Voxpopme 8: Two key tips or tricks for communicating insights that resonate with the C-Suite and drive real results


Along with a group of market resevoxpopme logoarchers from around the world, I was asked to participate in Voxpopme Perspectives – an initiative wherein insights industry experts share ideas about a variety of topics via video. You can read more about it here or watch the videos here. Viewers can then reach out over Twitter or upload their own video response. I’m more of a writer so you’ll catch me blogging rather than vlogging. 🙂

Episode 8: Share two key tips or tricks you have for communicating insights that resonate with the C-Suite and drive real results.

Alrighty, tip number one: Sample Sizes.

The reasons for choosing sample sizes are a foreign concept to many people, leaders included. Many people depend on you to provide helpful guidance when it comes understanding what an appropriate sample size is, the drawbacks of those sizes, and how results can be interpreted given those choices. One tip I’ve used is to give them specific examples of what might and might not be statistically significant when the results do come through. For instance, rather than sharing the margin of error around a specific sample size, instead I’ll say something like:

With this sample size, a result of 30% would be statistically different from 37% but statistically the same as 36%. Are you prepared to choose a winning concept that is preferred by 30% of people rather than by 36% of people?

Tip number two: actionability.

As someone who loves raw data, cleaned data, charted data, graphed data, and tabled data, sometimes it’s hard to take the next step and make the data useable and actionable. But business leaders don’t always care about individual data points. They may not even be concerned with summaries of the results. What they really want is your informed opinion about what the data actually mean, and the appropriate options that should be considered as a result of the data. So, beyond reporting that 30% of people like a certain thing, use your understanding of the rest of the results to indicate why they like a certain thing, why they might not like it, the implications of moving forward (or not) with that thing, and how that choice might affect other products on the market already. Take the data as far forward as you possibly can in order to give them fodder to spark further ideas.

Bonus tip!

Know your own weaknesses. I know that data visualization is not my strength. When I need data to be visualized well so that it is understandable by everyone, from junior to senior and expert to newbie, my only option is to find an expert. And here’s an example of how an expert would illustrate missing data. I would have never thought to do it like but look at how effective it is. It’s worth the extra cost.

http://www.thirdway.org/infographic/the-absurd-way-we-report-higher-ed-data

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