Designing for Interaction

Designing for Interaction

One of the advantages of Quadrigram is its built-in interactive features that give your audience greater control over the story you are presenting. Clicking on the data points allows your users to see more closely whats happening. When making an interactive data story, the question then becomes, how do you know when to add interactive elements?

Rather than focusing on the small details, always aim to keep focused on the “bigger picture”. What is your story about? What are you looking to tell? By approaching it this way will help realize areas that could improve and what is missing. Aks yourself, what do you know, that your audience does not know, that you wish they would be able to see more clearly? This could help uncover where data is hard to parse. Asking good questions opens up the opportunities for improvement and these are improvements that could reflect in your data story. Be honest. Once noticing areas that could improve this is where interactive elements come into play and can help your story really shine out.

Channel Your Audience

When presenting to your client or audience remember that while you need to know your audience, you are not your audience. So it is important to be aware of this and be able to clarify and explain each step of the way. One way to do this is by stating the question to your audience, the question that prompted and motivated you to do the analysis. Then give them the details of how you got there.

Explain each step of the way. Adding labels can help synthesize analysis by helping draw attention to the key points in your story. These help signal your audience that there is something important here that they should look at.

Know Your Data

“Data Storytelling’ is a term that gets thrown around a lot but what does this actually mean? Well, data storytelling basically refers to aiming to find the value in your data. Finding the value in your data is analyzing the data and adding a narrative to communicate that analysis to a wider audience. When communicating to a wider audience it is important to be familiar with the source data. You are a “knowledge spelunker” going into the depths of data analysis to get to find real value. The more you know about the source data the more confident you will appear to your audience.

What is missing?

Know that we know the data at hand and know our audience we can delve deeper into the interactive story we want to create. The data is there for analysis and the narrative that is going to be applied will help communicate that analysis to a wider audience. But there is a gap. This begs the question, what is missing? If there is information here that is not easy to parse or that is difficult to communicate, this is when interactive features can really come into play. It is important to remember that the point of interaction is not to show every bit of data but instead exposes the line between the narrative you present and your audience.

Thanks for reading! We are always looking to improve so write to us on our community if you have any questions or let us know what you think with some feedback!

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