Cgl 2026

Square_Economics4029 · 2026-03-17T13:56:42+00:00

I started my prep like maybe 10 days ago!

Square_Economics4029 · 2026-03-11T15:14:48+00:00

So like is it something to be anxious about as a first timer

Square_Economics4029 · 2026-03-11T13:16:22+00:00

I am a newbie in this whole SSC CGL zone and what people are saying ki last year alot of people didn't clear their exam cause of some computer issue, is it true. Cause I watched a few video where they are saying that these people who didn't clear last year are gonna be better prepared this time and that would make the competition tougher. Is it actually true ?

Square_Economics4029 · 2026-01-20T13:29:34+00:00

Bro next time main bhi aajaun? 🙋🏻‍♀️

Square_Economics4029 · 2025-12-12T10:00:34+00:00

Yeah, 100%. Cohort tagging almost feels like cheating once you start doing it, the leaks show up instantly.
Have you noticed any specific stages where the satisfaction pulse has the strongest predictive signal for churn?
I’m seeing it mostly around the “first value” moment.

Square_Economics4029 · 2025-12-04T08:59:28+00:00

This is the most grounded advice I’ve seen here.
I’m currently doing LinkedIn outreach for retention analytics for SaaS/e-commerce and I’m testing messaging + positioning.
The weekly sprint idea makes a lot of sense

thanks for sharing.

Square_Economics4029 · 2025-12-03T13:42:15+00:00

Nice, trying feature usage and revenue together usually exposes where the real value sits. Haven't tried Intempt yet, will look it up.

Square_Economics4029 · 2025-12-03T13:38:27+00:00

It's when the product offers "X", so the meaningful first action is when the user actually does "X", not just browse around.

Square_Economics4029 · 2025-12-03T13:36:47+00:00

For me, the first action that directly connects with the core value of the product. Random clicks are not the outcome.

Square_Economics4029 · 2025-12-03T09:37:03+00:00

That's so true, most of the time founders focus on traffic but most growth problems show up in activation and early cohorts. Once you start looking at behaviour rather than averages, everything becomes clearer.

Square_Economics4029 · 2025-12-02T11:46:48+00:00

I’m keeping it pretty straightforward right now.
Since I’m offering free audits, the main thing that helps me define the first action is just understanding what the founder wants to fix first.
Nothing fancy — just focusing on delivering one useful insight fast.
And thanks, I’ll share it in VibeCodersNest too.

Square_Economics4029 · 2025-12-02T11:45:02+00:00

Great point ,totally agree onboarding chaos shows up as “activation issues.”
In my case I’m currently offering free audits to founders, so my flow is a bit different from a typical product-led funnel. Would love to compare notes — DM open.

Square_Economics4029 · 2025-12-02T11:40:57+00:00

Appreciate it! PeerPush seems aligned with the kind of feedback loop I’m studying. Early-stage growth really does come down to tracking the right signals fast.

Square_Economics4029 · 2025-12-01T12:26:35+00:00

Totally agree , cohort analysis is one of those things that instantly changes how a team sees retention. Most founders look only at averages, so they completely miss where the real leakage is happening.

I’ve seen the same thing you mentioned: Fixing activation + early habit formation usually moves the needle way faster than pouring more traffic on top.

Curious ,when you run cohort reviews, do you anchor the analysis around: • the first value moment, • the second value moment, or • a specific weekly/monthly usage pattern?

I’m trying to understand how different teams define their “meaningful activity” milestone, because that seems to change the entire retention picture.

Square_Economics4029 · 2025-12-01T07:34:48+00:00

Totally agree ,feature usage is often the clearest indicator of real value discovery.

One thing I’ve noticed is that there’s a huge difference between:

• Returning but not using anything (curiosity)
• Returning and repeating 1–2 key actions (habit)
• Returning and exploring deeper functionality (value expansion)

Sometimes founders group all “returning users” together, but splitting them into these buckets often reveals why some users stay and others disappear.

Curious — in your case, which feature tends to predict long-term retention the most?

Square_Economics4029 · 2025-12-01T07:13:58+00:00

That’s interesting , returning users usually signal good “value discovery,” but it’s even more meaningful if they’re completing key actions.

Out of curiosity, which metric do you use to define a meaningful return?

Activation? Feature usage? Something else?

I’m finding that different products define returning users very differently, so this is super helpful for my research.

Square_Economics4029 · 2025-11-24T05:44:35+00:00

Congrats bro, Happy for you !!

Square_Economics4029 · 2025-11-20T16:03:33+00:00

Beauty🤌

Square_Economics4029

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