Upwave is trying to bring a Google Analytics feel to brand metrics measurement – less like post-campaign research consultancy and more like hands-on, inflight daily insights into brand awareness and sentiment using a software solution that can also support top of funnel optimisation. “If we do our job, we make brand campaigns feel like performance campaigns, which you can constantly look at and optimise every hour in some channels. Brand was missing that,” says Kelly.

The next step in this ‘brand-treated-like-performance’ approach is the use of programmatic to optimise brand campaigns. Upwave has generated a persuadability score that can be applied to a brand and its favoured KPIs at a household level. Currently in laboratory testing with partners, this gives a household a score between zero and one based on how likely it is that consumers can be persuaded by a brand or a message. The score spins out of data analysis and modelling that is underpinned by a combination of deterministic exposure data (including ACR or set-top box data) and consumer opinion survey data.

The programmatic buying will be optimised against the persuadability score (with Upwave feeding the data to the DSP – the company does not buy or sell media itself). “Based on how persuadable a household is, a decision can be made on what to bid [to win an ad spot].” Upwave’s ambition is that programmatic buys can be optimised for brand outcomes as well as for conversion.

Upwave has industrialised consumer surveys to generate the data that helps it understand brand impact and persuadability, and this includes full automation. Kelly says the company surveys millions of consumers every year. “We don’t maintain a panel; there is no single group of consumers. For every campaign we find a large representative sample of consumers to get their opinions,” he explains. For any campaign, tens of thousands of people are surveyed, including both exposed and non-exposed homes.

Upwave does not try to link brand-level outcomes to actual business outcomes, leaving others to fuse these data sets if they want to. But the brand-level outcomes can be used as a predictor, by showing propensity to become a customer, Kelly claims. When Upwave conducted some tests to gauge the accuracy of its uplift-to-customer assumptions, using grocery sales data, the connection was very accurate, he notes. “We believe we can be used to forecast sales, though we are not tracking sales ourselves. Our early tracking with sales data has been very accurate.”

Kelly says the TV industry is spending a lot of time worrying about audience measurement and currency but needs to put as much effort into demonstrating outcomes – and that includes top of funnel outcomes, where his company specialises. “If a CMO wants to protect their TV budget, what do they want to show: currency statistics proving that they got what they paid for [they reached their target audience] and they were not ripped off, or metrics showing their top of funnel outcomes and that it was effective advertising?” he asks.

Returning to his American Football analogy, Kelly explains: “When a player scores in the end zone, that is a sales conversion. But what about all the plays that get you down the field into the end zone? We measure the movement down the field.” He points to the potentially huge impact of brand advertising, which at its best generates demand and increases lifetime value of customers you do secure, which pays back over years (like when people churn from other brands but stick with yours).

The long-term impact of brand advertising may be understood but when the CFO knocks on the door, CMOs may need some answers today. “Within a short timeframe, we can accurately forecast that you are generating the basis for customer lifetime value,” Kelly claims.

What started as novel and helpful thanks to cookies, became overused and concerning. Increasingly consumers of all ages, locations, and persuasions have a better understanding of cookie-based ad tracking and have expressed concerns about its usage. Legislators got involved, and browsers began responding en suite by limiting or outright banning global cookies, while setting the stage for their own targeting capabilities. While their ultimate death keeps being forestalled, a day without cookies is on the horizon. As that day keeps getting pushed back, one likely reason is that it’s hard to wean ourselves off them without knowing what’s next.

While 84% of consumers care about privacy and want greater control over how their data is used, they also don’t want to return to an advertising stone age where ads for products they don’t want dominate their screens.

With changing industry standards and compliance requirements, it’s difficult for brands and their media partners to plan long-term advertising efforts that will be both effective and privacy-compliant. But that balance is going to be more critical than ever going forward.

There will still be a place for targeted ads, but they must have greater privacy controls. Advertisers, agencies, and technology vendors are all debating how to future-proof their cross-channel marketing and brand marketing optimisation. The goal is to identify a privacy-safe plan for ad tracking that doesn’t rely on cookies.Cookie-dependent advertisers must rip up their old playbook and begin investing in the future. The changing privacy landscape presents a catalyst and an opportunity for advertisers to rethink measurement. But while there are many potential solutions, all will not pan out, and others could lead advertisers astray.

Here’s what businesses need to consider to future-proof their advertising in the ensuing cookieless environment.

Begin weaning yourself off cookies

Even though Google has not yet banned cookies from Chrome, other elements make cookies less desirable. Users can easily block cookies on their mobile devices, and cookies don’t easily track in a multiple device world (e.g., users browsing a phone versus a desktop or watching streaming on a tablet or a CTV). Advertisers can no longer depend on cookies for advanced targeting.

Hashed emails have significant limitations

“Hashing” emails allows one website to obscure and “pass off” a user’s email to another destination via an anonymised customer ID. So they can track customers who logged in across multiple browsers or social channels. While it’s a novel idea, it cannot scale because only 10% of Internet traffic is logged in at any time. It’s too small an audience to develop a modern advertising strategy around.

Clean rooms show promise, but aren’t quite ready

A clean room can create a safe environment to combine anonymised first-party data with third-party data from ad platforms and publishers. It provides a promising opportunity to analyse ad tracking data while staying privacy-compliant. It is reasonable to think that almost every advertiser with at least $1 billion in sales will use them in the next five years, and the IAB is expected to release its first attempt at clean room standards later this year.

The work IAB and other organisations do to create standards is important as there is and will continue to be a tension between the privacy restrictions the clean room owner puts in place and the usefulness of the queries those clean rooms can support.

In addition, clean rooms typically contain data from only a single company. So, if you’re running a cross-channel campaign, you’ll likely need to analyse data in multiple clean rooms. In addition, clean rooms are normally run on first-party data, which some advertisers may not have due to the nature of their business. Therefore, the debate over privacy versus usefulness means that clean rooms are more theoretical than applicable right now. A lot of work and compromise must occur for clean rooms to be ready for use in all campaigns.

Micro cohorts: ready for primetime

While clean rooms show great future promise, micro cohorts are the biggest opportunity today for privacy-first, cross-platform campaigns. Micro cohorts deterministically isolate small groups of people without needing cookies, creating the opportunity to scale quality reach.

Even so, there are still challenges. It is difficult to distinguish between office and home IP addresses at scale, and some device IPs may be blocked for privacy reasons, like cookies. Also, creating successful micro cohorts requires significant investment in processing large data sets using complex algorithms. Nonetheless, micro cohorts present a promising alternative in a privacy-protected future.

There’s a lot to take in and debate. And no one solution will fit any individual advertiser. That said, the planning for the cookie-less future must happen now. And there are new approaches that are ready to use today and those that are more wait-and-see. Ultimately, the most important thing to do is to talk to your partners about the best privacy-safe plan for ad tracking for your business that doesn’t rely on cookies.