Three small steps to Big Data adoption

Perhaps it’s stating the obvious to say that most marketers would like to be more data-driven in their approach. According to a recent study by Columbia Business School, 91% of senior corporate marketing executives (and 100% of respondents who are CMOs) think that the most successful brands are or should be using customer data to drive marketing decisions to engage their customers more effectively.

Most marketers, however, face a number of hurdles when it comes to getting started with integrating Big Data into their current data strategy, including not collecting the data they need, having too little information, lack of ability to integrate data across the customer journey, infrequent data collection, and more.

Here are three initial steps you can take as you figure out what to do with all that data you’re now collecting (or will be gathering soon).

Automate your data intake. Using Big Data for meaningful insights can feel a lot like searching for golden needles in a field of data haystacks. All sorts of data has been stacking up: email activity, site visits, audience metrics, CRM details, social activity, online ad exposure, purchase history, direct mail, segmentation details, etc. But to get relevant, actionable information you can actually use, you need to not only capture the information, but also pull together the appropriate data sources to support meaningful metrics. In a best-case scenario, marketers can integrate all their data using a single master data warehouse of customer/prospect information, as well as automate data collection in real time. Doing so can enable the automation of updates and responses to what’s become known about each individual person in the system. This requires the use of a data management platform solution, preferably one with seamless integration of details across channels, sources, touch points and device types.

Create a plan. When transitioning to a Big Data approach to your marketing, start with specific goals you hope to accomplish. Typically, these will be measurable and attached to some aspect of ROI. Next, create a roadmap of the data you need to help take you there. Mapping it out will help you stay focused so you’re not chasing new and possibly meaningless metrics instead of addressing foundational metrics that will actually impact your goals.

Having a roadmap will also keep you from feeling overwhelmed in the process. Plus, when you connect with data scientists or analytics/technology partners, that initial plan will help frame your conversations and approach, helping to increase the efficiency of the engagement. General goals might include: increasing customer retention post-sale with enhanced targeting; reaching specific individuals based on social media shares; improving the cadence of ads to optimize media spend; finding the right mix of content and channels to shorten the selling cycle; and more. Clear goals are essential to developing a Big Data strategy that can give you the results you’re looking for.  This also helps demonstrate the measurable impact of a specific approach.

Build your team. Now that you’ve got your plan in place and the technology to piece together your multiple data sources, you’re still missing the most important part: the people. Big Data can offer significant returns, but it does come with some additional investment in creating a team to support it. You basically have three options: hire, inspire, or partner. If you choose to hire, know that data scientists and statisticians are in short supply, but they may be available for you to bring in-house for the right price. If you want to go the “inspire” path, that means finding people with talent within your own organization who can rise to the challenge of Big Data. If you like the idea of promoting from within, look for people with strong statistical skills who also have a love of code and experience with software development. Strong communication skills don’t hurt either. The third option is to partner with an outside firm or consultancy that specializes in actionable analytics, cross-channel metrics, and targeting strategies. When you’re just starting out, having a trusted advisor can help you get up to speed faster by shortening your learning curve.    

Remember, it’s important to lead with data, not hunches. When it comes to your customers, are you relying on data or do you still rely on intuition when making decisions? If it’s the latter, you’re not alone. Hunches, however, are not a reliable source for decision making—no matter how long you’ve used them. Using Big Data for decision making not only improves the customer experience, it gives you a clear, more complete view of each customer, and allows you to communicate with enhanced relevance.

Patti Renner is director of marketing at Knotice.

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