Data storytelling: Adding meaning to metrics

Your comments and likes are up month over month, and your new campaign hashtag has been used over 1,000 times, but what do those numbers mean? And, once you figure that out, how do you convey it to stakeholders? If you’re asking these questions, you’re not alone.

Discerning what metrics mean for a business is no easy task. And sharing the impact beyond your team, those most familiar with the metrics, is even tougher. To bridge the gap between metrics and meaning, we need stories. It makes sense, then, that The Sprout Social Index™ found the most effective way to share social metrics with an executive team is through in-person meetings—a platform that lends itself well to a narrative.

What is data storytelling?

Data storytelling is the art of translating raw data into a holistic narrative that describes the impact data has on an organization. It merges data science, graphic visualization and storytelling by providing necessary context.

As a social expert, you already have storytelling skills. Let’s talk about how to incorporate them into your approach to reporting and analysis.

Where is the value in the data?

In order to earn buy-in from executive stakeholders, you need to weed out and highlight the value in the data, both quantitatively and qualitatively.

Quantitative data storytelling

In social media, quantitative data refers to the numbers behind social media metrics such as engagement, awareness, share of voice, ROI and customer care. These numbers focus on the “how many” of social media, as in how many:

• new likes, comments or shares your content received
• impressions you’re achieving
• posts you’re mentioned or tagged in comparison to competitors
• purchases driven by a social media referral
• comments and questions about your brand that your team responds to

These are just a few examples of performance metrics. But, numbers can be deceiving. One viral post or brand crisis can skyrocket your numbers for a month (for better or worse), which could set unrealistic expectations for key performance indicators (KPIs) like impressions or engagements, if you don’t put the data in context.

Quantitative data storytelling

Comparing data month-over-month or year-over-year is meaningless without the story behind the trends. Plus increases and decreases aren’t always black and white. For example, maybe your comments are way up this week. Sounds awesome, right? Not exactly. If they’re mostly positive, that’s great. If they’re mostly negative, that’s a problem.

There needs to be an explanation for changes over time. This is where qualitative data comes in. Think of your quantitative data as the plot of your story, and your qualitative data as the juicy details that help set the scene.

In other words, qualitative data gives context. Your interpretation of what it all means gives both types of data a narrative. If influencers are posting about you, what are they saying? Are mentions raving about your products, or are they pointing out a serious customer service issue? If comment threads are accumulating, what’s driving the discussion, and what’s the overall sentiment?

Use social listening tools to analyze trends in discussions about your brand, which can be particularly helpful if you’re seeing a major spike. This can show you what people are talking about, sentiment, keywords and trending topics.

But even without social listening tools, you can look at your results and start to dig into the “why.” Look at individual messages to identify what people mentioning you are talking about the most, what they’re saying and so forth. Those specific examples will help you craft a report that puts your numbers in context, and allows you to identify future opportunities. This is where your story begins to develop.

Delivering analytics and metrics: Why is it important?

Executives and other stakeholders like quantitative data because it reflects how social impact’s the brand’s bottom line. They especially enjoy seeing a translation of social media numbers into revenue dollars, or growth in metrics that correlate with an increase in conversions. Although they might want to see quantitative data first, qualitative data is just as essential to telling your story.

Data doesn’t exist in a factorless vacuum. Remember that qualitative data provides potential influencing factors that are likely contributing to performance metrics. Plus qualitative data can support persuasiveness. For example, seeing concrete examples, such as screenshots of @-mentions or positive comments can make your points stick.

A balanced combination of qualitative and quantitative data is what separates dry data from an enlightening data story that leads to executive buy-in and actionable strategy.

Using data driven storytelling can help you develop credibility because you’re simplifying complex information into digestible key points and action items.

Steps towards effective data storytelling

To ensure your data story demonstrates value, follow these steps before diving into creating your presentation:

• Define your hypothesis. What do you think the data will tell you? What do you want to prove or disprove? Is there a trend or pattern you think will continue?
• Collect the data. Gather all the data you need to shape your story.
• Give purpose to your story. After reviewing and analyzing your data, summarize the goal of your story in one to two sentences. What is the data telling you and what story can you communicate?
• Plan what you want to say. Outline everything you want to say in your presentation, including your intro, major data points and conclusion.
• Ask questions. Does the data prove or disprove your hypothesis? Did you discover anything new that shapes your narrative? Your audience will likely have questions too so this is a good exercise to prepare.
• Identify a goal for your audience. What would you like your audience to do after hearing or reading your story?

While there are creative writing workshops abound, few cover the artistry behind presenting numbers in an elegant, comprehensible way. If you’re not sure where to begin, here’s a step-by-step guide with a data storytelling example:

1. Identify the most interesting points

If you have a large data set(s), it can be overwhelming at first. Put on your author cap and ideate the structure of your data story.

You should already have a main objective in mind, whether it’s relaying campaign status or justifying a bigger budget. What pieces of quantitative and qualitative data best support the main idea you want to convey? What data points directly contradict what you thought was going to happen? Perhaps the amount of website traffic driven by social has risen in conjunction with sales.

Even if you aren’t using UTM tracking to map your social efforts all the way through to purchase, understanding which content drives traffic (and what kind doesn’t) will provide some insight into what’s fueling the fire.

