Data-Driven Decision Making

by Monica Paici, Internal Marketing Director, PIN Business Network

As a data-centric company, it was only fitting that we ended our weekly all-hands meeting this morning with our founder professing the power of data and using that data to make decisions. It was suggested that a client who was experiencing massive success in garnering leads, allocate more spending towards AdWords and back-off on Facebook spending. The suggestion was met with a resounding, “not without the data to back it up.” Using smart actionable data rather than hunch-based decision making will lead to a higher success rate and best of all, it’s trackable and transparent.

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It’s not that we haven’t used data for years to make marketing decisions, it’s just that we often haven’t been able to use that data as efficiently and concisely as we wished. We haven’t maximized the power of our data.

The traditional marketing footprint is very much a hunch-based process. You cast a wide net and you “spray, pray & hope” that the leads will come in, people will turn up at your door and you will sell them your goods or services. A data-driven model uses a 1-to-1 marketing approach to reach the right people the way they want to be reached.

Sounds simple, right? Segmenting your audience, delivering the right messages to the most receptive audience, understanding your customers, etc. As marketers, we know the power of the data we have, but how do we unleash that power and make it truly actionable?

Believe it or not, it all comes down to math. The power is in the science. Taking your data and using algorithms to turn big data into targeted marketing campaigns. Using math calculations and science to find people who look, feel and act like your current best customers. Data-driven marketing can build comprehensive portrayals of your customers and you can use those personas to drive customers to your site or ad messages across the digital platform.

So what’s your next step? According to Jeremy Waite, Marketing Evangelist at IBM, marketers should move beyond big data and look to dynamic data. The 5 V’s of “dynamic data” are:

1) Volume: How much data should you really be measuring?

2) Variety: How many different kinds of data do you actually need / from how many channels (and how much of it is actually useful)?

3) Velocity: How fast is your customer data traveling? (Understand this in order to make sure you respond within your customers expected response times).

4) Veracity: Is your data accurate? (Are you sure?)

5) Value: Capturing valuable data is important, but make sure that you are creating more value for your customers than you are capturing.

Answering these questions, examining your answers and then making the appropriate marketing decisions using this information, will turn vast amounts of data into actionable strategies. Bottom-line, use data not guess work. If you don’t have the data to back it up, search, gather and mine what you have access to and then turn to math to find the answers.