See what the shape of a churn curve reveals about onboarding, product-market fit, and long-term value. Practice reading slopes, tails, and hazard spikes to diagnose what to fix next.
A steep early drop in the churn curve usually points to ______ problems.
DNS latency
onboarding or fit
bot traffic
cookie expiration
A long, flat tail in cohort curves indicates meaningful ______ value.
session-only
one-time coupon
ad-view
long-term
The area under the retention curve approximates expected ______ per customer.
active periods
advert impressions
SKU count
support tickets
A convex-down (quickly flattening) curve generally signals improving ______ over time.
survival probability
pixel quality
inventory depth
timezone routing
A mid-cohort spike in hazard (sudden drop) often aligns with a ______ event.
theme switch
billing or renewal
DNS cache flush
ad frequency cap
Comparing adjacent cohorts reveals if product changes shift the curve ______.
left or right only
up or down
into vectors
to grayscale
If cohorts with discounts show steeper later drops, the likely cause is ______ churn.
promotional
cookie-based
DNS-based
hardware
A curve that never flattens and trends toward zero suggests no durable ______.
loyal base
ad budget
schema
geo replication
Segmenting curves by channel helps identify acquisition sources with ______ retention.
identical
undefined
irrelevant
higher
Normalizing curves by first purchase instead of signup is useful for commerce because it aligns to ______ timing.
value realization
cookie consent
DNS propagation
ad viewability
Starter
Revisit curve shapes and what they imply about onboarding and loyalty.
Solid
Good reads—dig deeper into hazard spikes and channel-level segmentation.
Expert!
Superb—your curve diagnostics can guide product and pricing moves.
