What is quadrant analysis?
You can measure or compare a limited set of business data using a chart or KPIs, but if you have a large amount of data and want to pinpoint the areas to focus on, a quadrant analysis may be more suitable.
Quadrant analysis scatters the data that you want to analyze or measure into four quadrants. You can analyze data such as the type of campaigns versus the revenue generated to identify the campaign that was most effective or leads created versus lead source to identify the source you are gathering more leads from for the company.
Components of a quadrant analysis
Axis: The parameters the data is plotted in the graph based on are defined in the X and Y-axes. The X-axis is horizontal and the Y-axis is vertical. For example, if the X-axis represents the Number of Deals and Y-axis represents the Revenue Generated, the data will be plotted to the appropriate quadrant based on these two metrics.
Grouping: You can specify how you want to group the data that is measured on the X and Y-axes. For example, Deal Owner, Created Date, Deal Stage. If you group based on the Deal Owner, you will be able to see the number of deals created by each deal owner and the revenue generated by them.
Benchmark: The threshold limit for the X and Y-axes can be defined as the Benchmark. This splits the axis into four quadrants.
Types of quadrant analysis
There are two types of quadrant analysis: Standard and Advanced.
This analysis allow you to visualize the data based on the following factors:
- The module you have chosen
- How you want to group the data, e.g. by Date or Dimension
- The metrics you define to visualize the data, the X and Y-axis, e.g. X-axis = Number of deals, Y-axis: Sum of revenue.
- The benchmark
For example, you create a quadrant analytics to view the Deals by Salesperson versus Revenue Generated. Once all the components are defined, the data will be plotted in the appropriate quadrants.
From the above quadrant analysis, you can infer the following:
- Henry John has a lot of deals and has generated a lot of revenue for the company. He is in the first quadrant.
- Fatimay Zeref has few deals but has generated a lot of revenue. She is in the second quadrant.
- Steve Wright has few deals and has not generated a lot of revenue. He is in the third quadrant.
- Ian Bothom has a lot of deals and has not generated a lot of revenue. He is in the fourth quadrant.
From this, you can infer that the sales reps in quadrant one and two are performing better than the ones in quadrant three and four.
Advanced analysis is an extension of standard analysis which allows you to define how you want to group the data that you want to visualize in four quadrants. This type of analysis can be used to determine things like the type of business that generates the most revenue for the company or the deals in different stages of the sales pipeline. This will be indicated by the different sizes of the plot area. The larger the value, the bigger the plot area will be. You can use advance analysis to visualize the data based on:
The module you have chosen.
- How you want to group the data, e.g. Based on Deal Stage.
- How you want to measure the grouped data, e.g. the number of deals.
- The metrics you define to visualize the data, the X and Y-axes, e.g. X-axis = Number of deals, Y-axis = Sum of revenue.
- The benchmark.