12. Comparing Customer Distribution by Plan

 
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Overview

Interslice wants larger customers to use its more expensive plans. In this lesson, we’ll see if this is the case, by creating bins to analyze the number of users in a company.

Summary

Creating bins for user numbers

  • Some customers can have over 1,000 users of the product
  • In order to analyze this field, it’s therefore useful to divide the field into bins
  • Due to the distribution, we analyze only the bins covering companies with up to 300 users

Analyzing user distributions

  • Overall, most of the customers of Interslice have a small number of users.
  • Interslice want to investigate if larger companies are subscribing to the more expensive plans
  • When we compare plans, we can see that the Advanced plan has more customers with more than 50 users.
  • The Enterprise plan is similarly more popular than the advanced plan with larger companies, but not by as significant an amount

Transcript

In the previous lesson, we saw that customers with more users are given discounted prices when they subscribe to more expensive plans. We also noticed that no discounts were offered on the cheapest plans. Even for the largest customers.

Innerslices management has confirmed that this is a conscious decision. The company wants to encourage it's larger customers to use more expensive products, as these products are designed with large businesses in mind. In this lesson, we'll investigate the effectiveness of this strategy by comparing the distribution of customer size for each subscription plan. We'll start by creating a copy of the current report page.

We'll right-click the tab. And select duplicate page.

This allows us to retain the two slicers and the page level filter.

If we look at the X-axis of the line chart, we can see that customers size varies considerably. Ranging from single individuals to companies with over 1000 users.

Given this information, the best strategy for analyzing the distribution of customers is to create bins using the number of licenses field.

First, we'll clear the selections from both slicers.

And delete the two charts.

We'll then create the bins.

We'll navigate to the transactions table. Right-click number of licenses.

And select new group.

We'll keep the group type as bins.

Change the bin size to 25.

And press okay to create our bins.

We'll now use these bins to create a column chart.

We'll add a cluster column chart and expand it to cover most of the canvas.

We'll add the new bins field to the axis well.

And customer ID to the values well.

We'll then change the aggregation of customer ID to distinct count. We can see the distribution is skewed as most customers have a relatively small number of users.

Let's create a filter to focus on the important part of the data.

We'll scroll down to the filters area of the visualizations pane.

And adjust the visual level of a filter for the bins to be less than 300.

This chart tells us that most of Innerslices customers have a relatively small number of users.

The most common bin is the second one. Which counts the customers that have between 25 and 50 licenses. While this chart shows us the overall distribution of users. We want to analyze the distribution by plan.

To that end, we'll navigate to the plans table.

And add the plan name field to the legend well.

We now have individual columns for each of the four plans.

Let's limit our comparison to business customers by selecting business from the type of customer slicer at the top of the report.

We also want to compare the plans two at a time.

Let's select the plan name slicer.

Navigate to the formatting section of the visualizations pane. Open selection controls.

And turn single select off.

We'll start by selecting the basic and standard plans.

These two plans seem to have a similar distribution. Although the standard plan has more subscribers in each bin.

This is probably encouraging for the company. Next, we'll compare the standard in advanced plans.

From this chart, it looks like the company's efforts are working. The standard plan is more popular among companies with fewer than 50 users. But the advanced plan is more popular for higher bins.

Innerslice seems to be successfully pushing larger companies to the advanced plan.

Finally, we'll compare advanced and enterprise.

The most notable feature here is that none of the subscribers of the enterprise plan have fewer than 50 users. This is another decision taken by the company to restrict the plan to large customers.

It also seems that the enterprise plan is slightly more popular among companies with more than 75 users. It would appear that Innerslice is doing well at selling the advanced plan to large customers. But there's room for improvement in enterprise sales. Let's stop the lesson here.

As we've seen, bins can be used to conduct an analysis of a field that would be difficult to analyze continuously. In the next lesson, we'll look at Power BI's forecasting capabilities and see how to predict future churn rates.

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