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Tools or Platforms Don’t Make a Strategy

Eric BruceMarch 22, 2019

It happens at least once a week, but usually more often. The question comes up. “Do I need a DMP (data management platform)?” Or sometimes it takes different forms. “Should I get a CDP (customer data platform) or a DMP?” Even Acxiom’s own award-winning Unified Data Layer (UDL) comes up. “Do I need Acxiom’s UDL or a DMP or a CDP or …?”

If you’re in marketing or advertising, you’ve probably seen some version of the famous LUMAscape that’s updated every year, showing literally thousands of marketing and advertising technologies to satisfy just about any technological need.

Years ago, when I worked at an agency, there was a senior data analyst who had seen and done it all. He was a thoughtful man who taught me a lot about how to think about the business. He had a real talent for data and was creative when it came to solving client problems. When we would all sit down to discuss the challenge of the day, he would cut right to it: “We can do anything, but what are you trying to do?”

It’s the simplest question, but powerful – and one skipped too often.

Of course, there are limits to technology and how data can be organized and acted on, but his central point is critical. There’s a way, using data and technology, to accomplish just about any task. But the real point of his question is: forget the data, forget the tools, at the end of the day, explain what result you want to achieve. Explain the business problem or problems you want to solve.

Across the more than 7,000 options out there, there is likely an application or platform to do what you want. There are highly skilled data analysts and engineers who can slice and dice data any way you like. The real question is: Do you know what you’re trying to do? It’s the difference between “tactics” and “strategy.”

“Strategy.” What is your data strategy?

It’s just that easy. Except it’s not, right?

A data strategy isn’t developed by one person in a silo. In any organization, there are numerous stakeholders with questions and needs who deserve input. Perhaps in your organization, IT is responsible for any technology integrated with the brand’s systems and data governance. Marketing is probably responsible for content and media plans, and within marketing there are possibly sub-groups like customer loyalty, ad media, search, social media and more.  The CRM team could own the customer file that marketing relies on. Your organization might look like this, or it might be simpler or more complex.  Regardless, your data strategy should be defined by your brand’s leadership in terms of the business goals they want to achieve as well as the needs of the stakeholders responsible for their respective competencies.

Your company’s overall objectives and the needs of the people who “run the ship” should form the basis of your data strategy. When you formulate strategy first, the types of tools and data you need become clear.

“We need to grow our member loyalty base by 25% this year.”

Leadership defines business goals, but your data strategy takes shape by evaluating what it will take to achieve them. For example:

  • What do I need to know about my customers to identify prospects? What do my best customers look like? Do I already have this data, or do I need to acquire it from somewhere?
  • What methods of acquisition are most efficient at a reasonable cost?
  • On which platforms should I buy ads, and how do I know which ones are working?
  • How do I measure success? What metrics will tell us we are moving the needle? Am I collecting that data?

Answering questions like these determine the data you need to collect, where it needs to go, what you need to test, etc. Ultimately, those answers guide you to the tools you need. And the answers will differ from brand to brand. There isn’t a “one size fits all” solution.

The right answers may even differ from year to year or even faster! As we’ve seen, technology is constantly evolving. So are a brand’s needs. Data is being generated by more devices in more volume than ever; naturally, adaptability must be part of your data strategy.

As you become more sophisticated, so too will your data and the tools that generate, collect, and activate it. Your data strategy should strive to be “future-proof,” which means choosing partners with decades of experience and flexible tools. That said, there is no “easy” button in martech. Even the most “turn-key” solutions will need tuning, optimization, and maintenance.

Before you ask about the data you might need or if you should get the hot new tool, check how those questions align with your data strategy. Or maybe ask some professionals to help.