Strengthen the effectiveness of content.
Determine the type of data you will need to support your content, and determine the best approach for sharing it visually.
The five types of data include:
- Comparison data compares the values from more than one set of data. Comparisons can be static or over some time.
- Compositional data highlights the parts of a whole and their change over time.
- Distributional data captures the range, trends, outliers, and variance of values in a data set.
- Trending data shows how values in a data set perform over time.
- Relational data reveals how one set of values correlates to other value sets.
Some sources may already have the data you seek in a visual format you can adopt. Typical internal sources include:
- Your internal company departments.
- Product usage data.
- Customer data.
- Marketing performance data.
- Financial documents.
- Sales reports or other internal business reports.
External sources can sometimes fill in internal data shortfalls. This data comes with a monetary cost and may require you to use citations. The four types of external data sources include:
- Open data sources include government and NGOs, commissioning research, or studies. This data is freely available and may come structured or semi-structured.
- Shared data is shared between companies and may have fees attached. Shared data may be structured, semi-structured, or unstructured.
- Paid data includes dedicated portals or SaaS like Google Analytics or CRM services. Paid data is structured.
- Social media data comes from the content you generate through sites like Twitter and YouTube. Data comes unstructured and is subject to copyright restrictions.
Certain chart types pair best with specific data types. Once you’ve decided on the kind of data your content needs, select from the corresponding chart type to present it:
- Comparison charts: Include the bar, bullet, column, line, mekko, pie, and scatterplot graphs. For example, use a comparison chart to visually compare the performance of two or more products over time, before and after the launch of a marketing campaign.
- Compositional diagrams: Include area, mekko, pie, stacked bar, stacked column, treemaps, and waterfall graphs. You could use these types of charts to visualize the percentages of certain demographics in a customer base you currently serve.
- Distributional charts: This group includes the bar, column, line, mekko, and scatter plot graphs. These charts are perfect for showing the statistical distribution of your data, like the age distribution of your customers in a demographic.
- Trending charts: These usually present best through the column, dual-axis line, highlight tables, line, and word cloud graphs. You might use trending charts to visualize what keywords are trending in online searches relating to your industry.
- Relational charts: May use heat maps, tree diagrams, and bubble, Gantt, line, and scatter plot charts to visualize their data. These types of charts are perfect for visualizing the hierarchy within a system or organization.
Microsoft Excel has adequate graph-making capabilities but is limited to making approximately 20 types of graphs. More robust, commonly used software includes:
- Google Charts: This is a free SaaS that can pull data from Google Sheets, Salesforce, and SQL databases.
- Power BI: Microsoft’s robust data analytics and visualization tool lets users present graphs in an extensive range of formats.
- Tableau: This powerful app is easy to use, versatile, and loaded with visualization capabilities.
- Zoho Analytics: Zoho specializes in visualizing business intelligence data, like sales, costs, and profit.
Consider engaging a visual designer to develop your charts if you lack the time or know how to do it yourself. A professional graphic designer will have advanced tools and skills that will help your graphics stand out.
Great graphics are useless if they are obsolete. Establish a cadence to refresh your graphs with up to date data. Some applications, like Power BI, have automatic updating features built into them.
Try to sync your update schedule as closely as possible when your primary data source receives its updates. Doing so will keep your content relevant and reliable for your audience.