large datasets – billions of rows of publicly available data – [and] combining it with some proprietary data and third-party data. And it’s giving us insights that we never could see through the traditional demographic lens,” he said.
Indeed, Cooper argued, the established cornerstones of marketing – like age, gender, household income, geographical location, and ethnicity – increasingly are being exposed as an “awful proxy for how people really think and behave.”
The BlackRock/Enigma model, by contrast, aims to tap a significantly broader slate of insights in order to assist investors, for example, understand how changes in the financial environment may impact their portfolio or spending patterns.
“We think by having machine-produced segments, we can get much more precise. And already we’re finding some interesting things,” said Cooper.
These insights, he offered, cover a wide variety of areas, whether that is understanding granular customer mindsets, learning about financial advisers or discovering the optimal time and place for delivering creative.
“Instead of delivering creative against a large-scale demographic, we’re now looking at the nuances that bind real groups together. That’s a dramatic shift,” Cooper said.
Frank Cooper III, BlackRock’s senior managing director/global chief marketing officer, discussed this subject at the 2018 Collision conference in New Orleans.
And he referenced a platform developed with Enigma – a data-management and intelligence firm – that can sift, sort, and segment data to help BlackRock better understand the individual needs of current and potential customers.
“We’re creating this platform that we’re calling ‘precision empathy’,” said Cooper. (For more, read WARC’s in-depth report: BlackRock seeks “precision empathy” in marketing.)
“And the idea of ‘precision empathy’ is simple: It's ‘Can we use data and machine learning in ways that minimize human bias but still allow for human input?’”
Given it manages over $6 trillion in assets, BlackRock is an undoubted expert at making sense of extremely large numbers. But Cooper believes that fusing big data with smart software could thus humanize its brand.
“And the way in which we’re doing that is we’re basically taking large datasets – billions of rows of publicly available data – [and] combining it with some proprietary data and third-party data. And it’s giving us insights that we never could see through the traditional demographic lens,” he said.
Indeed, Cooper argued, the established cornerstones of marketing – like age, gender, household income, geographical location, and ethnicity – increasingly are being exposed as an “awful proxy for how people really think and behave.”
The BlackRock/Enigma model, by contrast, aims to tap a significantly broader slate of insights in order to assist investors, for example, understand how changes in the financial environment may impact their portfolio or spending patterns.
“We think by having machine-produced segments, we can get much more precise. And already we’re finding some interesting things,” said Cooper.
These insights, he offered, cover a wide variety of areas, whether that is understanding granular customer mindsets, learning about financial advisers or discovering the optimal time and place for delivering creative.
“Instead of delivering creative against a large-scale demographic, we’re now looking at the nuances that bind real groups together. That’s a dramatic shift,” Cooper said.
Sourced from WARC
