Customer Retention from new Customers in a period of time

[Anonymous]

Hey Everyone, how you all doing?

I have a challenge here in my office.

Every day we have new costumers in our App.

And in order to look at the retetion that we are causing on those new costumers I need to create a graphic just like this one as an example to see the accumullate retention throught the days.

And the dynamic is like this:

Every day we look back to see how many costumers we have in total (all the new ones from all the previous days), that already made more than one order. (This is the retetion, he entered as a new costumer and made a second order or more).

And the retentio is: all the base that made more than one order/all the base 

An important note here is that we can't consider the new costumer in the day that we are looking at.

So... If we are in day 5, we get all the new costumers from day 1 to day 4, see how many of then has already more than one order and divide by all the new costumers from day 1 to day 4.

And kind of do that every single day, to see if the retention increases.

It is important to enphasize that must be in a period of time.

I have a Calendar Table, an Order Table that has client_id on it.

Does anyone know how to crack this one?

Thank you very much in advance.

example below:

[v-shex-msft]

Hi @Anonymous,

According to your description, It sounds like a common data range analysis requirement. For this scenario, I'd like to suggest you take a look at the following link 'start date', 'end date' part to create a formula to analysis:
Before You Post, Read This  

In addition, you can also try to create a new table to expand table records for analysis:

Spread revenue across period based on start and end date, slice and dase this using different dates 

If these also don't help, please share more detailed information to help us clarify your scenario to test.

How to Get Your Question Answered Quickly 

Regards,

Xiaoxin Sheng

[Ashish_Mathur]

Hi,

Share a simple dataset and clearly show the expected result.

[amitchandak]

@Anonymous , Try measures likes these

Today = CALCULATE([Sales],filter(all('Date'), 'Date'[Date] = Max(Date[Date])) )

Rolling all before today = CALCULATE([Sales],filter(all('Date'), 'Date'[Date]< max('Date'[Date])))

New Customer This Period = Sumx(VALUES(Customer[Customer Id]),if(ISBLANK([Rolling all before today ]) && not(ISBLANK([Today])) , 1,BLANK()))

Retained Customer This Period = Sumx(VALUES(Customer[Customer Id]),if(not(ISBLANK([Today])) && not(ISBLANK([Rolling all before today ])) , 1,BLANK()))

Lost Customer This Period = Sumx(VALUES(Customer[Customer Id]),if(ISBLANK([Today]) && not(ISBLANK([Rolling all before today ])) , 1,BLANK()))

Blog on similar topic.

https://community.powerbi.com/t5/Community-Blog/Customer-Retention-Part-5-LTD-and-PeriodYoY-Retention-is-only/ba-p/2114497

We check customer's purchase for period(day/month etc)  and complete time period before that

then use isblank to play magic

or

Customer Retention Part 1:
https://community.powerbi.com/t5/Community-Blog/Customer-Retention-Part-1-Month-on-Month-Retention/ba-p/1361529
Customer Retention Part 2: Period over Period Retention :https://community.powerbi.com/t5/Community-Blog/Customer-Retention-Part-2-Period-over-Period-Retention/ba-p/1377458