Arman

Building a churn prevention tool for small SaaS teams. Currently in private beta

[Arman @TRW_Arman]

@epsifund Exactly — month-2 ghost vs month-8 non-renewal
are completely different problems but most
dashboards treat them the same. Cohort curves
tell the real story

[Arman @TRW_Arman]

@eldridqe @klausbyskov Would love that — DM me happy to get you access

[Arman @TRW_Arman]

15 days since beta opened. 0 confirmed users yet.

Not giving up — just being honest about where we are.

Getting people to care is harder than building.

Back to outreach.

[Arman @TRW_Arman]

@dipaaksarkar Smart dunning handles the 30% involuntary side
well the other 70% is behavioral, customers
who are fully paying but quietly disengaging
and nobody catches it until they cancel

[Arman @TRW_Arman]

@newonpolsia Login frequency drop is the earliest signal and
the most ignored — by the time failed payments
and shrinking seats show up the customer already
checked out weeks ago

[Arman @TRW_Arman]

@valerioamirani @0xVaha @SomieCITYY @vangrid_io @ZenovayDX 72 hour churn is real but the other wave hits
weeks later customers who activated fine but
slowly stopped logging in and nobody noticed
until the cancellation came

[Arman @TRW_Arman]

@BusinessxTechHQ No exit survey and no win-back is the reactive
side — the bigger gap is before they even reach
cancel, when they stopped opening emails and
logging in weeks earlier

[Arman @TRW_Arman]

@henry_purchase @samdblond 16 to 6 is a massive drop curious what actually
moved the needle, was it catching disengagement
early or more reactive fixes like cancellation
flows and win-backs

[Arman @TRW_Arman]

@Saasnext_db 9% from failed cards is fixable with dunning —
the harder problem is the other side, customers
who are fully paying but silently disengaging
weeks before they decide to cancel

[Arman @TRW_Arman]

@ZainabAwogbade Re-engagement automation should be on this list —
catching customers who go silent after onboarding
is just as important as the onboarding itself

[Arman @TRW_Arman]

@eldridqe @klausbyskov Gym churn and SaaS churn have the same root
members/customers go silent before they cancel
and most platforms only catch it after the fact

[Arman @TRW_Arman]

@iamspiggle Churn bucket gets ignored until it's too late
most teams only see it in the MRR dashboard after
the cancellation hits, not while the customer is
quietly disengaging weeks before

[Arman @TRW_Arman]

@fuyu_kasumii Nice try

[Arman @TRW_Arman]

@SuzieLeevj Exactly and that's the problem we're solving.
Built a tool that watches login behavior and
automatically re-engages customers before they
reach the cancel button. Would you want to take
a look?

[Arman @TRW_Arman]

@kevinyun Expansion revenue is a great retention lever but
it only works for customers still engaged — the
silent ones who stopped logging in 3 weeks ago
never make it to the upgrade conversation

[Arman @TRW_Arman]

@zuess05 Catches inactive SaaS customers before they churn
and re-engages them automatically

[Arman @TRW_Arman]

@Tanjim38 Experience churn is the hardest to catch because
there's no complaint — customers just quietly stop
logging in and you find out when the cancellation
hits weeks later

[Arman @TRW_Arman]

@tarush_agarwal_ @cekuraAi Losing customers on purpose to find the right ICP
is underrated — most teams are so focused on
preventing every churn they never figure out which
customers were never a fit anyway

[Arman @TRW_Arman]

@starter_story Phase 3 is the one most skip — identifying power
users is easy but catching the ones who are quietly
disengaging before they churn is where most teams
lose revenue without even noticing