Overcoming data privacy challenges in digital marketing

As the United States enters a new era of online customer data privacy, digital marketers are taking notice.

Both California and Virginia put new consumer data privacy laws into effect in January. The California Consumer Privacy Act and the Virginia Consumer Data Protection Act give customers more rights to protect, alter and limit how their online personal data can be used by companies.

Colorado, Connecticut and Utah also have similar privacy acts going into effect later this year.

Such laws echo Europe's monolithic General Data Protection Regulation, which aims to bring data control back to users by giving them more access to alter or remove personal information held by companies.

Stuart Meyler, president of Beeby Clark and Meyler digital marketing agency in Stamford, Conn., spoke with TechTarget Editorial about how these data privacy restrictions pose new challenges for digital marketers. He discussed how to pivot from capturing personal data and still use relevant material to target desired customer bases, and how automation and AI factor into creative marketing.

Editor's note: This interview has been edited for clarity and conciseness.

How has digital marketing strategy changed over time?

Stuart Meyler

Stuart Meyler: Before, we focused on the technology and became enamored with the variety and depth of data we could access. For a guy like me who came out of database marketing, that was exciting to have all that information, to build really advanced segmentation.

As the segmentation became more granular, we were able to create precise relevancy for even the smallest segment. We focused on becoming more and more Byzantine in terms of segmentation structure and messaging, which worked for a while.

I scored major airlines' loyalty database of all their cookies with thousands of attributes, including where people flew and whether they bought in-flight services. But it was all without users' permission.

We overreached as an industry. Now there's been a pullback through privacy and legislation, making that approach less available -- in some cases, not available at all.

Can you explain how this is a challenge in digital marketing?

One stark example is in the housing category, which is a protected class with legal and policy-driven limitations within the major platforms like Facebook. If you are advertising in the housing category on Facebook, you can't use age, income, ZIP code or interest to reach your intended audience.

Without these specifications, the target audience becomes broad. We're trying to reach people age 55-plus in the upper-scale housing community, but we also have to advertise to 18-year-olds that are unemployed.

How do companies overcome that challenge?

They need to implement creative segmentation. Instead of using large amounts of data to create specific messaging to reach various little segments, use the power of algorithms to create the type of messaging that you need to attract the desired segment.

That will get people to respond, and more responses help the algorithms learn the language of the targeted audience. They'll start to deliver more of your marketing to people that you want to reach.

What is most important to customers nowadays in terms of digital experience?

Customers have really grown to expect relevancy. It doesn't matter whether you're Amazon or Google. Customers have been conditioned to expect companies to anticipate what they need and to respond accordingly. That can be difficult, because it's not easy to be Amazon or Google and predict what your customers want.

How do other companies create that relevancy for customers?

My advice: Don't focus so much on the technology and the 'whiz-bang' wizardry of all that. There's a lot of ways you can make your advertising and your marketing relevant that aren't necessarily technical.

Before you start thinking about CRM feature sets or personalization engines, consider your customers' needs and how your product might be relevant to them. Consumers are good at tuning out things that aren't relevant. If you can't cross that bar, we find that you can't even really start the conversation with the consumer.

Could you give us an example?

It's all about putting the right creative marketing out there and training the algorithm to steer it toward what we want it to do.

Circling back to housing, which is a protected class on Facebook: We literally cannot target anything like ZIP code, which we already know is related to income levels.

But after running on a creative segment basis, we're delivering it over 83% composition. That means we're delivering to 83% of the people we want to reach, which are 55-plus with higher income brackets in certain ZIP codes.

It's all about putting the right creative marketing out there and training the algorithm to steer it toward what we want it to do. That's the approach that's working.

Tell us more about the power of creative marketing.

It all ties back to good, solid consumer research -- understanding what motivates your consumer. We invest money in consumer research platforms that we license on behalf of our clients. What we're trying to get into is, 'What are those unique needs or motivators?'

Sometimes it's, 'Hey, I'm 55-plus; I'm looking to retire. I've sold my house and I need a place to live.' Sometimes they're more emotional in nature. It might be, 'Hey, I've worked really hard, and I'm ready to retire. I want to have a life that I've dreamed of.'

They're different ways of positioning the same thing. We try to understand what these key motivators are, then we test them.

We'll send out different groups of creative messaging. One might be about affordability and loan processing -- all those transactional things that make it easy for you to get this house because we know you're just trying to make it easy.

Another is more dream state messaging, which might include imagery about golf courses and buffets.

We would run those two messaging groups against this audience, and the algorithm will start to see which of these approaches works best. Sometimes they both work because they both might meet different segments of the audience.

How do automation and AI technology factor into this technique?

We use AI and automation to manage campaigns. We have platforms that are infused with machine learning and AI.

Automation tools are managing the budget, changing placement bids and tweaking things like that. People are using generative AI to write marketing copy.

But I'm more interested in AI-supported tools that score the copy -- whether it's generated by humans or AI -- and, based on a predictive score using lots of different copy versions, predict which version will perform best. We've been testing that, and it's been effective.

Mary Reines is a news writer covering customer experience and unified communications for TechTarget Editorial. Before TechTarget, Reines was arts editor at the Marblehead Reporter.