Meta, Google and Snap execs on how they’re prepping advertisers for the cookieless world

Here are the top themes they spelled out:

Improved conversion modeling could fill measurement gaps

The demise of third-party cookies throws a wrench in the works for not only ad targeting, but also ad measurement.

To help brands combat new measurement challenges, major publishers such as Meta and Snap are investing more dollars in advanced conversion modeling. Conversion modeling leverages non-identity-linked consumer data to quantify conversions.

At Google, it has become a high priority for the advertising team. “We are investing in conversion modeling, which, for many of you, is an industry best practice. It’s helping really complete the customer journey through using prediction,” said Christine Warner, vice-president of global advertising partnerships at Meta.

Snap, too, is focusing on how conversion measurement tools can help advertisers get the most out of their spend. The company is seeing “strong adoption” of its proprietary conversion API, per Chris Plamback, vice-president of marketing science at the social platform. “It drives clear value to advertisers – you use the API, you get better visibility into the actual transactions that advertising is driving.” Using Snap’s conversion API in conjunction with the Snap Pixel – a cross-site tracking technology similar to a cookie – has helped brands see 11% more purchases and 13% more attributable revenue than if they were using the Snap Pixel alone, said Plamback. Ultimately, he argued, conversion modeling helps advertisers see higher returns on ad spend as well as improved visibility into media performance without using cookies.

Advertisers can unlock first-party power with customer data platforms

As third-party data becomes taboo in the world of advertising, brands are focused on building up their own first-party data. Helping them do so effectively are customer data platforms (CDPs).

“Customer data platforms can enable you to have a better insight on your customers; it can help you knit together that customer journey. It can also help you drive marketing and advertising that respects the privacy preferences of the customers that you're seeking to engage with,” said Meta’s Warner.

Deloitte Digital principal and national market offering lead Michelle McGuire Christian echoed Warner’s convictions, saying: “As it relates to all things digital right now, CDPs are having a moment, which is being driven by that need for insight into a personalized journey that makes ads more effective.”

In essence, robust first-party datasets stored in CDPs enable brands to continue tailoring personalized, targeted messaging – while respecting users’ unique privacy preferences.

Having first-party data is not the same as knowing how to manage and use it

Experts largely agree that brands would do well to invest in first-party data. But the problem is that many advertisers don’t know how to make the most of that data once they have it.

Deloitte Digital recently conducted research on how the demise of cookies will impact businesses in the real world. The company surveyed some 1,500 marketing professionals on how the shift would impact not only marketing functions but the organization at large. While nearly all respondents acknowledged that the change would impact their business, very few could quantify the financial impact on investment returns or revenue. A key part of the problem, the consultancy determined, is that many marketers are investing in their data strategies and building out their CDPs, but ultimately don’t know where to go from there.

“What we heard from folks was ‘I know I have to get a plan to [organize] my first-, second-, third-party data; my online and offline data…so that I can then action it.’ But that was the number one blocker [of progress] – once I have it, how do I action it with partner platforms, inside tools like customer relationship management platforms and others?”

She suggested that there’s an opportunity for organizations to invest in “capability building” around the use of consumer data. “Now I have all this data in my CDP, what am I going to do with it? So that includes things like data science, [for which] traditionally, marketers have relied on IT to do.“ Now, she explained, it’s becoming the responsibility of marketing teams to master data science.

Other approaches for brands looking to make the most of the customer data they already have entail leveraging cleanroom solutions to pair up different anonymized data points and create profiles in a privacy-safe way.

It’s something that Google is investing heavily in. Outside of its cleanroom platform Customer Match, the tech giant is dedicating more resources to helping brands manage and make the most of their first-party data. “[Cleanrooms and CDPs] tend to be really powerful measurement solutions for advertisers who need to understand the impact of their ad dollar spends without having to sacrifice any of their privacy principles,” said Jessica Nussbaum, the company’s head of audience platforms and advanced data.

“Something that we're going to be doing at Google over the next year is investing more in creating connection points between Google and the CDPs and cleanrooms in order to make it really easy for advertisers to leverage their first-party data for marketing purposes, regardless of where that data happens to live today.”

AI and machine learning will help advertisers market with precision

Another priority for Google – which is in many ways the determining voice in the debate around the use of consumer data, considering it eats up the largest portion of US digital ad spend (last year it owned 26.5%, per eMarketer data) – is the development of artificial intelligence and machine learning tools for marketers.

Digital advertising needs to work for everyone – and that includes helping publishers monetize their content, helping advertisers achieve their business goals and, just as importantly, ensuring that users who are out there navigating the internet are doing so in a safe and protected way.

“Machine learning and AI powers most of Google’s business and consumer products – and it’s definitely a big area that we’re going to be investing in more so in the ads and measurement space … as we move forward into this new cookieless, no-tracking-users-across-the-web future,” said Nussbaum.

Nussbaum explained that large-scale signal loss for advertisers across the web – brought on by both legislative and tech-induced privacy changes – has created new gaps in knowledge. AI and machine learning, she suggested, have the potential to solve for these challenges while respecting consumer privacy. “We need to be investing more in machine learning technology and other predictive technologies that allow us to kind of smooth out these things as inventory environments fragment, and ensure that advertisers can still achieve that level of performance that they’re looking for.”

To this end, Google is investing in optimized targeting and new performance tools within Google ads offer automated bidding and targeting solutions without violating users’ privacy.

Nussbaum, however, acknowledges that there’s a long road ahead – and one that will likely involve a number of players and a variety of privacy-preserving technologies. “There’s going to be many solutions out there as different technologies react to these changes, and that’s OK. We expect users to use multiple things. But the stuff that we’re focused on at Google is ensuring whatever solutions that we come up with show that privacy and performance are not at odds with each other – and that regardless of what happens when cookies go away, Google is not going to be building or investing in any types of technologies that allow for continued tracking of users across the web.”

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