Data reporting can be challenging. When you've immersed yourself in numbers and found so many compelling proof points, it quickly becomes fascinating to you. But it's just data to everyone else! The only way to effectively report stats is to use the data to tell an engaging story.
There's an old saying in sales: Facts tell. Stories sell.
It's true. You can list facts and figures all day long. What motivates people to act, however, is when they can connect the points to their situation. It's the story the data tells and not the data itself that converts.
The problem with traditional data is that it's just numbers. It can be sliced and diced in so many different ways, and it can tell other stories depending on how you're using it.
What makes data important is perspective.
Here's another all-too-common problem: you're not tracking the right things, or you're not using the correct data sources. Before you even begin to think about how to use the data you've gathered, make sure you're collecting the right information to measure your KPIs.
A focus on data reporting and analysis is one of the five skills every marketer needs to be effective in today's industry. That's just step one, however. It's what you do with the data that matters.
If you're boring people with a recitation of numbers, they'll tune you out. You've got to take the data and tell stories.
We like to think of ourselves as logical. The truth is that humans are emotional creatures. Some studies have shown that as much as 90-95% of decisions are made subconsciously. (Inc.) For your data to make an impact, you need to appeal to emotion more than logic.
After completing your data analysis and drawing conclusions, you need to think about your data reporting purpose. Is it to report on past progress? Is it to motivate someone to act? Are you trying to convince someone? Decide your goal and start to build your case.
Now you've got to find your narrative.
In journalism, they call it "the hook." What's the thing that will get people to pay attention and remember the information. For example, a reporter telling the story of the number of businesses permanently closing due to the pandemic might start by telling the story of a family-owned business that's now shut its doors after three generations.
By humanizing the number, it's more powerful when they tell you that 800 small business like that one are closing every day (Yelp)
The most compelling data reporting presentations don't bury people in numbers and data points. They pull out the fundamental facts to support the narrative. They keep things at a high level and save the details for people that do want to investigate further.
Data visualization is a critical storytelling tool. Showing how many people recognize our brand and associate it with quality right now is essential. What's more important is whether the strategies we've put in place have improved our position over the past year. A chart comparing the two is the way to go. Perspective is king.
Here are a few essential tips:
Here's one other thing to think about. Ditch the traditional charts and graphics and find compelling ways to visualize your data. Instead of using numbers or pie charts to show the number of satisfied and dissatisfied customers, use happy faces and sad faces. The more attractive your visualization, the more likely the information will resonate.
Marketers shouldn't just conduct business intelligence for its own sake. At the end of your data reporting, always summarize the key takeaways and explain the action you want someone to take.
We started by talking about your purpose. At the end, it's time to go right back to the start. What do you want someone to do once they've seen your data? Don't leave them guessing.
Becoming a great data storyteller also requires one more essential strategy. You need to understand your audience. For example, if you're presenting to your CEO and they have limited time, you'd be better get right to the point.
If it's your sales team, you need to demonstrate how they can use the information to make more sales. Take the time to think about the right approach for decision-makers and what you want them to do with the data.