Analysts and marketers are recognizing the importance of telling stories with data. For too long we’ve watched data-intensive presentations fail to connect with internal stakeholders and have little impact on decision making. Data storytelling represents a powerful way of bridging facts with emotion to make your insights more engaging, compelling, and memorable for business audiences. However, as you use more storytelling techniques in your data presentations, it’s important to consider five ways you might be inadvertently undermining your effectiveness as a data storyteller.
1. Not knowing your audience
Being familiar with your audience sounds so basic and simple. However, too often analysts presume to “know” their audience and then—surprise, surprise—end up completely missing the mark. If you don’t clearly know what’s important to your audience and what their priorities are, you might as well be spinning a roulette wheel with your presentation. The simple fact is the less you know about your audience, the more likely you’ll fail. You could have a great data story, but it could be the wrong one for your specific audience.
2. Using unfamiliar analytics jargon
Most people don’t live in the analytics tools and aren’t necessarily immersed in the numbers like analysts are. Rather than expecting your audience to understand our language, we need to speak theirs—typically that means putting things in business terms. You must make a conscious effort to translate what you’re going to share into something that your audience will comprehend. In most cases, that means not overwhelming them with references to statistical terms (e.g., correlation coefficients or R-squared values) or analytics tool features such as eVars (SiteCatalyst) or Regex formulas.
3. Providing too much detail
An opportunity to present your analysis findings to internal stakeholders shouldn’t become an excuse for a data dump (some call it data puking). Your audience can only absorb so much information in one sitting. You need to be selective about what you share with them. Analysts often make two key mistakes when deciding what to include in their presentations.
First, they feel obligated to substantiate or defend every insight. While you should be prepared to answer questions, most audiences are going to trust your expertise. If you need a safety blanket of supporting details, move it to the appendix of your presentation and reference it only as needed.
Second, analysts often want to show the steps or process they used during their analysis. Whether it’s an attempt to demonstrate how much effort was spent on the project or display their analytical ingenuity, most audiences won’t care about the steps or processes you used—just the insights you uncovered. To use an analogy, they are interested in sampling the delicious cake you’ve baked—not examining the ingredients you used or inspecting each step in how it was prepared.
4. Leaving out valuable context
In contrast to the previous point, this is where an analyst ignores or leaves out relevant information for their analysis. There are two ways that a lack of context can ruin a data presentation.
First, when analysts don’t have adequate context into what they’re analyzing, they can go down misguided paths with their analyses. For example, if an analyst doesn’t know the promotional discount was recently reduced from 40% off to 10% off, he or she may unnecessarily jump through various hoops to explain why online sales are down this month. Eventually, any data set will surrender some kind of insight after it is sufficiently prodded, probed, or tortured. However, it won’t necessarily be accurate or useful without the right context. As an analyst you don’t want to waste cycles analyzing something that can be easily explained by a simple piece of information that lives outside of the data you’re examining. You want to secure as much context upfront to avoid this type of scenario.
Second, audience members also need sufficient context to properly comprehend the insights you share with them. As analysts, it can be difficult for us to NOT KNOW what we know. Chip and Dan Heath, authors of Made to Stick, referred to this as the Curse of Knowledge. Your audience hasn’t examined all the data forwards and backwards like you have, and therefore, they may not draw the same conclusions without the same context. You need to make sure you don’t overlook vital contextual information that’s in your brain but not in your slides. For example, you may know which types of video content performed better last year, but does your audience know this? You need to insert enough context into your data presentations to help frame your insights.
5. Talking too much and not allowing for discussion
Lastly, as an analyst it’s natural to get excited about the insights you’ve uncovered. However, you need to be careful that you don’t spend too much time presenting your findings and not allow adequate time for discussion. Ultimately, you want your audience to ACT on your findings, not just HEAR them. In most cases, stakeholders will have questions and may need to discuss what to do with your insights. Are you leaving enough time to accommodate questions and discussion at the end of your presentation?
A few years ago I watched a smart analyst deliver a great presentation to a number of senior executives. Unfortunately, he used the entire meeting to present his findings and didn’t reserve any time for discussion. I saw the panic on his face when all of the hard-to-schedule executives start packing up their laptops near the end of the meeting, and no conversation had occurred around what they would do based on his findings and recommendations. Opportunity missed. It took another couple of weeks before he could get everyone back in a room to determine next steps.
Storytelling with data is an essential skill for all digital analysts and data-driven marketers. It can make the difference between insights being adopted or ignored. Don’t let the aforementioned pitfalls prevent you from driving value from the nuggets you’ve discovered. To reiterate, it all starts with knowing your audience. With them in mind, you will want to avoid unnecessary jargon that they won’t comprehend. You’ll then want to determine how much detail and context are necessary so they can fully grasp what you’ve uncovered. Finally, you’ll want to leave ample time for discussion so together with them you can move the ideas forward. Good luck fellow data storytellers!