We use a lot of data visualization — Excel sheets, charts, graphs, infographics, etc. — to help interpret the data we collect for our social media marketing clients.
Often times the client doesn’t care about the raw data and wants to see the “pretty” reports (as we call them).
Luckily, we have a team who is skilled at data storytelling.
But what if your team isn’t well versed in how to collect, clarify, and confirm the data?
There are three issues that delay data visualization; we’ll spell them out here and give ideas for overcoming them.
Why Is Data Visualization Important?
Spreadsheets with mass amounts of data in several hundred rows and columns can be daunting.
But when given context visually, say in a pie chart or graph, data can be much easier to understand.
We’ve found that many times it’s less about the data and more about interpreting the data we collect to tell a story.Metrics should be less about the raw data and more about the story the data tells.Click To Tweet
And there’s plenty of data you can use to tell a visual story:
- KPIs (key performance indicators)
- Daily/weekly/monthly metrics
Our social media management tool, Sprout Social, helps us automate some of the data visualization, and some of it is done manually.
Here are a couple of data sets represented in visuals:
Tools are one easy way your team can get help with data visualization — but more on that below.
3 Problems That Delay Data Visualization
With all of the potential data gives us, it’s obvious that certain companies or teams are still struggling with using data to make informed decisions.
Why are they struggling?
It probably has to do with one of these three problems:
1) [Problem] Not using data to make decisions[Symptoms]
- Ignoring data
- Focusing on vanity metrics
- Not able to tie data to business goals
- Little to no detail or storytelling with the data
These marketers or teams can often be found making decisions based on “gut feelings” versus facts.[Solutions]
Understanding and making data-driven decisions should be a part of the job description … for everyone on the team.
Everyone must be involved with the data “payoff” and must:
- Understand how to mine for the RIGHT data
- Analyze the data
- Know the key metrics
- Utilize the tools or dashboards
2) [Problem] Lack of tool strategy / technology limitations[Symptoms]
- Spreadsheet fatigue
- No process or workflow for moving data from raw to “pretty”
- Not using proper tools to make data visualization cohesive
There are several tools that can help teams get from collection to interpretation — and they range from free to paid.
3) [Problem] No push for data fluency[Symptoms]
- One “gatekeeper” or data analyst
- Flawed organizational development
- No adoption of data-driven reports for team
Creating an internal culture of collaboration needs to be a priority. Figure out ways to turn data decisions into data-driven decisions.
This can be accomplished by getting the whole team to focus on micro changes in data, and on the client side by continuously educating the client on the story the data is telling.These 3 common problems can delay data visualization for your team.Click To Tweet
Bottom line: Data fluency comes before data visualization.
Solving The Above Data Problems
If it isn’t already obvious, I’ll spell it out.
Data fluency — or effective communication on data — is essential before you can move to data visualization.
If you work to solve the above data problems, you should be well on your way to both collecting and creating thoughtful reports, visualizations and stories with data.
How are you using data or data visualization to help inform your marketing decisions? Let us know in the comments section below!
*The Sprout Social link is an affiliate link to their 30-day free trial (no credit card required).
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