Tax & Accounting Blog

So You Think You’re a Data Analyst. Maybe Not.

Blog, Business Practices, Marketing August 7, 2014

Data driven marketing is all the rage. However, despite the focus on statistics surrounding trends and campaigns, many marketers aren’t used to looking at data. They aren’t comfortable talking about numbers or building the bridge from data to business application.

Many marketers have lived in a fuzzy world where we “thought” we made a difference or we “believed” our activities helped sales. The technologies available today make subjective statements like that inexcusable. We can and should do better.

That’s why marketers need data analysts on their team—or at least someone with the business-focused mindset that data analysis requires. People who transform marketing data into effective marketing programs must, at a fundamental level, understand what makes the business run. They need some financial background. The need to know which financial levers are important for the business: EBIDTA or revenue? Investment yields or cash flow? Customer volume or customer lifetime value?

Once they understand how the company is measuring its performance, they can apply a lens that’s closer to the target in setting marketing objectives. If marketing is not aligned with the business strategy nor focused on the top priorities of the business, the marketing strategy will be disconnected from the organization’s financial goals. Not good.

How you organize around collecting data also is important. At the Tax & Accounting division of Thomson Reuters, we have had different groups collecting data and information about our customers — website data, customer insights, leads, awareness, and more. We are working to connect the dots into a holistic view, one that aggregates customer data to give us an overall data-driven look at our performance.

The challenge, then, is knowing what to look for — what’s important to the business—and what’s most important to the customer, then understanding how to connect to other data to answer those questions.

Our organization has developed dashboards for such guidance, and we seek to measure three simple areas across the company:

  • Awareness
  • Leads
  • Customer experience

These three areas orient people around a common set of focal points with comprehensive information, rather than looking at various types of data through multiple silos. We hate silos and try to bust through them whenever we find them.

Lead capture is one area where our dashboards are proving especially helpful. They tell us where leads are situated in the buying process — for instance, at the appointment stage, evaluation or trial. This visibility in partnership with our sales teams is delivering fantastic insight.

Recently we discovered that a lot of leads for a campaign were stuck in the appointment phase. The reason is that they didn’t understand the value proposition of moving from manual spreadsheets to automated tax technology. Our marketing strategy had assumed they already understood the value of our product and we were selling features instead of value.

Once we knew what our prospects really cared about, we created a campaign around automated tax technology and published an e-book in a week that laid out the benefits. We asked the analytics team what would be an appropriate number of prospects that we could expect to move on through the sales funnel. By using data to help manage leads through stages of the sales process (vs. a one-shot) we are developing an agile marketing process that moves at the pace of sales because we are understanding what data really matters.

To help ensure you are setting up an effective data analysis capability in your marketing organization, it will be helpful to consider the following points:

  • Define what you want to measure. You need to understand what it is that spells success.
  • Look at the competency of your group to attain those goals, examining people, processes and technology. Processes may be the most complex of these, because they involve not just you and your department but many groups across the business. They will need to change along with you.
  • Don’t get hung up on a deluge of metrics. Analysis paralysis is a real disease here at Thomson Reuters and we’ve worked hard to deliver a treatment that simplifies the measurements we believe really impact the business. Dig deep as you identify what matters. It’s not about the click-through rate; it’s about the attribution of click-through rate to purchase.
  • Be careful not to drown your organization’s executives in data. People will get lost pretty quickly. If you over-present or present in the wrong format you’ll lose support. Understand the right way to visualize the data for each of the people you’re reporting to and how you can articulate what’s important for them to see.
  • Ensure your efforts provide a direct connection to driving the most important business metrics up or down. Your data must provide information that is actionable and own-able.
  • Maintain a reliable cadence of reporting. Marketing should prepare weekly reports just as finance does. Create a regular schedule to show the performance of your campaigns.

In short, data analysis does not mean figuring out what all the obtainable numbers add up to. Rather, it consists of finding the right numbers and understanding how they impact your organization’s financial goals. It also means you probably need some data ninjas to help you apply them in the most effective way possible.

What are your thoughts?

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