A part of any strong revenue operations team is the dependence on data and data visualization to support decision making within your go-to-market teams and business. And while investing in reliable data is critical, it's just as important to invest in the mechanisms that allow you to interpret and understand what the data is telling you.
Having spent the past decade supporting revenue leaders within sales, marketing and customer success, I've witnessed the growing reliance on having strong data visualization to support both short and long term business planning. No wonder why the market for data visualization tools is set to grow to $10.2 billion by 2026.
Investing in the right technical skills and data visualization software can provide your organization with the leverage to acquire, retain and grow customers in the long run.
What Is Data Visualization?
Data visualization is both the art and science of representing large and sometimes complex data sets visually. For some, this involves excel spreadsheets while for others who are further along, it involves interactive reporting and dashboards through comprehensive BI tools.
Data visualization lessens the reliance on summarized text and emphasizes the important brain function used to understand images. From a physiological perspective, reading text is rather inefficient for us, as the human brain processes images 60,000x faster than text. This is partly why infographics are so popular for digesting information.
Within revenue operations, creating efficiencies in how we understand, interpret and action on data is critical. And this is why we see many B2B SaaS organizations invest in growing the business intelligence functions that are responsible for measuring business performance.
Visualization such as charts, graphs and diagrams are great tools in turning raw data into expressive visuals that can tell a story. These visuals serve as powerful solutions for conveying information and facilitating making important decisions at all levels.
The Benefits Of Data Visualization
Within RevOps, data visualization has countless use cases. Data visualization can be used to forecast revenue, measure marketing effectiveness, or understand the overall health of your customer. Although these use cases are many, I found that they are primarily centered around five very important benefits received when you make the investment in robust data visualization.
1. It Provides Accessibility: Information needs to be shared and remain accessible for employees within your organization. Formatting data into an easy to understand manner can help drive alignment between teams. Everyone’s role has some level of dependence on data which makes data accessibility an important benefit of data visualization.
2. It Helps Draw Comparisons: Data visualization is often used to compare data points. Visual images and representations make it alot easier to spot trends, differences and similarities. Visuals like bar charts or line graphs are great examples commonly used for comparing data sets.
3. Describing Relationships: Revenue operations professionals must be able to articulate and translate the relationship different data points have within your business. A simple example - what is the relationship between your sales team’s order values and your sales team’s average sales cycle. With the help of data visualization, describing relationships becomes easier.
4. Recognizing Patterns: Humans are great at detecting patterns through visualization. In RevOps we use data visualization to highlight both patterns and outliers within data. Visualizing patterns makes it easier to spot trends, anomalies and themes that would be much harder to articulate through just text.
5. Data Storytelling: As a revenue operations professional you are very close to the data within your organization. It is not only our role to maintain and aggregate data, but to also inform stakeholders what the data is telling us. Data visualization is a critical component to effective storytelling. Learn to use data visualization to share your point of view and story while also enabling other GTM leaders to effectively storytell and also share their own narrative.
10 Real World Data Visualization Examples in Action
Now that we have unpacked what data visualization is and the realized benefits in investing into it, I'd like to take you on a visual journey through some real life examples of different data visualizations.
Here are 10 real world examples of both business and non business-related data visualization examples for your viewing pleasure.
Column Chart: Apple's iPhone Quarterly Review
Column charts are unique in that they are simple to use and understand. A column chart is the representation of numerical data displayed as columns with varying width or height. Take for example this column chart displaying iPhone Quarterly Revenue for Apple from 2014 to 2022.
When to Use a Column Graph
A column chart could be used to track changes over time intervals just like in the image above. These charts can also be used to compare data across different categories or groups.
These chart types are great at highlighting differences and visualizing rankings, making these charts effective in presenting discrete data such as frequencies, count or percentages.
Waterfall Chart: A History of the European Union
Within Revenue Operations, I've seen waterfall charts frequently used to forecast sales performance within specific periods. For example using these visualization types to forecast sales pipeline within a specific time frame.
Waterfall charts are useful in displaying a host of data beyond sales and sales pipeline. This real life example is a waterfall chart that displays how the EEC/EU region grew and shrank throughout the years up until Brexit.
When to Use a Waterfall Chart
Use this chart to show the breakdown of a whole number. These visualization types make it easy to understand how specific variables impact a specific value over time.
Line Graph: Tesla Vehicle Delivery History
A line graph (also known as a line chart) shows trends and progress over a specific time. Take for example this real life illustration of Tesla's Vehicles Delivery History since 2016. This line graph is clearly illustrating the exponential growth of the Model 3 and Y while a steady decline in the delivery of Tesla’s model S and X.
