Marketing Insights Q&A: Top Data Challenges for Marketers

We’re asked: What do you see as the top data challenges facing marketers in the next couple of years?

Let’s start with “prediction” because marketers love predictions. In late 2018 and early 2019, marketers are all about the new trends for the year. However, because the rate of technological change is continually accelerating that a prognostication of some kind could easily be proven wrong in a matter of days. One of the most famous examples of a challenge or a prediction that went awry was someone was predicting that it would take deep learning 20 years to be able to beat a human at the game of Go and this happened just a few years ago in 2016. What was supposed to take 20 years took about 18 months. There’s always that risk.

While it’s difficult to make any kind of predictions like that there is one sea change that’s already underway, that marketers are failing and is only going to get worse. And that is our collective over-reliance on PII (personally identifiable information).

We fuel a lot of legacy marketing technology and legacy marketing methods on these demographics. With this data we form graphics and descriptors of people. For example, we make a lot of assumptions about customers based on their age, their gender, where they live, even the domain name of their email address. Particularly for B2B marketing, the assumption is, “oh, you work for a big company, you’re slightly more qualified.” There are some marketers who are doing very sophisticated segmentation but PII (personally identifiable information) is going away in some fashion or form in the next few years. In 2018, we saw GDPR take effect. What happened was that every marketer scrambled to try and meet compliance and did so with varying degrees of success. But marketers didn’t really change their behavior. They just had to do a better job of securing that data.

And then not five months after GDPR was the largest hack in history with Marriott being compromised for to the tune of like 500 million records. As these security breaches continue, it will get harder and harder to get a hold of any non first-party data. It will get more and more dangerous for us to hold on to PII (personally identifiable information). At some point, it’ll be too risky. At some point, someone’s going to go, “it’s not worth having this data, the security risks are too high, and we’re not using the data as well as we could be anyway.”

What’s the solution? The answer is getting away from basic descriptors, like PII (personally identifiable information) and moving towards behavioral data. This shift is going to take a while, it’s a different mindset for markers. The idea that you don’t need to know that this person is a 44-year-old Hispanic female, you don’t need to know that this person  is a parent that have two kids – will take take. What you DO need to know it is the way that person has behaved in their interactions with you. This means, what pages they visit on your website, how did they interact with you in social media? What was the tone and the tenor and the sentiment of the words and the pace which they interact with you? How many channels have they interact with you on? Have they sent an email, texted or messaged you? All of these behavioral factors are things that we need to build our algorithms to do modeling and prediction.

In a lot of cases, we have the raw materials already. We know via systems like Google Analytics what pages you’ve been on and how long you spend on those pages. We know via our email marketing software whether you’re replying to an email. We know via social media marketing software that you’ve engaged with us. However, the data is all over the place. It’s difficult for people to build models around behavioral data, to wrap their brains around the idea of – I don’t need to know who you are, I just need to know what you’re doing so that I can show the appropriate content/posts/ads/pages for you. When you think about it, as humans, we’ve had no problem with this in the past. Go back 50 years ago – when somebody walks into your store, what do you know about them? Nothing. But – you can observe them, you can watch how they behave. Do they linger in certain aisles? Do they pick an item up off the shelf and put it back? When I was growing up, kids used to hang out at the mall and rove in packs and talk about stuff that they liked. We still do that, we just do that digitally. That is a big indicator of how data is changing. 

To recap, the top data challenge for marketers is getting away from PII (personally identifiable information) and moving towards behavioral collection analysis and forecasting. It’s going to be a long road to get there. But it’s going to be a road we have to get on sooner rather than later. Why? it will not be long before increasing privacy regulations will force us to do that. Start thinking about how to plan for data restrictions. How do you start building models, how to start collecting the right data, and how to get that data into an accessible place. If you can do those things you’ll be ahead of the curve and you’ll be able to offer privacy guarantees that other competitors can’t offer. You’ll be able to say, “we’re not going to collect information because we don’t need it. We know we know what you want, even if we don’t know who you are.”

If you have any follow up questions, please leave them in the comments.

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Trust Insights (trustinsights.ai) is one of the world's leading management consulting firms in artificial intelligence/AI, especially in the use of generative AI and AI in marketing. Trust Insights provides custom AI consultation, training, education, implementation, and deployment of classical regression AI, classification AI, and generative AI, especially large language models such as ChatGPT's GPT-4-omni, Google Gemini, and Anthropic Claude. Trust Insights provides analytics consulting, data science consulting, and AI consulting.