This playbook focuses on helping you look at your existing cancellation data, identify where customers are struggling today, and specifically target those struggle points in your cancel flows.
Looking for instructions on how to set up your cancel survey?
Check out our Setting Up Your Cancellation Survey article
TLDR: Use Your Current Retention Data to Inform Your New Cancellation Survey
Before enabling your new cancellation survey, set your brand up for success by going through this checklist:
☐ Reviewed your top cancellation reasons by volume
☐ Identified which products are most commonly canceled within each reason
☐ Chosen 1–2 high-impact cancellation reasons to optimize first
☐ Mapped each selected reason to a clear save action (delay, swap, discount)
☐ Decided where conditional logic should apply (e.g., show swap only if delay is skipped)
Completing this pre-work ensures you’re using the data you already have to intentionally design your new cancellation survey—not guessing once it’s live.
Step 1: Review your existing cancellation data
Before enabling or expanding your new cancellation survey, start with a quick data audit. This step is about understanding where customers are struggling in your current cancellation experience.
Look at:
Top cancellation reasons (ranked by volume)
Products most commonly canceled within each reason
Patterns (one product dominating a reason vs. evenly split)
This pre‑work helps you decide which save actions are most likely to work before you build anything.
Ask yourself:
Are customers canceling because of timing, quantity, price, or product fit?
Are certain SKUs over‑represented in specific cancellation reasons?
Step 2: Choose one cancellation reason to optimize first
Don’t try to optimize everything at once. Start with a single, high‑impact cancellation reason.
Example: “I have more than I need”
This reason usually signals a timing or quantity issue, not dissatisfaction with the product itself.
From your data, you might see:
One SKU driving most of these cancellations (for example, grapefruit flavor soda)
The rest of cancellations spread across other products
That insight should directly inform the save offers you set up.
Step 3: Match the cancellation reason to the right save action
Once you understand why customers are canceling, you can layer in relevant save offers like delay, swap, or discount to directly address that reason.
Example setup for “I have more than I need”
Recommended save actions:
1. Delay order
Ideal as the first option
Configure up to 4 delay options
Directly addresses over‑inventory without changing the subscription
2. Conditional swap action
Shown if the customer skips the delay
Choose either a “Swap Catalog” or “Swap Custom” action, giving full flexibility on swap options
Useful if variety fatigue is contributing to over‑ordering
Example flow:
Customer selects “I have more than I need”
Offer a delay order action
If they bypass the delay, present a swap (for example, switching flavors)
This keeps the experience relevant without overwhelming the customer.
Step 4: Use product‑level data to refine your offers
Not all cancellations are equal—even within the same reason.
If one product appears disproportionately:
Consider product‑specific swaps (e.g., grapefruit soda → watermelon)
Pro-tip: Reference Stay’s Product Performance Analytics to identify your hero product(s) to help decide what customers should swap to!
Test product‑specific messaging or save actions
If cancellations are evenly split:
Keep save offers broader and simpler
The goal is alignment—not complexity.
Step 5: Repeat the framework for other top reasons
Once you’ve optimized one cancellation reason, apply the same thinking to the next.
Example: “Product is too expensive”
This reason typically signals price sensitivity, not lack of interest.
Recommended save actions:
Discount code as a save offer
Optional segmentation by product if one SKU drives the majority of cancellations
Step 6: Build your cancellation flow intentionally
When configuring your new cancellation survey, think of this as the final step in the data-driven flow: data → insight → action.
Start with data‑backed save offers
Segment those save offers so they are offered to the right customers at the right time
A focused flow converts better than a complex one.
Summing it Up
Taking a look at your existing RetentionEngine data, outlining your customers’ biggest struggle points using cancellation reasons, and then setting them up for relevant save offers will help you get the most out of the new Cancellation Survey in Stay AI!