Marigold

Rooted in deep industry expertise, Marigold unites world-class, fit-for-purpose marketing solutions across the full customer lifecycle that build loyal customer connections for over 40,000 global brands, from SMB to enterprise.

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Why, when and how to use data storytelling in relationship marketing

August 29, 2023

By Rima Deming (principal marketing strategist), Georgia Gkolfinopoulou (marketing strategist) and Britt Fetterhoff (marketing strategist)

Good relationship marketing is all about communication, and the best way to communicate is to tell a good story. For instance, a famous experiment by Significant Objects found that good storytelling can increase the value of a product by 2706%.

While there are many ways to tell a good story, one particularly effective method is through data storytelling.

What is data storytelling?

Data storytelling is the art of combining data analysis with compelling narratives to convey insights that drive action.

Data storytelling comes with many benefits. Engaging and inspiring readers are the two main factors that make storytelling with data exciting. With data storytelling, complex information and large data sets can be distilled into simple and easy-to-understand narratives applicable to customers across demographics regardless of age, role, or background. The result is more memorable, relatable, and ultimately impactful communications.

Formats like infographics, data visualizations, case studies, and success stories are all useful data storytelling options. Or perhaps we should say “storytelling with data” because if done right, the story always comes first. It takes more than just throwing together a chart and saying “good luck.” No one wants to look at endless graphs and pie charts.

Why use data storytelling?

There are many reasons to pursue a data storytelling effort. Data storytelling helps customers grasp complex information by presenting it in a narrative format that is relatable and easy to comprehend. Incorporating storytelling elements into data-heavy communications helps capture the audience's attention, evoke an emotional reaction, and keep them engaged throughout the narrative.

Data storytelling creates a sense of purpose and urgency, motivating customers to take action based on the insights presented. And it taps into the human aspect of data, creating a connection between the audience and the insights.

When to use data storytelling

As powerful as data storytelling is, it’s not a tactic to use with every customer outreach. It’s a tool best used only for the appropriate opportunity. A few that come to mind include:

Presenting insights

Good relationship marketing begins with collecting zero-party data from customers. Often that data is used to personalize messaging, deliver product recommendations, and make timely offers. But it can also be combined with other types of data to present broader insights or findings that customers might find interesting.

Influencing decisions

Data storytelling empowers customers to make informed and confident choices. By presenting data-driven narratives, you can combine the emotional relatability of a good story with facts grounded in evidence and analysis. Together, both emotional and rational considerations combine to drive strategic decision-making.

Engaging stakeholders

Use data storytelling to engage and captivate diverse stakeholders while fostering a shared understanding and promoting collaboration. Data storytelling captivates and engages audiences by presenting complex information in a compelling and relatable format. It ignites curiosity, stimulates interest, and inspires action by connecting data-driven insights to real-life situations and challenges.

Simplifying complexity

Utilize data storytelling when dealing with complex data or technical information, making it more accessible and easily understandable for a wider audience. With data storytelling, complex information is simplified and distilled into meaningful and easily understandable narratives. This helps customers grasp key findings, trends, and patterns without getting overwhelmed by technical jargon or intricate data details.

Data storytelling best practices

Regardless of which of the above scenarios call for a data storytelling approach, there are a common set of best practices to keep in mind when creating your campaign. Good data and good stories won’t be of much use with poor execution. Follow these steps to ensure your data storytelling efforts are maximized for success.

  • Define your objective: Clearly state the purpose of your data storytelling.
  • Know your audience: Tailor your data storytelling to your audience's level of expertise and interests.
  • Use a narrative structure: Structure your data presentation like a story with a beginning, middle, and end.
  • Keep it simple: Avoid complex charts and jargon; simplify your visuals and explanations.
  • Visualize data effectively: Choose appropriate visuals and use colors, labels, and annotations to highlight insights.
  • Provide context: Explain relevant trends, benchmarks, and comparisons to add meaning to the data.
  • Tell a story with data: Use data points and examples to support your narrative.
  • Use storytelling techniques: Incorporate anecdotes and real-life examples to make your data relatable.
  • Make it interactive: Engage your audience with interactive elements like polls or quizzes.
  • Test, test, test: Try creating multiple iterations of your data storytelling effort and monitor which generate the best response from customers, then optimize for what’s proven to work best.
  • Use data ethically: Handle data responsibly and respect privacy guidelines.
  • Be transparent: Communicate any limitations or uncertainties associated with your data.

As marketers, we use data every day to determine where to invest our resources, determine campaign success, and make copy and creative decisions. Your customers are doing the same to make purchasing decisions of their own. That’s why data storytelling plays such a critical role in your customer communications.

Tags

storytelling
Data Insights
Relationship Marketing