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The right customer at the right tier, every time.
Leadership wants to reduce early churn and customer support costs, without materially slowing gross adds.
Three voices from the onsite shaped how I thought about this.
Target: 6-15% reduction in 90-day early churn within two quarters, validated by component-level A/B testing, without measurable impact on gross adds.
Why this won't slow gross adds. The hypothesis is that the right friction at the top (coverage transparency, tiered identity verification, plan education that sets honest expectations on throttling) filters customers who would have churned in the first 30 days anyway. Higher quality customers, not fewer customers. The answer isn't slower onboarding; it's right-sized onboarding for who's coming through the door.
Four segments to design for, ordered by risk profile.
Already verified, billing history on file. Highest LTV. The current flow probably feels like overkill to them.
Identity and credit history are signals the current flow throws away. They left for a reason, came back for a reason.
Don't currently exist as a segment because Mobile has no referral program of its own. A referral comes pre-qualified by trust.
No existing relationship, no trust signal. Highest fraud risk, highest churn risk, lowest unit economics.
Without internal data, I'm working from industry benchmarks. MVNO and prepaid wireless monthly churn runs 3-5%. The first 90 days carry disproportionate risk; the first 7-14 days are the most predictive of long-term retention.
Four churn drivers that frequently show up:
Cricket Wireless cut early churn 37% by tightening consistency between sales promise, delivered service, and first bill.
The funnel is the foundation, the referral program increases lead quality/LTV, and unified support reduces confusion and churn.
Build onboarding as a library of modular components (coverage check, plan education, light or full eKYC, credit decision, deposit logic, activation, post-activation engagement) and assemble different paths per segment based on a real-time risk score. Fixed bundlers see four steps. Cold customers see seven. Same components, different path.
This aligns directly with the instinct on differentiated fraud flows. ID scanning isn't on or off. It's one tier in a graduated identity system. Light eKYC for referred customers, full eKYC for cold promo signups, skip entirely for verified Fixed bundlers.
At HVAC.com I owned a 7-step funnel. The whole thing was instrumented for A/B testing: I could reorder steps, update the copy within them, and remove steps entirely, then measure the conversion impact of each change.
Four customer segments use the same components, but follow different journeys. Click a customer segment to see how the funnel adapts.
Add a Mobile referral program alongside promo codes. Both referrer and new customer earn $10 at activation and $20 more at 90 days, with the larger credit gated on staying through the promo cliff. This extends Optimum's existing Fixed-side referral program ($50, 60-day vesting), with smaller credits sized to Mobile and two vesting milestones instead of one.
Today the mobile homepage chatbot and the Allie support bot are two different experiences, and a user mid-onboarding can land on either. Unify both into a single chat that gets users where they need to go, regardless of where they entered from.
Each approach hits a different churn driver. The funnel hits onboarding friction and bill-shock prevention. The referral program hits customer quality at the top. Unified support hits support friction and ticket volume per new customer.
Sequence the work to deliver value while the bigger build is in flight. Unified chat ships first as quick wins and instrumentation. The modular funnel builds in parallel. The referral program layers on once the funnel can receive segment-aware traffic. The Execution tab walks through the wave-by-wave plan.
Track five metrics to see if the changes are working. Cut each by segment so we can tell when one kind of customer is getting better while another may be getting worse.
Cut by funnel variant. Did the customer finish the path they were assigned?
Per new customer in the first 30 days. Tracks support load and serves as an onboarding-experience proxy.
The protected constraint from the brief. Watch for any meaningful negative delta.
Per onboarded customer, online versus in-store. Tracks the economics of each channel as volume shifts.
Used to diagnose moves in primary metrics:
Modular architecture pays off here: we can run separate experiments on coverage check placement, eKYC step ordering, deposit messaging, and welcome emails without touching adjacent components. Existing flow as control, new adaptive flow as treatment, evaluated separately by segment.
The first and easiest test: make the existing coverage checker (optimum.com/mobile/network) a required Step 1 of onboarding (auto-confirmed for Fixed bundlers since we already have their address). The example here shows a multi-zip coverage checker flow: home, work, and other, so that you can easily check your most-visited locations in one shot. Mint Mobile makes coverage check a hard requirement at signup. Coverage gaps are a leading silent-churn driver. Customers who exit at this step aren't lost gross adds, they're 30-day churns we surfaced early and didn't pay support, SIM, and activation costs to discover later.
The metric to watch: 90-day churn delta between the new flow (with required coverage check) and the existing flow (no coverage step in onboarding). Coverage-related exits get their own bucket, not counted as funnel abandonment.
The target: 6-15% reduction in 90-day churn. That's the conservative end of a 6-20% range from industry case studies. We'll adjust once we see internal numbers.
Each card below shows what one component actually looks like, plus the experiment we'd run on it.
Quick wins in weeks 1-6. Modular funnel through month 4. Referral program by month 6. Each wave produces signal that informs the next.
Five teams own pieces of this. Each one is essential to at least one wave.
Modular front-end architecture. Decisioning service. Component-level analytics infrastructure.
eKYC vendor selection. Deposit policy by tier. Risk-tier definitions and audit logging for the model.
Honest messaging today (TCPA). Required disclosures when declining credit (FCRA). Readiness for the upcoming FCC Revoke-All rule.
Chat routing logic and copy. Coverage-check standalone landing page. Plan-comparison clarity on throttle behavior.
Device compatibility messaging during the 5G SA migration. Coverage data accuracy at zip-code level.
First-week priorities:
AI is a research accelerator and a drafting partner. I'd use it the same way on Optimum's product work: speed up discovery, stress-test framing, surface counterarguments, and produce drafts I review, edit, and own.