4 Things Every CMO Should Do Before Approaching IT About Big Data

There are several contradictory Big Data misconceptions floating around the corporate cosmos. First, that marketing owns Big Data and can run projects without IT. Second, that IT owns Big Data and is slow to deliver it to marketing. The truth is, that while IT departments are vital in designing, implementing, and managing Big Data projects, both IT and marketing must work together to transform a project into a viable revenue source.

The database administrators, programmers, and data scientists at work are the ones responsible for gathering insights from a company’s data sources. But these insights echo across departments and few teams are as attuned to them as marketing. In reality, 45 percent of Big Data deployments are for marketing initiatives, employed to grasp customer satisfactions, demographics, and preferences.

You’ve likely heard the whispers (or shouts) about Big Data’s potential, how it’s the holy grail of marketing—and it can be. But to uncover this information and take action on it, marketing needs to partner closely with all departments, especially with IT. Yet this is where many companies run into roadblocks. When implementing a Big Data project, there’s often a disconnect between CMOs and the IT department.

IT can go off and develop as many Big Data initiatives as it wants, but without the necessary insights from the marketing team, those projects will never translate into sales. But if each plays to its strengths, with CMOs entering the Big Data conversation with logistics upfront, then IT’s structural knowhow can bring that solution to fruition.

Here’s what every CMO must do before approaching IT about a Big Data project:

1. Provide defined use cases

Nothing bugs Big Data engineers more than executives spouting high-level jargon they heard on CNN. If you want to drive a successful initiative, do your research before entering any conversations with IT about your project. Assemble your team and create as many use cases as possible. The more use cases you develop, the better and more efficiently IT can architect the right solution for you. Use cases have a direct impact on the tools IT will use to implement your Big Data project—and if they’re not clearly defined, IT will not deliver a successful project.

 2. Plan how you’ll transform data into sales

IT can pull up a crystal clear picture of each of your customers and what they might be interested in buying, so it’s easy for CMOs to get wrapped up in the promise of Big Data. But CMOs need to stay grounded in the realities of the project, remembering that any knowledge gained is useless without a way to put it into action. That not only requires clear communication with IT, but with the rest of the organization. While it’s great to know, based on social media interactions, that customers in Dallas prefer stripes, CMOs need to figure out how to transform that information into sales, and this requires an open line of communication between IT, marketing, store managers, inventory managers, purchasing, and so on.

3. Show IT the money

IT doesn’t have the money for Big Data projects. In a lot of cases the IT budget is stretched thin between security, infrastructure, licensing, point-of-sale systems, and more. So if you want to produce a Big Data project, you need to bring the funds with you. Start with the CEO. In most companies, the CEO will be the only executive willing and able to allocate Big Data funds, but only if CMOs can show a measurable ROI.

4. Remember: It’s all about ROI

The most important step CMOs need to take into account when developing a Big Data project is proving ROI. That’s what’ll secure financing from CEOs and give IT the green light to get started. There are two ways to prove ROI. First, investigate whether the project will reduce bottom line costs. Many Big Data projects can improve operational procedures, and, in turn, reduce upkeep spend. In addition, uncover potential top-line revenue streams, such as Big Data insights that can be transformed into sales.

To define potential ROI, CMOs and IT departments must work together to develop and run a small, proof-of-concept test. Through this simulation, CMOs can uncover insights and see if they have any commercial value before running a large-scale project. By assessing a project’s potential revenue and savings—then subtracting the cost of the project as a whole—CMOs can uncover predicted ROI.

Big Data is the flashy new tool all marketers are scrambling to get their hands on. Yet to properly develop and implement a valuable Big Data practice, marketing must partner closely with IT. To avoid common miscommunications and capitalize on Big Data’s actually potential CMOs need to do their research up front. They must identify use cases, think through implementation, secure a budget, and prove ROI in order to transform a fancy idea into a money-making reality.

Samer Forzley is the VP of marketing at Pythian.

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