Kalpa Connect

Kalpa Connect

Mobile, broadband and subscription services. The unit where the people who make a number look good have already left, and where almost every metric is a blend of populations that should never have been averaged.

Code CON. The home of survivorship, cohort mixing, and the gap between predicting something and being able to do anything about it.

Where it sits in the locked ladder

Build 3, Week 9. The stakeholder is Ananya Bose, COO, and her problems are the Week 7 and 8 text problems at telecom scale. Every sub-problem carries an output contract and a cost ceiling, which is what makes them different from the Week 8 exercises:

#	The sub-problem	The contract on it
1	Churn early warning from support text	An action window that a retention team can actually use
2	Ticket triage	A fixed schema the output has to match every time
3	Incident summarisation	A citation contract
4	Plan recommendation	A refusal rule
5	Reply drafting	A cost ceiling, and repeatability

The AI-free observed debug drill runs on the Wednesday morning of that week: each learner debugs a deliberately broken training loop from evidence alone.

Connect is also the last of the three transfer domains from Week 5, usually on churn and support.

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1. Who runs it, and what each of them wants

Role	Measured on	What they want to hear	What they will resist
VP Subscriptions	Blended retention, on a board slide	That retention improved and there is a reason to be proud of	A within-channel view that shows the improvement was a mix shift
Head of Acquisition	Signups this month, cost per signup	That the cheap channel is working	Being charged for what happens to those subscribers next year
Head of Retention	Saves, and offers accepted	That targeting the highest churn scores works	Being told the highest scorers have already decided
Network Operations lead	Incidents, and mean time to restore	That the network is stable	A definition of incident that cannot be reclassified
Head of Support	Containment and cost per contact	That the assistant handles ninety percent	A per-issue count that includes the customer's three retries

The tension that generates most cards here: acquisition is measured monthly and retention over a year, so a quarter can be won by buying subscribers who will churn after the reporting window closes. Every survivorship card in the bank has its natural home in this unit.

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2. The data estate

What exists	The catch it carries
Signup date, plan, acquisition channel, cancellation date	Channel mix moves between cohorts, so the blended rate answers a question nobody asked
Usage and billing records	Involuntary churn from a failed payment sits in the same column as a decision to leave
Support tickets and chat transcripts	The transcripts record what agents said, including what they said wrongly, with no label for which
Network incident logs	What counts as an incident is a classification made by the team being measured
The plan catalogue, with historical versions	Plans were renamed, so a plan-level trend crosses a rename and looks like a shift in demand

The absence that defines the unit: there is no record of which promotion ran on which channel. Every before-and-after comparison in Connect is missing the one variable that would explain it, and asking for it is the move.

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3. The KPIs, and how each one is gamed

KPI	What people say it is	The denominator that decides it	How it breaks or gets gamed
Churn rate	Cancellations divided by the base	The base at the start of the period, split voluntary from involuntary	Involuntary churn from failed payments hides inside the same number and has a completely different fix
Retention by cohort	Share still subscribed at month three	Within channel, cohort by cohort	Cut a cheap high-churn channel and the blended rate rises while total retained subscribers fall
ARPU	Revenue divided by subscribers	Which subscribers, and whether a suspended line counts	Suspending rather than cancelling keeps the numerator and shrinks the denominator
Customer acquisition cost	Spend divided by signups	Per channel, within an attribution window	A shorter attribution window makes any channel look better
Lifetime value to CAC	The health of the business	A forecast divided by a fact	LTV is a projection presented as a measurement, and its assumption is rarely written down
Satisfaction	How customers feel	Respondents, and the response rate	Nine percent response measures the people who still had the energy to answer
Containment	Contacts resolved without a human	Per issue, never per session	A customer who retries four times gives you three extra contained sessions
Mean time to restore	Incident response	Per incident, with a fixed definition of incident	Reclassify a long incident as three short ones

The KPI this unit exists to teach: absolute retained subscribers alongside the rate. A rate can improve while the business shrinks, and Connect is where a learner sees that happen with their own hands.

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4. Case families, mapped to modules

Module	Case family here	The teaching version
1 Foundations of AI and Data	Cohort retention, blended against within-channel, and the definition change in a release	S-CON-AN-02, the retention that improved because the unhappy left
2 Applied Machine Learning	Churn prediction, the action window, uplift against propensity, plan recommendation	Predicting churn nobody can act on in time, then fixing the label rather than the model
3 Deep Learning and Neural Networks	Usage sequences and anomaly detection on network telemetry	Where a threshold rule is the baseline that has to be beaten
4 Natural Language Processing	Support ticket triage and routing	Class imbalance and a label taxonomy nobody agrees on
5 and 6 Generative AI	Network incident summarisation, a plan-question assistant	An evaluation set built by the people who wrote the knowledge base, which is the trap
7 Production AI	Guardrails, containment measured honestly, and a control that fails open	S-CON-GA-16, where blocks fell to zero for the wrong reason
8 and 9 Agentic AI	Multi-agent escalation between triage, retention and billing	Where handoff between agents becomes the failure surface

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5. The situations hosted here

Page	Cards
Analytics	S-CON-AN-02 (the retention that improved because the unhappy left), S-CON-AN-08, S-CON-AN-09
Machine learning	S-CON-ML-10 to S-CON-ML-12
GenAI and agents	S-CON-GA-14 to S-CON-GA-16

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6. What Connect must never be used for

1. A card whose twist is only arithmetic. Simpson's paradox is a mechanism here, and a card that is nothing more than the paradox restated is a riddle rather than a situation.
2. Real telecom data or any operator's published figures presented as Kalpa's. Kalpa's numbers are invented and labelled as invented.
3. The first survivorship lesson and the first cohort lesson on the same day. They are the same idea wearing two coats, and a room needs to meet them a week apart.