Are You Making a Mistake with Your Data-Driven Marketing?
The prevalence of data, and its promise to provide measurable, actionable results for businesses have created an unprecedented demand for us (marketers) to adopt data-driven mindsets. Thanks to improved software and analytics, we are able to capture hundreds, even thousands, of metrics on our marketing activities on a day-to-day basis.
The prevalence of data, and its promise to provide measurable, actionable results for businesses have created an unprecedented demand for us (marketers) to adopt data-driven mindsets. Thanks to improved software and analytics, we are able to capture hundreds, even thousands, of metrics on our online marketing activities on a day-to-day basis.
The intensity and availability of data only stands to increase. In a recent study, 78 percent of marketers reported feeling pressure to become more data-driven*. Although this is an admirable goal, there are consequences to becoming too data-driven.
These recommendations are for teams looking to align themselves around data, while avoiding common stumbling blocks:
Uneven adoption and use of data across teams. Understanding shared metrics requires education. Make sure to inform your team and peers about the rationale for adopting a new metric, or using it as a reference point for success. By ignoring this step, you introduce friction between teams or their members.
Not qualifying data sources. When adopting a new tool or piece of software, include key stakeholders in the evaluation process. Roll out the tool by educating a broader group than just those using the tool. When data from the tool is referenced in the future, every team member should have context for what that data point means, and how it is being used.
Using data selectively. If you have metrics to report upon, choose them before starting project and use them consistently. If you investigate a problem by digging in to your analytics, do not selectively use data points that reinforce your hypothesis. Instead, consider all data points, including the ones that support and contradict your instinct. Develop a theory and propose a solution that takes into account the outlying metrics.
Looking at only quantitative, not qualitative, data. Quantitative data encompasses the “what,” but doesn’t always illustrate the “why.” Understanding product-market fit or the leaks in your marketing funnel should be informed by both of these data types. In many cases, your choices on what to change will be informed by this qualitative feedback. Leverage customer surveys, user testing, A/B testing tools, and interviews to collect feedback on your marketing messaging, website flow and content.
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*Data taken from a 2013 Teradata study of 2,200 marketers.