With so much data to process, it can be tempting to view the slightest variation in ROI from one channel or campaign to another as evidence for a total shift in approach. As a smart marketer, you must know when to ignore this impulse.
Data is only as valuable as your understanding of it. To know what to do with your analytics, you need to consider what they are really telling you. What information is significant and what is just noise?
For a finding to be statistically significant, it must fall outside patterns of expected variation. Statistical significance has a specific mathematical definition, which your data analysts should employ.
For marketers who are not responsible for the math, the concept is still crucial. In order to gain valuable insights from data on a specific marketing campaign, you first need a baseline reading. What does customer engagement look like before you implement a new campaign? How has it fluctuated over the past year? Use these markers as a standard of comparison for the data you gather from that new campaign.
Similarly, data from too small a sample cannot be used as a basis for larger predictions. Consider this when performing market testing of all types.
Variation in the effectiveness of your marketing can indicate a number of things. It may reveal that a given campaign successfully tapped into a cultural “moment,” or show that a campaign misjudged your audience. But your findings may also reflect outside factors. Learning to separate the things under your brand’s control from the background noise in your data is crucial.
Keep an eye on data about your competitors and the larger market, as it can offer insight into when gains or losses fit into a larger pattern or are specific to your organization.
Data can be fascinating in its own right and serve as a window into the ways people behave. But a savvy marketer must be able to spot the meaningful data points in a sea of information. Stay focused on learning about your target audience and the things that move them.
How do you interpret data insights and use them to shift your marketing strategy?
Photo Credit: Sebastiaan ter Burg via Flickr Creative Commons
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