In a recent post titled Data: It’s big now. We get it. (Part I) [1] I discussed the notion of “Big Data” and how marketers can invest substantial amounts of money into the most sophisticated software systems, but the insight and value they get out of them will be limited to the value of the data that backs it and the skills and insights of the analysts. In the following blog post I talk about the importance of making your data visual and how a marketers testing and learning is never done.

Appealing arguments convince people, not numbers

I recently attended the CMA’s Analytics Conference as well as the AMA’s Big Data, Big Difference Virtual Exchange and a common theme throughout both was about making data visual and using data to tell a story. Don’t underestimate the importance of this.

Don’t expect to present your team/boss/client with a bunch of numbers, stats and charts that support your point and expect everyone to jump on board. As a self-labelled analytical thinker, I’m often guilty of feeling that the numbers tell the story and feeling frustrated at times that other people don’t always come to the same seemingly obvious conclusion that I do. Having access to a lot of data empowers us to make better, more informed decisions but it’s normal for emotion to influence people’s decisions. A couple of the speakers at these conferences touched on this and I think it is worth re-stating. Make sure that you can present your analysis, conclusion and recommendations in a concise and visual way to appeal to your audience.

Sometimes numbers are just numbers

Numbers can be a perplexing medium to work with, so use scrutiny when reviewing data and reports. We’ve often had a mentality in the past that when the data is available, we need to derive insight from it and we need to “work with what we’ve got”. Sometimes only part of the story is told by the data you already have. Look for meaning in those numbers but also think about what data you could have or what you need in order to get the full picture, and then take a problem solving approach for how to get it. Diane Findlay, Manager of Compass for Success ( [2]), spoke at the CMA Analytics Conference about addressing the problem of transforming the database they had into the database they needed. By creating and sharing insightful reports that told a story about how students were doing, they were able to positively influence the attitudes of the students and the network of schools that they support. This has resulted in improvement of student performance.

Always Test! Always.

Every execution should include an A/B test plan. This is still the truest form to capture insight about how a marketing treatment is performing. Continue to summarize the learning from each test, think about why a specific treatment performed better than another and continue to test those assumptions.

In order to get the best results from investments in business intelligence software, organizations should be defining their marketing problem first, and then using the software as a tool to analyze, find insight, and implement new solutions (with continuous measurement and adjustments, of course).

Are there any old practices you feel are being neglected as we shift to big data analytics? Add your comment below.

May your Data Mart runneth over with insightful metrics!

[1] [2]