Transactional Customer Churn
This topic demonstrates how to set up a dashboard that helps you define churn for your transactional customers.
This analysis contains advanced calculated columns.
Calculated Columns
Columns to create
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customer_entitytable -
Customer's lifetime number of orders -
Select a definition:
Count -
Select a table:
sales_flat_order -
Select a column:
entity_id -
Path: sales_flat_order.customer_id = customer_entity.entity_id
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Filter:
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Orders that are counted
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sales_flat_ordertable -
Customer's lifetime number of orders -
Select a definition: Joined column
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Select a table:
customer_entity -
Select a column:
Customer's lifetime number of orders -
Path:
sales_flat_order.customer_id = customer_entity.entity_id -
Filter:
Orders we count -
Seconds since created_at -
Select a definition:
Age -
Select a column:
created_at -
Customer's order numberis created by an analyst as part of your [DEFINING CHURN] ticket -
Is customer's last orderis created by an analyst as part of your [DEFINING CHURN] ticket -
Seconds since previous orderis created by an analyst as part of your [DEFINING CHURN] ticket -
Months since orderis created by an analyst as part of your [DEFINING CHURN] ticket -
Months since previous orderis created by an analyst as part of your [DEFINING CHURN] ticket
Metrics
No new metrics!
Reports
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Initial repeat order probability
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Metric A: All-time repeat orders
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Metric:
Number of orders -
Filter:
Customer's order number greater than 1 -
Metric B: All-time orders
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Metric: Number of orders
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Formula: Initial repeat order probability
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Formula:
A/B -
Format:
Percent -
Time period:
All time -
Interval:
None -
Chart type:
Scalar -
Repeat order probability given months since order
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Metric A: Repeat orders by months since previous order (hide)
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Metric:
Number of orders -
Perspective:
Cumulative -
Filter:
Customer's order number greater than 1 -
Metric B: Last orders by months since order (hide)
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Metric:
Number of orders -
Perspective:
Cumulative -
Filter:
Is customer's last order? (Yes/No) = Yes -
Metric C: All-time repeat orders (hide)
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Metric:
Number of orders -
Filter:
Customer's order number greater than 1 -
Group by:
Independent -
Metric D: All-time last orders (hide)
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Metric:
Number of orders -
Filter:
Is customer's last order? (Yes/No) = Yes -
Group by:
Independent -
Formula: Initial repeat order probability
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Formula:
(C-A)/(C+D-A-B) -
Format:
Percent -
Time period:
All time -
Interval:
None -
Group by:
Months since previous order -
Show top.bottom: Top 24 categories, sorted by category name
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Chart type:
Line
The initial repeat order probability report represents the Total Repeat Orders / Total Orders. Every order is an opportunity to make a repeat order; the number of repeat orders is the subset of those that actually do.
The formula you use simplifies to (Total repeat orders that occurred after X months)/ (Total orders that are at least X months old). It shows us that historically, given that it has been X months since an order, there is a Y% chance that the user places another order.
Once you have built out your dashboard, the most common question asked is: How do I use this to determine a churn threshold?
There is no “one right answer” to this. However, Adobe recommends finding the point where the line crosses the value that is half of the initial repeat probability rate. This is the point where you can say “If a user is going to make a repeat order, they probably would have done it by now.” Ultimately, the goal is to select the threshold where it makes sense to switch from “retention” to “reactivation” efforts.
After compiling all the reports, you can organize them on the dashboard as you desire. The result may look like the image at the top of the page
If you run into any questions while building this analysis, or simply want to engage the Professional Services team, contact support.