When to Use a Line Graph
In my view, line graphs are best used to illustrate trends and as well as showcasing comparative differences. Within Revenue Operations, you can use these graphs to highlight sales trends over a period of time. Add in multiple lines to showcase specific products and how their sales are also progressing or declining.
Scatter Plot: Populations in the World
A scatter plot is a graph type that allows you to see the relationship between two variables. These graph types are also used to reveal distribution trends as well.
In the real life example below you can see the comparison drawn between Birth Rates and Death Rates for different countries. The different colors represent geographical regions while the size of the dots display population size.
When to Use a Scatter Plot
Scatter plots are great for displaying multiple data points just like in our example above. They are best used to show relationships between these various data points. This graph type is also helpful in visualizing distribution patterns such as outliers you may have within your data analysis.
Pie Chart: Spending Benchmarks for SaaS
A pie chart shows how specific categories can make up part of a whole number. Generally, a pie chart displays numbers in percentages and the total sum of all parts needed to equal 100%. In my example below, you can see a pie chart that illustrates spending benchmarks for SaaS companies with more than $20 Million in ARR.
When to Use a Pie Chart
Pie charts make it easy to see how your data is segmented. You can think about leveraging pie charts when looking to segment customer demographics, look at product sales, or even analyzing customer churn data.
Mekko Chart: S&P 500 by Sector
Also known as a Marimekko chart, this type of chart is a visual representation that uses stacked bars of varying widths to represent categories of data. In our example below, you can see how the top S&P 500 stocks fair in terms of size both relative to their industry as well as the index as a whole.
When to Use a Mekko Chart
Mekko charts are great at illustrating things like growth, market share or even doing a competitive analysis. With that said, use Mekko charts when you want to emphasize scale or differences between groups of data.
Funnel Chart: Website Conversions
Funnel charts are excellent for viewing a series of steps and progression through a path. Commonly used to measure the marketing and sales processes and conversion rates, funnel charts are great at visualizing a linear journey. Take for example this funnel below that is measuring website conversion metrics.
When to Use a Funnel Chart
Use funnel charts in your data visualization when you have 4-5 stages of sequential data to display. These charts are very versatile especially for marketing and sales teams as they can be used to report on a wide amount of data such as sales pipeline, website conversion and/or marketing campaign performance.
Bubble Chart: Tech Markets in North America
Bubble charts are an extension of scatter plots and are used to measure the relations between three numeric variables. In the case of our example below, you can see visualization that representings the technology markets in North America broken down by major cities.
When to Use a Bubble Chart
Bubble charts are really helpful in visualizing the relationship between different variables. Within RevOps, bubble charts are great business indicators as they can help examine the relationship between related variables like cost, margins, and price as an example.
Heat Map: Risk Level for Contracting Covid 19
A heat map shows the correlation between two variables and provides a scale of grading such as high to low. For example, this heat map below is a visual representation of the risk level for contracting covid 19 by county within The USA. Americans in red areas are at a higher risk while Americans in green are considered to be at lower risk.
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When to Use a Heat Map
There are several different use cases for this type of chart. Heat maps can be used to understand population density or to visualize your customer base. They are great at displaying a more generalized view of numeric values especially when working with large data sets.
Stacked Bar Chart: Famous Writers' Productivity
Last but not least is one of the most common visualizations I've personally seen being used to measure sales performance often. Stacked bar charts (also known as a stacked bar graph) are great for visualizing how a group of data moves from one column to the other. An uniquely interesting display of this is below in our example. See how each famous writer's productivity varies as it also segmented this further by literary type.
When to Use a Stacked Bar Chart
Stacked bar charts are a good option for measuring sales performance over a given time frame and segmenting by sales team. They help in visualizing outliers in historical trends while also comparing your strategy with your overall performance.
Bringing The Picture Together
Business that want to align their people and strategy should go beyond basic data visualization techniques and begin to invest in robust types of data visualization going forward. With the growth of powerful visualization tools like Tableau, Looker and Domo, it no longer requires a team of data scientists to transform raw data into beautiful data creations that measure KPIS and business performance.
Make sure you tune your visualization to support the needs of your target audience and remember to make the visualization part of the story you are looking to tell. The best data visualizations are ones that are easy to understand by all who wish to interpret it (and not just data science experts), so don’t overcomplicate it. Interactive data visualization can also be a useful tool to keep everyone engaged.