2. Lead with your second most interesting piece of data

You don’t want to show your whole hand, but you do want to demand attention right at the beginning. For instance you might say something like, “As you already know, sales are up this quarter. What you may not have seen is that this trend correlates with our increase in traffic from social.” Include any other interesting points after this, but don’t use your best one yet.

3. Leverage visual aids as you present

Lean on data visualization to drive home your points. “As you may already know, sales are up this quarter,” (graph of this quarter’s sales appears). “What you may not have seen is that this trend correlates with our increase in social media traffic,” (the second graph of traffic by social platform appears as an overlay to the first graph). Accompanying your story with visuals would drive the impact of your data in this scenario.

4. Predict questions or challenges

Naturally, your audience will analyze what they are seeing. In the example we’ve used so far, they may ask something like, “How do we know sales are up because social traffic is up, and not the other way around?” Depending on whether you’re presenting data to a group live or emailing a written report, incorporate slides or bullet points that answer the questions you expect your audience to ask. These questions are good: They keep your audience engaged long enough to deliver your grand finale data insight.

5. Share the most interesting piece last

Leave your audience with takeaways they will remember by sharing your most interesting piece of data last. For instance, you could say, “We considered that correlation might not indicate causation, so we dug a little deeper and looked at the shares, social referrals and conversions. We were able to trace 33% of our new customers this quarter to one particular influencer’s post,” (screenshot of post here) “in which she raved about how our product helped her. She has over 700,000 followers, many of whom also shared the post and clicked through to our site from it.”

Notice how this example answers the question from the audience while providing both quantitative and qualitative data. This sweet spot is what will make your data story memorable and impactful.

6. Get to your next steps and the “so what”

Just because you’ve shared the data doesn’t mean your analysis is done. Round out your presentation with why this matters to your overall social media and business goals. Then share how you will be using this data to inform new ideas moving forward. For example, because this one influencer post did so well, you’re looking to partner with other influencers who have similar audiences.

Boom. Mic drop.

This flexible format can be repeated as needed and applied to just about any medium from presentations to reports and emails.

It is important to note the common data point threaded throughout this story: social traffic. Additional data points can help complement or emphasize your main point. Think of these related data points as significant moments in the running theme of your story. And your main data is your key plot point.

You may have lots of data to comb through to find the right points to cover. That’s why the first step is picking out the most interesting ones. It’s up to you to gather the data that best illustrates your main idea and use it to focus your audience on your key message. Here’s how Lindsay Bruce, Marketing Manager at Twitter Business, approaches using data to both understand her target audience and create more impactful reports (serious reporting pro tip at 1:13).

Examples of effective storytelling with data

Get inspired with these data storytelling examples:

1.   User Interviews

The State of User Research 2022 report by User Interviews uses plain language in the report copy and has informative illustrations throughout, along with a clickable table of contents to keep the audience engaged.

2. The Pudding

As a publication that specializes in data journalism, The Pudding is a master class in data driven storytelling. In How Artists Get Paid From Streaming, the Pudding breaks down the mechanics of the music industry and streaming platforms.

The story is scrollable, and as you maneuver down the page, animated data visualizations appear. Notice how the copy is short, simple and complements the graph to the right. Also note how the graph is colorful and vibrant, but isn’t too distracting.

3. Sprout Social

I don’t mean to toot our own horn, but Sprout has some excellent data storytelling as well. Our data reports, like the Creator Economy, feature digestible narratives and visual aids. Remember that your visuals don’t have to be graphs and charts. You can use a graphic to emphasize a stand-out data point.

What to avoid when creating your data story

Social data in action is a beautiful thing, but there a few things to avoid when developing your data story:

• Not considering your audience. Consider what information is the most relevant to your audience. If you show data that isn’t valuable to them, your story will get lost.
• Highlighting too many metrics. Again, consider your audience and what is the most important. Too many metrics can feel overwhelming.
• Not using qualitative data to provide more context. Don’t disserve your audience by leaving out necessary information that qualitative data provides.
• Using data visualizations that are too distracting. Stick to simple, fresh visuals that are easy to interpret.
• Omitting data visualizations altogether. Many people are visual learners, as visuals can make intaking information easier. Plus, graphics will make your presentation more engaging.
• Using only text formatting. Avoid using text formatting (think: color, highlighting and font-weight) to emphasize key points.
• Providing negative or lackluster results without context. Not every story has a happy ending, and that’s okay. Instead provide more context or a solution to your audience.

The power of data visualizations

To tell a story with data, you need to show not just tell. Storytelling with data visualization can illustrate those findings. Data visualizations like graphs and charts synthesize complex data and make it easier to digest with a quick glance.

Social media networks offer native analytics tools that provide plenty of platform-specific data to work with. However, strong storytelling comes from a big picture view that takes all your social media marketing into account at once. Compiling that information takes a lot of work!

Fortunately, software like Sprout can alleviate the workload. Sprout pulls all of your metrics from various social media platforms into one place. It even provides presentation-ready reports and enables you to compare your metrics over time and to competitors.

When quantitative data is pulled together into one place, it leaves you with more time for strategic storytelling.

Sprout presents a bird’s-eye view of what content is working, who is talking about your brand and the sentiment behind it. You can also uncover audience demographics, the best times to post and which platforms have the highest ROI.

Ready to get started? Sign up for a free trial and explore our data analytics and reporting features so you can write your brand’s data story.