Data visualization is a powerful way to tell stories with data, but how do you measure the impact of your data-driven stories? How do you know if your audience is engaged, informed, or persuaded by your visuals? In this article, you will learn about some of the best tools and platforms for measuring data-driven story impact, and how to use them effectively.
Before you start measuring the impact of your data-driven stories, you need to define your goals. What are you trying to achieve with your visuals? Who are you trying to reach? What actions do you want them to take? Your goals will determine what metrics and indicators you need to track, and how you will interpret them. For example, if your goal is to raise awareness about a social issue, you might measure the reach, impressions, and shares of your visuals. If your goal is to educate or inform your audience, you might measure the time spent, retention, and feedback of your visuals. If your goal is to persuade or influence your audience, you might measure the conversions, donations, or advocacy of your visuals.
At Uncos, we have designed our model to score news and other platform articles' expected impact. We defined our criteria (Publication, Readership, Sentiment, Google Presence, Story Quality, Author etc etc etc,). We combine AI with human curatorship. We update global firms daily on the real-time impact of news on their brand, as well as their chosen competitors and sector developments. All of this news is then scored, curated, and provided by our analysts. Visualisations range from a simple email to dashboards, charts and intelligence levels from Macro to Micro. We are always developing, as each client has their own requirements, but the structure allows us to turn stories into data, which in turn allows us to keep our clients informed.
Data-driven storytelling requires a compass in addition to a scorecard. Determine the goal of your narrative before delving into metrics: increase consciousness? Teach? Win over? These objectives—reach, engagement, and action—direct your map. A social problem? Track impressions and social share metrics. concentrating on learning? Monitor time spent, feedback, and retention. Do you want to do something? Your compass points are conversions, donations, and advocacy. Recall that while data tells a tale, your objectives dictate the screenplay. When you concentrate on both, your images have a real impact.
When measuring data-driven story impact, there are a variety of tools and platforms to choose from. However, it's important to ensure that the ones you select match your goals, audience, and budget. Popular and effective tools and platforms for measuring data-driven story impact include Google Analytics, Tableau Public, and Datawrapper. Google Analytics is a free tool that enables you to measure the traffic, behavior, and outcomes of your website or app hosting data-driven stories. Additionally, Tableau Public is a free platform for creating and sharing interactive data visualizations online. It allows you to measure views, likes, comments, and downloads. Finally, Datawrapper is a paid and user-friendly platform for creating and publishing data visualizations for the web. It enables you to measure impressions, clicks, and interactions of your data-driven stories. All of these tools can be embedded on your website or blog with Google Analytics to measure their impact.
Some Business Intelligence and Data Visualziation tools (e.g. MicroStrategy) that are used by large enterprises can also be used to measure data-driven story impact, with no need to use any other tools. You can track everything from how many opens of your dashboard you've received over any period of time. You can also track who uses the dashboard, when they used it, and how often they use it. Using these kinds of metrics, you can quickly measure how your data-driven story / dashboards are being used, or more importantly, not used...
Once you have chosen your tools and platforms, it is essential to analyze your data to measure the impact of your data-driven stories. Comparison of data with goals, as well as seeking patterns, trends, and insights will help you answer questions such as: how many people saw your data-driven stories; how long did they spend on them; how did they interact; how did they find them; how did they react; and how did they act after seeing them. Additionally, you should consider the context and limitations of your data, avoid making assumptions or jumping to conclusions, use multiple sources and methods of data collection, triangulate your findings, be aware of potential biases, errors, and gaps in your data, and acknowledge them.
Enterprise Business Intelligence and Data Visualization tools usually come with built in "Usage" metrics. With the enterprise grade tool that I use most often, the vendor provides access to almost every type of usage metric - Report usage, # of times opened, how long someone spends in a report, what they do within the report, plus many more stats. Most important is being able to view these metrics over any period of time - This week VS last week, this month VS last month, and so on. Also, being able to see usage trends over longer time periods can indicate if your data driven dashboard is gaining or losing popularity. You can even start seeing trends, like which day of the week / month the dashboard is used most.
After you have analyzed your data, you need to communicate your results to your stakeholders, partners, or sponsors. You need to show them how your data-driven stories achieved your goals, and what impact they had on your audience. You need to use data visualization to present your results in a clear, concise, and compelling way. You need to use charts, graphs, tables, or maps that are appropriate for your data and your message. You need to use colors, fonts, labels, legends, and annotations that are consistent and readable. You need to use titles, captions, headlines, and narratives that are informative and engaging. You need to use data storytelling techniques to highlight your key findings, insights, and recommendations.
If someone has created a data-driven dashboard in your organization, I think it's imperative that you have a mechanism to send usage statistics to them. Based on these statistics, the dashboard builder may tweak their work to increase usage. Without communicating these usage statistics (or providing direct access to them) a dashboard creator is flying blind in relation to whether anyone is using their work. Something as simple as a Week over Week usage report could be enough to let them know how their work is being adopted, or not...
Finally, you need to improve your practice based on your results. You need to use your data to evaluate the strengths and weaknesses of your data-driven stories, and identify the areas for improvement. You need to use feedback, surveys, or interviews to gather the opinions and suggestions of your audience, and learn from their perspectives. You need to use experiments, tests, or trials to compare different versions or formats of your data-driven stories, and optimize their performance. You need to use best practices, guidelines, or standards to enhance the quality and credibility of your data-driven stories. You need to use data visualization as a continuous process of learning and improvement, not a one-time product or project.
Does your data drive change? Do you bring new efficiencies? Do you give actionable opportunities? If your data is just "nice to have", it isn't impacting the business. Making sure it's tailored to the needs of the stakeholder will directly influence how impactful it is.