Third-party cookies may be on the way out in Chrome, but that doesn’t mean the end of data-driven advertising.
There are still many other types of audience data that marketers will have at their disposal, including identity graphics and consented third-party data, household-level data, secondary data, contextual data, cohorts and, of course, first-party data. , including login data.
Marketers now have the complex task of figuring out how these components fit into a strong identity strategy, said Adam Broitman, an associate partner focused on digital marketing at McKinsey & Company.
“In the short term, the world without a kitchen will be complex,” Broitman said. “Advertisers will have to test many solutions.”
Many solutions, indeed. Sometimes it feels like a new, supposedly no-bake solution is born every minute (and maybe a sucker too).
Here’s a cheat sheet for the six main types of data targeting marketers will need to become familiar with before third-party cookies are gone for good.
1. First party data
First-party data – email addresses, in particular – will heal whatever ails you. Well almost.
Connection data is often considered the gold standard for consumer data, said Rohini Sen, managing partner and head of science and audience measurement at Wavemaker. It’s even more valuable when consumers validate their information, such as signing up to receive emails or texts in exchange for a coupon or other benefit.
(However, it is still – seemingly eternal – to debate how much consumers value the more traditional trade-in value of data collection and targeted advertising in return for access to free content.)
“Once someone reaffirms their information, you can see that, yes, that’s a real person,” Sen said. “And then when they go online, you know you have at least one reliable method of getting their direct attention.”
Benefits: Consent, precision, useful for measurement, and practice as a set of truth to train machine learning models.
The inconvenients: Scale and potential privacy issues.
“There are two main questions: scalability and are we littering the web with personal information?” said Nishant Desai, director of technology and partnerships at Xaxis. “If every site requires something like Unified ID 2.0, the scale will increase, but this data is arguably more at risk if everyone digs into it.”
2. Identity graphics
Identity graphics will continue to be viable, and even vital, after the depreciation of third-party cookies. But some of the entries will have to change, as will the links that are made between different data points.
Today, third-party cookies are the backbone of most identity graphics.
“At Xaxis, we’re doing a bunch of cookie matching and we’re going to have to do similar bridging and post-cookie matching between multiple sources,” Desai said. “There is an infrastructure cost to this and the identity graphs need to be maintained, so I would say this is a solution for businesses and large publishers who can afford it.”
Benefits: Marketers and publishers have the opportunity to rebuild their identity graphics on a more solid foundation for the long haul.
The inconvenients: Identity graphics are resource intensive.
“If you can relate enough data, it’s useful,” Desai said. “But you have to ask yourself if you are getting the return and if it is financially worth it.”
3. Household level data
Household data has been “the workhorse of media and advertising for years,” McKinsey’s Broitman said, especially for full-funnel marketers looking to build brand value because they need to cast a wide net.
But there is a catch, of course. Most household targeting relies on an IP address, and the future of IP address targeting is fragile at best, the senator from Wavemaker said. IP addresses to associate several devices that connect to the same WiFi network. there is a future in there.
“I advise my brands to avoid this, as it doesn’t seem to respect the intent and direction of privacy in the industry,” Sen said. “On the flip side, however, everything opt-in is still very much on the table, including the kind of buyer data that a company like Catalina collects.”
Benefits: Improved range and works quite well on TV for years.
The inconvenients: Decreased personalization and potential privacy risks associated with cross-device tracking methods that use device fingerprints.
“Still, I don’t think less individualized ads necessarily have to mean less personalization,” Desai said. “When audience targeting and programmatic took hold, the sector largely abandoned household targeting; but now with the end of cookies it feels like everything old is new again.
Speaking of breathing new life into legacy methods, contextual targeting is experiencing a renaissance and marketers are weighing their post-cookie options.
Data collaboration has a lot of potential – if datasets are securely merged and stored securely.
And data consortia could turn the power back to publishers and turn away from the obsession with audience-based targeting. “You can think of it almost as an extension of the first party relationship,” Sen said.
The danger is that second-party data partnerships are often not clear to consumers. “They don’t know which sites are tracking their data, how it’s going or who is involved,” she said.
Benefits: Publisher power, scaling, improved ad targeting, and measurement capabilities.
The inconvenients: Consumers may not be clear on how data is shared on the backend. Appropriate data security and governance is essential in light of platform changes and increased regulatory scrutiny.
Who could forget the cohorts?
Google grabbed the headlines with FLoC [Federated Learning of Cohorts], but Google’s proposal isn’t the only game in town.
Cohort targeting – using common behaviors and interests to create anonymized groupings rather than tying those attributes and experiences to an individual identifier – is a key concept in post-cookie product development.
Benefits: Theoretically secure for privacy …
The inconvenients:… But could introduce new risks for privacy. Cohorts, for example, do nothing to eliminate predatory targeting. They have also not proven their worth in a context without a kitchen. Google’s controversial FLoC experiment, for example, relied on real-time access to cross-site publisher data that will no longer be available once Chrome clears third-party cookies.
“There are subtle differences in the way FLoCs and cohorts are collected and identified,” Desai said. “I don’t see any good way, at least for the moment, to be able to predict the performance of a FLoC.”