Marketers have more data at their disposal than ever before, but choosing what to measure – and crafting a visual story to share the insight gained from data analysis – can be a vexing dilemma.
A recent post in the UK’s Guardian newspaper sums up what many marketers are facing with a quote that’s often attributed to Albert Einstein: “Not everything that counts can be counted, and not everything that can be counted counts.”
All decisions can’t be based on real-time, infallible data, according to the post. For example, companies often can’t directly attribute sales revenue to social media outreach efforts.
Thus, companies should focus their data analysis efforts on areas that have more readily available measures that can track performance against strategic objectives.
For instance, businesses should consider these questions:
- Compared to other marketing channels, does the company have good reach across its target audience on social media?
- How does the target audience engage with the company’s content compared to how the audience engages with the content of the company’s competitors?
“Align the data you need to your strategic objectives, assess the options and make the decision accordingly,” the author of the article advises. “This could be big data, small data or somewhere in-between data. These principles hold true now, as they did when customer relationship management was marketing’s next big thing, and before the quote itself was conceived.”
Companies should also think about the answers to these questions:
- Is there a clear connection between strategy and the data being analyzed?
- Will the company collect the data it truly needs to make better informed decisions, despite the size of the data?
- Does the company have a roadmap for what to do with the insight gathered after the analysis?
- What experts – such as data scientists – does the organization have or need for data analysis?
The first step is for organizations to tap the data to be measured that best aligns with corporate objectives. The next step is ensuring that the insight generated via data analysis is presented in the most compelling and effective way to the decision makers.
One of the best ways to do this is through data visualization, telling the story of the data by graphically depicting statistics. But, what is the best way to tell a story through data?
A recent Harvard Business Review post suggests that the most important first step is identifying a compelling narrative.
“Along with giving an account of the facts and establishing the connections between them, don’t be boring,” according to HBR. “You are competing for the viewer’s time and attention, so make sure the narrative has a hook, momentum, or a captivating purpose.”
It’s also important to carefully consider the audience and what it may already know about the topic; the visualization should be built around the information the audience already has, both correct and incorrect, the post notes.
“A visualization should be devoid of bias. Even if it is arguing to influence, it should be based upon what the data says–not what you want it to say, according to the post. “Viewers and decision makers will eventually sniff out inconsistencies which in turn will cause the designer to lose trust and credibility, no matter how good the story.”
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