The Routing Review: Teardown of a Save-Campaign Rule Set
Objective: Given 4 synthetic save-campaign automation rules (the trigger-to-workflow logic that fires when a risk signal crosses threshold), identify which ones route the signal to the wrong save motion and explain why the mismatch costs the account.
You're auditing Snowflake's, the cloud data-warehousing company, retention-ops rule set ahead of a quarterly review of save-campaign intervention success rates.
Review each rule against the lesson's signal-to-motion mapping and composite-scoring principle, flag defects like a sentiment trigger routed to an automated sequence or a flat queue with no priority tiering.
Before you start
What you'll need
Free path (everything below is enough to finish)
Free, sufficient for a structured review checklist across 4 rules
The process
Specimens to review
Is this the correct save motion for a usage-decline trigger? If not, what's wrong?
RULE: IF login_frequency drops more than 40% over 14 days THEN send a single automated 're-engagement' email from the marketing team and close the alert.
Specimen: synthetic, realistic
Does this routing match the lesson's signal-to-motion mapping?
RULE: IF support-ticket sentiment score crosses the negative threshold twice in 30 days THEN enroll the account in the standard 4-email automated win-back sequence.
Specimen: synthetic, realistic
Is this routing correct as written, or does it have a defect?
RULE: IF an account uses fewer than 30% of core features for 3 consecutive weeks THEN route to a targeted onboarding walkthrough of the specific unused feature most correlated with retention.
Specimen: synthetic, realistic
Does this composite-scoring setup match the lesson's framework?
RULE: IF login_frequency drops more than 40% OR support sentiment crosses negative OR feature adoption falls below 30% THEN treat all three cases identically: assign the account to the CSM's general outreach queue with no priority tier.
Specimen: synthetic, realistic
Final deliverable
A defect log across all 4 save-campaign rules: which route correctly, which don't, and the specific fix for each defective one.
See a reference example
Freshworks, save-campaign rule audit (excerpt) RULE 1 (usage-decline): PASS with note — add a recheck for other signals before auto-closing RULE 2 (sentiment): FAIL — routed to automated sequence, must route to human CSM call RULE 3 (adoption-stall): PASS — matches lesson framework RULE 4 (composite): FAIL — flat queue, no tiering, no motion-matching by dominant signal
Success criteria
You're done when you can:
- Correctly identifies the sentiment-to-automated-email misrouting as the critical defect
- Recognizes the flat no-tier queue as violating the composite-score requirement
- Does not flag the two correctly-routed rules (usage-decline, adoption-stall) as defective