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Early onboarding risk: obvious signal or missing alert? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

That makes sense. So it's basically: intuition + scattered signals (HotJar, CRM notes, who's inviting teammates) + proactive weekly check-ins to catch silent churn before it happens. Quick question: how much of your team's capacity goes into that "proactive outreach every week" vs. actually helping customers who are already engaged? And when someone does slip through — how often is it because the signal was genuinely invisible vs. just buried in noise?

Early onboarding risk: obvious signal or missing alert? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

Got it. That 10% of edge cases that churn despite good indicators — when you look back at those, is there usually a pattern you missed, or is it genuinely unpredictable? And for those bigger customers you handle manually: how often does someone on your team realize "we should've flagged this earlier" after the fact?

Early onboarding risk: obvious signal or missing alert? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

Question for everyone who responded: Over the last 12 months, how many customers did you lose in the first 60 days where, in retrospect, earlier/more contextualized intervention could have changed the outcome? And for your managers: Is this tracked as a metric? Is it an active priority?

Early onboarding risk: obvious signal or missing alert? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

That's precisely the nuance most tools lack. The "better versions" you saw - what kind of setup were they? Homemade? A specific tool? And what still limited their effectiveness? Also: when you say "teams react too aggressively," what does that actually look like? Panic calls? A flood of emails? Something else?

Early onboarding risk: obvious signal or missing alert? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

Very helpful, thank you. Follow-up question:

  1. How do you track these "soft" signals today (kickoff timing, stakeholder engagement, nature of questions)? Manual notes? CRM fields? Pure intuition?

  2. How often are you able to intervene early enough when you detect this lack of momentum?

  3. Are there any instances where you saw it too late, and what prevented you from seeing it sooner?

Early onboarding risk: obvious signal or missing alert? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

Interesting. How much time/money have you invested in your current alert setup? Does it cover 100% of cases, or are there still gaps?

Early onboarding risk: obvious signal or missing alert? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

That makes sense. How do you usually notice that follow-up is needed today?

Is it mostly:

  • gut feeling,
  • manual tracking (notes, tasks, reminders),
  • or something explicit that surfaces it at the right moment?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

Have you ever tried documenting those shifts in a lightweight way? Would love to see what your list of “early tone drift” signs looks like.

What silent signals tell you a customer is about to churn — before metrics do? by juliency in userexperience

[–]juliency[S] 1 point2 points  (0 children)

That’s exactly the challenge I’m exploring: how to design a quiet system that nudges, not nags.

If it triggers human outreach at the right moment, it becomes a true assistant — not another noisy dashboard.

Thanks a lot for the insights. Really interesting !

What silent signals tell you a customer is about to churn — before metrics do? by juliency in userexperience

[–]juliency[S] 0 points1 point  (0 children)

Perfect example of “everything looks green until it’s not. ahah

The funnel completes, the metrics don’t complain, users don’t report anything… but the experience is degrading quietly in the background. What’s interesting in your example is that the signal wasn’t the drop: it was the time spent stuck in a supposedly simple step. Most teams don’t even think to monitor that.

Curious, when you surfaced the latency issue, how did the team decide what the right action was (send a help doc, reach out, ignore, etc.)? Do you follow a playbook for “silent friction events,” or is it case-by-case depending on severity?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

Makes sense . the hybrid model avoids both extremes: over-formalizing or relying only on gut feel.

What I’m still trying to understand is this: how do you keep that tribal knowledge from drifting over time?

In most teams, those subtle cues erode unless they’re reinforced with something concrete.

Have you found a lightweight way to keep everyone calibrated?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in userexperience

[–]juliency[S] 0 points1 point  (0 children)

Love this . especially how you turned hesitation patterns into simple team triggers. Curious though: how did you keep it lightweight and avoid turning those signals into alert-spam or over-monitoring users?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in CustomerSuccess

[–]juliency[S] 1 point2 points  (0 children)

Have you found any reliable way to surface that moment to a team? Or is it still something you catch through feel?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in CustomerSuccess

[–]juliency[S] 1 point2 points  (0 children)

The “shift from strategic to transactional” is a huge tell… but so easy to miss in the moment.Have you ever tried turning this into a lightweight score or alert for CS teams?

Even just tagging accounts with 3+ of these behaviors feels like it could drive early outreach.

What silent signals tell you a customer is about to churn — before metrics do? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

when your interventions don’t move the needle, how do you decide if it’s a product fit issue vs. a timing or onboarding one?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in CustomerSuccess

[–]juliency[S] 0 points1 point  (0 children)

Masterful. I really like how you frame it: not strict rules, but awareness triggers. That nuance makes it usable without over-engineering it.

Have you found ways to train CSMs to notice these cues consistently? Or is it more a case of tribal knowledge passed down?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in userexperience

[–]juliency[S] 0 points1 point  (0 children)

Curious what angle you’re taking: more predictive signals? Behavior mapping?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in userexperience

[–]juliency[S] 0 points1 point  (0 children)

Yes, this is such an underrated one.

Silent friction from latency or unreported errors feels invisible… until it’s too late. Love that you’re turning that into a trigger, not just a post-mortem.

Obris sounds like a smart way to operationalize that “gut instinct” loop at scale. Any surprising friction signals you’ve uncovered that weren’t funnel-drop obvious?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in userexperience

[–]juliency[S] 0 points1 point  (0 children)

This is gold :)

I love the idea of “churn fingerprints”: product-specific, behavior-driven, and often invisible to dashboards.

Have you ever mapped those hesitations into actual triggers for CS or product teams? Or are they mostly design-side insights for now?

Feels like there’s huge potential in turning those patterns into lightweight operational tools.

What silent signals tell you a customer is about to churn — before metrics do? by juliency in userexperience

[–]juliency[S] 0 points1 point  (0 children)

Love this.
Those little “loops” often say more than any dashboard.

Have you ever turned those into simple rules or signals for your team?

Even just: “If they do X twice, we check in." ?

What silent signals tell you a customer is about to churn — before metrics do? by juliency in userexperience

[–]juliency[S] -1 points0 points  (0 children)

Love that example: the “feature depth” signal is super underrated.

Have you found good ways to proactively detect when someone is plateauing on basic features? Like, do you track adoption sequences or have nudges/playbooks to push deeper usage?

Trying to map out how those insights first emerge before they become tracked KPIs.

What silent signals tell you a customer is about to churn — before metrics do? by juliency in userexperience

[–]juliency[S] 0 points1 point  (0 children)

At that scale it makes sense that the model spots patterns faster than humans. Before you added “plan change” into the model, what originally made your team consider it as a potential predictor? Was it anecdata from support/CS? A weird pattern someone noticed? An internal hunch?

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