The data challenge in marketing is one that many B2B marketers face every day. The problem? Data can be tedious, complex and dry for prospects who just want meaningful information about what you have to offer them on their journey towards success with your product or service but also hard because most people don’t enjoy reading long blocks of numbers when they’re trying to get through some exciting content.
Data is powerful because it can tell stories. Stories have always been the way people communicate, and data should be used in this manner to connect with your audience, convey important information about products or services they may want more of (or less), move them towards taking desired actions like signing up for email lists, etc., all via their preferred mediums- whether that’s online ads on Google Adwords; Facebook campaigns where you post specific times based off what keywords get searched during certain hours/days.
There are five steps you need to take in order to create story-driven data visualizations. The first step is identifying the type of stories that will be told with your visuals and how they can help tell those tales, then crafting an interesting narrative for them using words or graphics; finally presenting it all together, so people get what’s going on at once.
The process may seem daunting, but there are tools out here designed just for this kind of creativity at aftros.
1. Review Data Set
What story am I trying to tell? How does this issue or problem affect my audience, and why should they care about it.
What’s at stake for people who don’t do X (the solution)? What are some ways that you could make things better if we solved the problem together – architecting solutions based on data insights from validated user stories
- Is there anything about my data that surprises me?
- Is there anything in my data that suggests any trends or themes?
- Is there anything in my data that stands out as a key character or player?
2. Develop Your Narrative
The story you tell yourself about your business and its future is just as important to its success. It can be a simple arc or more complex than that–whatever works best for how much time we have!
Your positive mindset will help drive motivation, too, so make sure not only do I know what’s going on but also why things happened this way instead of wasting energy wondering if there might’ve been some other option better out there.
Data visualization is an example of storytelling with visuals. It tells the story of how this young marketer attended his first marketing conference and had too many drinks over the course of the weekend!
3. Build Your Narrative Framework
The framework I use to create my stories is as follows:
This process starts with identifying your story’s central message or theme, which usually evolves out of one’s personal experience and involves some formative event.
Once you have identified this important concept for yourself, two ways can be expressed in terms of narrative—either directly through the description (elegiac tone) whereby we see how our protagonist grows into an increasingly more perfect understanding; another approach might include subplots where various aspects related specifically around issues like family relationships, love life, etc., come together at last towards reconciliation. Depending on what type of effect(s) these emotions
Visual storytelling doesn’t always need an image; text can be just as powerful. The Salesforce infographic below tells the story of one company’s success by using data points and information in its base layer, which are connected with lines to form a visual representation (a secondary ‘layer’ if you will) for those who want more detailed info on certain topics like revenue or profit margins – but only when they click through!
4. Formats for Data Visualization
The four most common data relationship types you can consider to convey your story are bar graphs, line plots, radar charts, and DON’T FORGET THE IMAGE!
-Bar Graphs show trends over time. They’re great for showing accumulation or change in single populations across different points of comparison (e g., “This year’s graduates had attended school fewer days than last”).
-Line Plots demonstrate relationships between two variables by connecting them with lines that represent what might be called either an “experimentally determined effect size” if there was no previous study.
5. Create Your Visual
Data visualizations are an excellent way to communicate complex information engagingly and interestingly.
In this example, Red Bull compared the speed of their Air Race planes with other motorsport series such as F1 racing or NASCAR races by creating one graph that shows how they compare against each other based on various statistics like takeoff weight limit per engine type (lightweight wings mean quick takeoffs; heavy airplane requires faster speeds).
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