If successfully operationalizing data across your business is a goal (if it’s not, it should be), there are three equally-important steps that will need to be taken.

First, there is the technical work of unifying, cleaning, and structuring data before using algorithms and calculations to identify trends and patterns or make predictions. This is what most of us think of when we hear the phrase ‘data analysis.’

Secondly, you need to take that work and draw out the most important insights, prioritizing the most important information to hone in on the most actionable insights discovered. And, finally, you need to tell a story with the data.

Without a narrative, presenting to a board or leadership, or inspiring your team members to act on the insights drawn is all but impossible. Rich storytelling wins hearts and minds and builds trust in the data, two core components of creating a truly data-led organization.

In this blog, we’ll share what data storytelling is and why it matters, how you can tell a compelling story with your data, and a checklist for effective data stories.

Data storytelling definition

Data storytelling is about crafting a narrative from your data. It often comprises both a written or verbal story as well as data visualizations, descriptive imagery, or even video material.

There are all kinds of applications for data storytelling, from talking through a dashboard on a weekly team meeting to building a case for a major new initiative with your leadership team or board. No matter how routine or simple, the act of crafting a compelling narrative from the numbers could be the difference between winning the room or losing it completely.

What is the difference between data storytelling and data visualizations?

Make no mistake, data visualizations play an important role in data storytelling. But they are not one and the same.

Data visualization is all about displaying data in charts, graphs, maps, tables, infographics, and other visual styles to give people a snapshot of the data being displayed. Data storytelling brings these visualization techniques together with a written, audio, or video narrative to better communicate the story behind the data and persuade your audience to take action on the insights or change their opinion.

There are many different ways to visualize your data and the type of visualization you choose can play a major role in how your story is communicated. Choose wisely and, remember, the simpler the better.

Why is storytelling with data so important?

Storytelling is one of the most powerful teaching tools we have. Humans have been telling stories for as long as they have walked the earth, and with good reason. A story is the most efficient, effective, and sticky way to communicate an idea or set of ideas.

In an article from 2021, Harvard Business Review breaks this down in psychological terms, sharing that when we hear stories, three important parts of the brain are engaged. This includes the amygdala where we process emotions, the Wernicke's area responsible for language comprehension, and mirror neurons which play an important role in developing empathy for others.

When these three parts of the brain are engaged, we are more likely to commit what we’re hearing to memory. Numbers alone, on the other hand, are more likely to go in one ear and out the other. Of course, no matter how compelling your story is, when you’re talking about data analysis, you’re going to want to back your story up with numbers. But leading with a story is more likely to evoke empathy, emotion, comprehension, and long-term memory.

How to tell a story with data

Now you have your what and why, it’s time for the all-important how. When you’re first starting out with data storytelling, it can feel overwhelming. You might have an idea of the hypothesis you’re hoping to prove, the opinions you’re hoping to change, or the project you want to start, but the first step feels elusive.

This simple step-by-step guide will help you craft your narrative.

Step one: Identify your primary goal

It’s easy to get wrapped up in the numbers and wind up with a bunch of disconnected insights and numbers. To avoid this, start by composing one question you want to answer or a hypothesis you want to prove. This will give you a clear north star to work towards as you progress.

Your goal could look something like this:

• Hypothesis: Investing more in loyal customers will result in great revenue for the holiday period

• Question: Where in the customer journey are we losing the greatest volume of revenue?

• Hypothesis: Customers who have been repeatedly exposed to our sustainability message spend more than those who don’t.

• Question: Which types of content are playing a role in the middle and bottom of the funnel?

Step two: Unify, structure, and clean your data

With a primary goal in mind, you’ll have a better sense of the types of data you need and how they may work together to ultimately prove your hypothesis or answer your questions.

In many organizations, data is siloed in teams. Breaking down these silos is crucial to getting the whole story and uncovering actionable insights. Platforms like Ortto can help you do just that. With Ortto, you can integrate your data from marketing, sales, support, and product and use it to filter your audience and create segments, and build reports and dashboards. This means you can get a granular view of your customers’ activities, platform and campaign performance, transactional behavior, and how these things combine to tell a story.

Step three: Find the data that matters

With your data unified and structured in a platform like Ortto, you will be able to use filters to segment your audience and drill down to find the data you need.

Start by taking your hypothesis or question and creating a wishlist — for example, if you want to answer the question, “Are customer support interactions leading to higher MRR or increased engagement?” you may want to start with the following:

• Data on customers who have had a support interaction

• Financial data on when MRR increases occurred

• Engagement score data

• Customer feedback data

You may also want to build a few audience segments to group customers together by engagement, MRR increase, and customer support data. These segments will make report-building even simpler. If you’re an Ortto customer, you can get granular with your audiences using any combination of demographic, firmographic, transactional, or behavioral data. Learn how to segment your audience in Ortto here.

Step four: Identify patterns and form insights

Within these data sets, aim to start spotting patterns. Perhaps there’s a sharp increase in engagement in the week after a support interaction, with MRR following six months later, but only if the customer continues to regularly engage with support. Make note of every pattern you spot, and use these patterns to form insights.

If you are an Ortto customer, at this point it’s likely you’re creating a lot of reports to connect the dots between your data sources. Our visual reports will serve you well later on as you’re finalizing your story. Keep track of the most compelling reports in a dashboard — you’ll thank us later.

Step five: Build your narrative

With your patterns, insights, and data assembled, it’s like you have an answer to that question or you’ve proven your hypothesis. Now it’s time to bring your story to life.

Any story — whether it’s a data story or your favorite novel — should have a narrative arc including an introduction, a point of tension in the middle, and an ending where the tension is resolved. Follow this arc with your story, introduce the why behind the story, explain the tension or problem, and present the solution identified through data and insights.

Another good way to think of this is the four C’s — context, character, conflict, and conclusion.

These models are a great place to start, but — as Cole Nussbaumer Knaflic points out in Storytelling with Data — different audiences will care about different ‘peaks’ and levels of detail along this journey. Will this be presented to a creatively inclined brand marketer or a data-driven growth leader? Lean into the things they care about to get your point across.

Remember - always give your story to an outsider to review. What is clear to you, may not be to others.

Step six: Use visuals to bring your story to life

Remember that dashboard you created? You’re going to want to use these visual reports to bring your data story to life. Visualizations are the way to make dense data quickly comprehensible to your viewers or readers — they are a must-have in your data story.

If your hypothesis or question relates to your customers and their journey, create characters that illustrate who they are and why they are taking a specific journey.

If your resolution is a proposed solution, take some time to visually map out the steps that need to be taken to get there, the expected results along the way, and the stakeholders, team members, or consultants you may need to involve.

Step seven: Review your story as a cohesive narrative

Now that you have your written story and your visualizations in one place, it’s time to review it all as one, cohesive narrative and see how it all comes together. If you’re going to be presenting this story to a board, leadership, or other decision-makers, it’s always worthwhile to do a couple of run-throughs to ensure your narrative is clear and your data is presented in the best light.

Final word

Telling a compelling story with data is the best way to inspire people to take action on the insights and build trust in the data. Follow the steps outlined in this blog to build a narrative that inspires change, and remember it all starts with unified, organized data. Try Ortto for free today to make your data work for you.