Like any good trilogy, data storytelling consists of three strong acts:
Act One: Collecting the Data
Typically given the rap as time consuming and mindless work, data reporting is so much more than that – it’s the plot of the data story! The data you compile is the foundation of the report and can make or break the data story.
When a pulling a report, though, the sheer amount of data can be overwhelming. To help guide you through the perils of data collection, it’s best to adhere to this simple question: does the content relate to the context? For example, if you’re running a video campaign, you should focus on video completions and engagement rates. Additionally, if you’re running a lead gen campaign, focus on responses and leads and their respective costs.
Like any solid first act of a trilogy, we’re introduced to a group of adversaries determined to derail the data story referred to as “common data misconceptions.” These include:
- The legendary tale of quantity over quality
Although volume makes a report visually appealing, quality insights make a report valuable. Try to include data that’s relevant to the campaign, and specific to your team’s digital efforts, rather than include syndication data to purely drive up mention and impression numbers
- The rumor that only positive data is allowed
All performance tells a story, regardless of its nature. Yes, it’s always easier to present only positive data to clients, but “negative data” highlights challenges that, with your team’s help, your client can overcome.
- The belief that the more sources, the merrier
When compiling a report, try to pull from the same source for all data. That way, you can easily compare data within the report, as well as week over week, quarter over quarter, and year over year.
After overcoming the common data misconceptions, and compiling data relevant to your campaign objectives, it’s time to move into act two.
Act Two: Drawing Conclusions
Now that the data is collected, what’s next? Similar to the second act of a trilogy, we’re presented with a major challenge that needs to be resolved: the data dump. Renown as a fast solution to provide clients with insights, the data dump actually produces more work…for the client. When sharing a data dump with a client, the expectation is now on the client to sift through the data and find meaning in the data findings, rather than on you to present insights and recommendations. Although the data dump may be a fast fix, it can overwhelm the client and insinuate that your team doesn’t know how to draw conclusions from your data.
To avoid the data dump, it’s best to apply a narrative to your data:
- Why is the data performing this way?
- What is the driver of performance?
- How and Where can we apply this data?
- Who is being impacted?
By drawing conclusions and providing a narrative to why and how the data is performing, you’re not only providing actionable insights to clients, but also proving to clients you can speak to the data and apply it to campaign objectives and efforts.
Before diving into act three, it’s important to remember that data dumps come in various forms, and even a graph can be considered a data dump. The best way to spot a data dump is to ask the simple question: what does this data mean? When examining your data report, if that answer is not clearly stated in the report, then you’re looking at a data dump.
Act Three: Story Time
Now that you have your data, how should you present it? Best practice: let the data speak for itself. Avoid “fluff” and “filler” information in order to let the data shine. Everyone likes a good story, so a few key considerations to keep in mind include:
- Stay concise and to the point
- Speak in active voice
- Be confident! Refrain from using ”would,” “should,” and “maybe”
In the current digital age, simply sending excel spreadsheets to clients are no longer acceptable. You need to explain why data is relevant and how clients can use it. By applying these best practices and tips, you’ll be able to conquer data misconceptions, avoid the data dump, and become a data storyteller. After all, it’s a data driven world and we’re just living in it. Want to learn more about how we do data? Check out or analytics page.
Now that the data is collected, what’s next? Similar to the second act of a trilogy, we’re presented with a major challenge that needs to be resolved: the data dump. Renown as a fast solution to provide clients with insights, the data dump actually produces more work…for the client. When sharing a data dump with a client, the expectation is now on the client to sift through the data and find meaning in the data findings, rather than on you to present insights and recommendations. Although the data dump may be a fast fix, it can overwhelm the client and insinuate that your team doesn’t know how to draw conclusions from your data.
To avoid the data dump, it’s best to apply a narrative to your data:
- Why is the data performing this way?
- What is the driver of performance?
- How and Where can we apply this data?
- Who is being impacted?
By drawing conclusions and providing a narrative to why and how the data is performing, you’re not only providing actionable insights to clients, but also proving to clients you can speak to the data and apply it to campaign objectives and efforts.
Before diving into act three, it’s important to remember that data dumps come in various forms, and even a graph can be considered a data dump. The best way to spot a data dump is to ask the simple question: what does this data mean? When examining your data report, if that answer is not clearly stated in the report, then you’re looking at a data dump.
