Steve Lohr
Personalized marketing — the product pitch or message that
really hits its target, the right person at the right time — is the
much-discussed ideal in advertising and sales.
The truth is that personalized marketing is, well, mostly marketing today. With modern tools of data analysis, it is becoming increasingly possible to identify customer groups in smaller segments than the big demographic buckets of the past, which filtered by age, gender, income and place of residence. But smaller audiences are still a long way from personalized marketing.
On Wednesday, IBM and Facebook are announcing a partnership to take a step closer to the ideal. The partnership stems from how the companies bring complementary strengths to the lucrative business of data-fueled marketing.
The truth is that personalized marketing is, well, mostly marketing today. With modern tools of data analysis, it is becoming increasingly possible to identify customer groups in smaller segments than the big demographic buckets of the past, which filtered by age, gender, income and place of residence. But smaller audiences are still a long way from personalized marketing.
On Wednesday, IBM and Facebook are announcing a partnership to take a step closer to the ideal. The partnership stems from how the companies bring complementary strengths to the lucrative business of data-fueled marketing.
IBM's data analytics business caters to major retailers
and big consumer product brands. And Facebook, the social networking
giant, does too. IBM's data scientists do a lot of social media and
sentiment analysis, but not with the vast laboratory of
human behavior and preferences that Facebook has.
"Our clients have urged us to bring Facebook into the equation because it is so important," said Deepak Advani, general manager of IBM Commerce. "Facebook is where consumers spend a lot of their time."
Blake Chandlee, vice president of partnerships for Facebook, said, "We both want to connect people with brands. Our objectives are very much aligned. And we share quite a few major clients."
The partnership is intended to combine data that marketers have on customers — like purchase behavior, responses to a marketer's email campaigns and call center inquiries — with Facebook data including likes, comments and complaints.
More from the New York Times:
Google pushes advertisers to smaller screens
Twitter's evolving plans to make money from its data stream
IBM creates Watson Health to analyze medical data
IBM's data analytics will then be used to help big brands find and communicate with more finely targeted audiences on Facebook. Mr. Chandlee called this "personalization at scale." And the insights gleaned from analyzing Facebook and other data should also help companies better target consumers in other marketing channels, such as ads on the web and email programs.
Facebook will also be the first company to join IBM's new Commerce ThinkLab. The new lab is a collaborative setting for applied research involving teams from major consumer brands and retailers, IBM industry experts and data scientists, and teams from Facebook as well.
For IBM, the Facebook partnership is the most recent alliance the enterprise technology company has forged with consumer-focused technology companies, notably Apple and Twitter.
For IBM, the payoff from the partnership is intended to be more revenue for its data commerce business. For Facebook, the incentive, Mr. Chandlee said, is not more ads on Facebook but better-performing ones that can command higher rates.
When it is accurate enough, personalized marketing becomes personal, which raises privacy issues. But Mr. Chandlee emphasized that while Facebook can identify people by their names and email addresses, that kind of information is stripped off before signals about consumer behavior and preferences are passed on for analysis.
"Personal data never flows back and forth," Mr. Chandlee said.
human behavior and preferences that Facebook has.
"Our clients have urged us to bring Facebook into the equation because it is so important," said Deepak Advani, general manager of IBM Commerce. "Facebook is where consumers spend a lot of their time."
Blake Chandlee, vice president of partnerships for Facebook, said, "We both want to connect people with brands. Our objectives are very much aligned. And we share quite a few major clients."
The partnership is intended to combine data that marketers have on customers — like purchase behavior, responses to a marketer's email campaigns and call center inquiries — with Facebook data including likes, comments and complaints.
More from the New York Times:
Google pushes advertisers to smaller screens
Twitter's evolving plans to make money from its data stream
IBM creates Watson Health to analyze medical data
IBM's data analytics will then be used to help big brands find and communicate with more finely targeted audiences on Facebook. Mr. Chandlee called this "personalization at scale." And the insights gleaned from analyzing Facebook and other data should also help companies better target consumers in other marketing channels, such as ads on the web and email programs.
Facebook will also be the first company to join IBM's new Commerce ThinkLab. The new lab is a collaborative setting for applied research involving teams from major consumer brands and retailers, IBM industry experts and data scientists, and teams from Facebook as well.
For IBM, the Facebook partnership is the most recent alliance the enterprise technology company has forged with consumer-focused technology companies, notably Apple and Twitter.
For IBM, the payoff from the partnership is intended to be more revenue for its data commerce business. For Facebook, the incentive, Mr. Chandlee said, is not more ads on Facebook but better-performing ones that can command higher rates.
When it is accurate enough, personalized marketing becomes personal, which raises privacy issues. But Mr. Chandlee emphasized that while Facebook can identify people by their names and email addresses, that kind of information is stripped off before signals about consumer behavior and preferences are passed on for analysis.
"Personal data never flows back and forth," Mr. Chandlee said.
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