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Jellyfish is a marketing performance agency, helping brands navigate the changing privacy landscape. Here, the company’s VP of data science, Di Wu, shares three actions brands should consider when shaping their privacy-safe strategies.

A Black woman with short, dark, curly hair, wearing a white cowl-neck sweater and black pants, safely browses and reads product reviews on her mobile phone.

The customer is at the heart of every good marketing strategy. And, in today’s privacy-first landscape, many brands want to understand how they can build consumer trust while continuing to deliver personalized user experiences. What’s more, they want to know how they can drive marketing performance when the tools they’ve traditionally relied on have begun to adapt to new standards.

As a marketing, technology, and data partner, we’re asked this question every day at Jellyfish.

Not too long ago, we were having almost daily conversations with our clients about sifting through mountains of data to stitch together the user journey with every possible touchpoint to create a holistic view of the consumer. However, because of changes to data-collection standards, that’s a lot harder to achieve today.

But that isn’t necessarily a bad thing.

Instead of seeking out every piece of data available, we’ve seen top brands focus on collecting and measuring what matters to build a media strategy based on consumer trust and consent. And they’ve seen great results.

Here are some things brands should consider when building their privacy-safe strategies.

Bring the right teams together

In our work, we consistently observe silos within and between teams, which can lead to operational inefficiencies, like silos within the data itself, making it harder to see the bigger picture. These silos can also create privacy risks. For example, a team could be storing data that is no longer necessary.

Brands should seek to involve all facets of the business, including legal, business intelligence, marketing, and engineering, in conversations dealing with privacy and data-management strategy. To clarify leadership responsibilities, bringing in a data privacy or chief compliance officer, for example, can help to set the right tone and unite teams.

Top brands focus on collecting and measuring what matters to build a media strategy based on consumer trust and consent.

Upskilling your team and bringing the right expertise into the mix can make a big difference. For instance, data clean rooms, such as Google Ads Data Hub, help to distill granular campaign insights and attributions. These data clean rooms go beyond what the standard reporting platform can provide, but using them effectively requires skills across digital marketing, data science, and engineering.

Prioritize responsible data collection

Brands we work with have already seen great results in moving away from cookie-based measurement. One upside of dropping the cookie: Businesses are immediately prompted to think about all their marketing more holistically.

Collecting high-quality, consented data, as opposed to high-volume data, is now a smarter strategy. In a world where automation will be more important than ever in measurement and activation, it makes better sense to start with a high-quality data set. Not only that, there’s less risk associated with data storage and management at a practical level, where privacy is concerned.

Privacy should always be at the top of mind for the business. When it comes to marketing activities, putting privacy into the regional perspective is especially important. Each regional context and its associated laws will influence and guide your campaign’s data collection and management practices. For example, if you’re operating in both the U.S. and Europe, you need to consider the General Data Protection Regulation, the California Consumer Privacy Act, and other emerging pieces of U.S. privacy legislation.

Of course, responsible data management is of the utmost importance. We start a data management audit with a list of questions like:

  • What data is being collected?
  • Is there a legal right to its collection?
  • Has consent been provided?
  • Where is the data stored?
  • Are data sources centralized and organized in a logical way?

From an implementation point of view, it’s essential to consider data encryption, backups, data access, and control to ensure confidentiality and network security. Databases need to be flexible enough to allow users to opt in or out of certain features, and they should be able to accommodate any expiration or retention periods associated with the data. The best way to ensure that the platform can handle these features is to adopt a privacy-by-design approach and consider all these factors as early as possible.

Adopt a culture of experimentation

Testing is the only way to determine how efficient your marketing is. We’ve seen the most effective privacy-forward brands try multiple experimentation approaches with their first-party data to find what works best for their goals. When we experiment with new approaches, it’s best to adopt a robust data-driven framework to evaluate how well it benchmarks against our goal.

In one case, the client faced challenges in measuring the effectiveness of connected TV (CTV) ads for both online and offline businesses due to the limitation of cookie tracking. By leveraging geo-lift experiments, we identified similar geographic areas and adjusted CTV spending based on the test design. Through testing, we were able to demonstrate the impact of CTV on key business objectives, such as revenues and engagement goals, which helped the client to test different strategies, optimize media spend, and reduce cost.

Maintaining the status quo is simply not an option in today’s ever changing privacy-centric environment.

Outside of geo-based experiments, we also experiment with running regression-based attribution (RBA) and marketing mix models (MMM). MMMs ensure that we can make accurate comparisons across investments and measure the effectiveness of advertising spend over time. RBA models supply actionable insights for optimization without relying on cookies.

There isn’t a one-size-fits all experimentation approach, and experimentation can expand beyond return on investment. Brands should also use experimentation to make sure that consent forms and other customer-facing assets are formatted to be most effective.

Maintaining the status quo is simply not an option in today’s ever changing privacy-centric environment. What is safe and functional today may not be the same in the next year or two. We need to keep adapting, experimenting, and looking ahead.