Customer Analysis
If you are eager to measure your progress regarding your customer base: the frequency of their purchases and the churn rate of various cohorts, then this template is for you.
This template helps you discover insights about the development of your customer base through the use of cohorts and segmentation. Moreover, this analysis shows retention and churn rates, and their changes over time. Lastly, KPIs have been put in place for a quick reference of the most important metrics about your clients.
Note: If you connect data to Business Intelligence tools for the first time, please refer to our tutorial on Data Studio or Power BI first. Also, this report is created primarily for data exported by ROIVENUE. If you try to import your own data, the whole report may fail, and you will have to make every single component compatible.
This report is focused on the analysis of your customers, the revenue that comes from each customer group and their order reoccurrence over time.
In this article, you will learn how this helps you manage your business. The KPIs we are working within these reports are related to:
- Average revenue and profit per customer
- Number of Orders per Customer
- Customer Segmentation ( New / Returning / Lost Customer)
- ... and more.
When analyzing a customer base, segmentation is the first thing that comes to mind. This is especially important for e-shops that are targeting a variety of clients. The segmentation in this report is based on revenue (each segment represents 25% of the total customer base), the time of purchase (new customers, returning customers, and lost customers) or a combination of the two.
Our analysis gives an in-depth look into each category of customers with the ability to filter down, even further, based on the channels that brought them. The slicer presented in the dashboard allows dynamically selecting when a customer will be considered lost - for example, some companies may consider a client lost after a month, while others may consider a client lost after six months. Lastly, the chart allows comparison between each of these groups, making discovering insight even faster.
Through the use of revenue segmentation, the report allows quick analysis of each group. The report also shows the use of Pareto's rule in your business. The top segment, the bright blue color, represents the top 20% of customers. Moreover, one can also see the consistency or volatility of revenue.
Lastly, the key piece is the cohort analysis. A cohort is a group of people who are tied together by some characteristic. Here, that characteristic is when they placed an order. See the count of customers or the percentage of customers coming back to your business based on the this.
Having clear information about how many people are sticking with the company is vital for assessing and creating targeted customer retention strategies. The cohort analysis even shows the average revenue and profit coming in from each cohort.
Using this template with Power BI, due to the nature of the software, requires two separate data exports - one for the Orders dataset, and another for the Customers dataset. Google Data Studio doesn't carry this same requirement and the instuctions for that platform can be seen further down.
1) Select the Orders dataset on the Data Source tab.
2) For type of query, select Aggregated. The Export Periodicity depends on your needs: if this is a one-time analysis or if it needs to be refreshed daily, choose accordingly.
3) Select the following dimensions and measures.
4) The next steps: filters and date range, depend on your needs. If you are not sure, what each of the tabs means, it is described in more detail in this tutorial.
5) Destination - the last step of export - must be set to CSV.
1) Select the Customers dataset on the Data Source tab.
2) Select Source Data. The Export Periodicity depends on your needs: if this is a one-time analysis or if it needs to be refreshed daily, choose accordingly.
3) Select the following columns.
4) For the next steps: attribution model, filters and date range; ensure that you select the same selections as made in the previous section.
5) Destination - the last step of export - must be set to CSV.
Once you have your data exports ready, please use this tutorial to supply the ROIVENUE data into Power BI.
1) Select the Orders dataset on the Data Source tab
2) Select Source Data. The Export Periodicity depends on your needs: if this is a one-time analysis or if it needs to be refreshed daily, choose accordingly.
3) Select the following columns:
4) The next steps: attribution model, filters and date range; also depend on your needs. If you are not sure what each of these tabs mean, it is described in more detail in this tutorial.
5) Destination - the last step of export - must be set to Google Sheets.