Data-Driven Marketing | Step Three: Untangle the Data Hairball

by Lisa Arthur

Previously, I’ve blogged about how to create a strategic plan for data-driven marketing and how marketers can tear down the silos that prevent change. I’m now ready to share my third step to data-driven marketing covered in more detail in my “Big Data Marketing” book – untangle the data hairball! First you might be asking, “What exactly is a big data hairball?”

I use the term “hairball” as a metaphor to define a complicated jumble of interactions, applications, data and processes that can easily accumulate in a company without proper sources and methods for handling big data. It’s different than the “data deluge” or the “sea of data” — other terms you might have heard before — because the data hairball would be the shoreline after a tsunami, prior to reconstruction.

I see the data hairball as something that represents both a promise and a threat behind big data and online channels. The data hairball can be a “promise” because there’s an unlimited amount of value inside it. The hairball can also be a “threat” because, for some companies, it can become the single biggest obstacle to them improving customer engagement.

How can you untangle your data hairball and make the most of new data-driven marketing strategies? By taking things one step at a time. My book includes detailed information on the exact process, but there are also eight steps you can consider at the most basic level.

1. Define the vision. What does your company’s ideal customer experience look like? Figure out what the customer journey looks like right now. Next, draw a picture of what you’d like it to look like. Your goal should be making your vision a reality as soon as possible.
2. Outline the questions to answer. Which business questions could your data answer? Too many projects fail because they never had a defined outcome. If you aren’t sure what questions to ask, set up a discovery session with key stakeholders who can help you generate some.
3. Assign the right team with the right sponsorship. Bring together smart people who “get it. “As a Harvard Business Review article highlights: “Data gives you the what, but humans know the why.” Make sure you have senior leadership on your side. Go deep into the organization, across multiple departments and geographies, to get their buy in. Everyone should be open to challenging the status quo whenever necessary.
4. Identify the data requirements. Do you understand what types of data you’ll need to access to be able to create your desired customer experience? Look at the data you have today, and then map your future needs as they relate to your present abilities. If you find any gaps at this point, don’t worry. Move on to step 5.
5. Find the sources of the data you need. Take inventory across the enterprise of what data is available and where it’s available. Other departments (like customer support, R&D, operations and inventory management) may be collecting and storing data you could use but didn’t know about before. Add this information to the picture you’re in the process of building. Next, look at the remaining gaps and determine what additional data you need to collect.
6. Identify and ready one source of truth. Most companies use a combination of technologies to achieve a single source of verified data or the “truth.” These enabling systems usually include a data model or organizational structure, an enterprise data warehouse that becomes the single repository for organizational data, a big data analytics discovery platform that collects structured and unstructured data for analysis and insights and, finally, a master data-management solution to build one source of customer information called the “golden record.”
7. Consolidate, integrate and iterate your data. Once you’ve got one source of the truth, you’ll need to bring all the data together. Start by consolidating and integrating the data to create the strategy, campaigns and initiatives to improve the customer experience. Complete the process of unraveling this part of the data hairball by developing a series of new processes to use going forward, and add governance policies based on what you learn.
8. Test, expand and evolve. Don’t forget to measure and analyze your progress at ever step of the way. Start by answering the business questions you wrote in my article, Step 2: Tear Down the Silos, and verify that they’re actually the right questions. Deliver a few quick wins, and identify any landmines you’ll need to address before you can move forward. Chart out critical points along the way where more data will be available to improve a particular customer interaction or campaign, and then test those, too.

An iterative approach like the one I’ve outlined can improve results and build confidence your data. The key here is to start small. Small-scale, pilot projects are the perfect place to start because they allow you to test your data strategy’s feasibility with fewer resources and less risk than large projects allow. Small-scale projects also keep you from getting anxious about the size of your data hairball. Focus on untangling the hairball one strand at a time. Try new things, and learn along the way. Keep untangling the knots in the hairball one by one, and you’ll soon notice that it’s dwindling!

This is the third post in a series of steps to achieving digital marketing success by Lisa Arthur. Click here for step one and here to read step two.

Hear more marketing advice from Lisa in her exclusive interview with C-Suite Network Radio.

Lisa Arthur is the Chief Marketing Officer for Teradata Applications, the leader in integrated marketing software. She meets with thousands of CMOs and marketing professionals annually through public speaking and events. Learn more about Lisa’s book, “Big Data Marketing,” and follow her on  Twitter @lisaarthur.