Four Steps For Diving Into Big Data

IBM's recent study, “Marketing Science: From descriptive to prescriptive” quantified what most marketers intuitively know: while virtually everyone wants to use data to drive marketing decisions, most marketers (82 percent) still rely largely on hunches and experience.

Although experience should never be understated in the art of marketing, adding the science of data and analysis to the mix can unlock enormous potential. Here are four things to consider as you shift toward the cutting edge of data.

1. Evolve your corporate culture

The first step to gaining data/analytics maturity as an organization is wanting to change. Building a data-driven culture is difficult and takes time and energy -- and you can’t get there by simply buying the latest or greatest technology.

Data becomes valuable when it becomes useful, so investing in the people, the processes, and the organizational structure is essential in building a solid foundation on which to grow. Instituting small, consistent, and realistic steps with buy-in from all of your stakeholders will be your key to positive change.    



2. Establish the right technical architecture

Most marketers already have a trove of data they have been collecting in the hopes that they can someday use it. But very few have designed systems that comprehensively track their entire digital footprint and provide data that can be used for strategic analysis and decision-making.

All good analysis starts with good questions, so visualize your end game: What kinds of things do you want to do with your data? Maybe you’re interested in being able to attribute value to each of your channels and optimize your media mix, or maybe you want to understand what characteristics determine your most valuable customers. You will need a host of data points to answer these questions, and understanding what you want from the data will help you determine what data you will need to collect, what method you’ll use to collect it, and where and how it will be stored and accessed. 

Getting this right can seem overwhelming -- especially in a space that is changing and evolving as fast as this one. But just as most executives aren’t expected to do their own lawyering or accounting, most aren’t expected to be trained technical solutions experts or data analysts -- so don’t be afraid to get help. 

3. Understand the business requirements

Getting the right data to the right people at the right time is essential, and it must be easy to understand. Analysis isn’t a matter of handing out user names and passwords to your tools or exporting weekly charts. It’s about defining the metrics that matter to you and your business objectives, the visualizations that will convey the messages, and the processes that will deliver to the right stakeholders at the right frequency.

Defining key performance indicators (KPIs) and tying them to business objectives is critical -- focus on the decision support and reporting requirements that your constituents need to enable and speed decision making. What are the success metrics, outcomes and goals of your organization? What set of performance measures will provide a holistic and accurate view of success or failure against these objectives? And how can you choose visualizations and build dashboards that can help surface the right data in the right way, for the right purpose?

And don’t forget to establish data governance that can explicitly define who needs access to what data at what level, ranging from ownership and responsibility of a particular area to simply being informed and aware.  

4. Let data drive strategy

Once you have the technology, the processes, and reporting in place, you can go from learning how you performed to anticipating how you can do better.

How can I allocate my marketing spend more efficiently? How can I best respond to customer segments through different channels? As you develop your strategy, use your data to do things like lifetime value analysis, sophisticated attribution modeling, media-mix planning, customer segmentation analysis, advanced channel and content testing, predictive analytics, and more. 

Get going -- your investments in culture, teamwork, technology, and strategy can turn raw data into actionable intelligence that can transform your business. With marketing plans based on data, statistics, and good old-fashioned math, you can finally fine-tune and improve those hunches.

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