SaaS lifecycle programs

Purpose

Lifecycle messaging is only as good as the events behind it. Most lifecycle problems are not missing campaigns. The events are not tracked, they are tracked inconsistently, or they never reach the messaging platform, so the program quietly sends the wrong message to the wrong people. This skill checks the data first, then designs or audits the programs against the customer journey.

When to use

• Trial conversion or activation is low.
• Churn is rising, and the team wants messaging to help.
• Onboarding or failed-payment messages need review or a rebuild.
• A win-back flow is needed.

Route elsewhere when:

• The question is the customer success motion. Use cs-operations.
• The question is the product's own onboarding. Use onboarding-activation.
• The question is the price or plan design. Use pricing-monetization-ops.

Inputs

• The list of events and user attributes that exist, and how many records each has.
• The cohort retention curve, by signup month.
• Current lifecycle messages, with their triggers.
• The plans, trial length, and billing system used for failed payments.

Procedure

1. Audit the data layer first. For each message the program would need, confirm the trigger event exists, is populated, is consistent, and reaches the messaging platform. Name every gap. If the pipes are broken, the first deliverable is fixing them, stated plainly, even when the request was for a campaign.
2. Read the retention curve before prescribing anything. A curve that flattens means retained users are a stable base to build on. A curve that keeps falling means the first priority is retention, not acquisition messaging.
3. Place the user journey on the eight stages:
   1. Acquisition: signup, setting expectations, first login.
   2. Activation: reaching the first moment of value.
   3. Onboarding: completing the setup steps that predict retention.
   4. Adoption: building the habit and widening feature use.
   5. Retention: reinforcing value and preventing decay.
   6. Expansion: hitting limits, upgrading, adding seats.
   7. Advocacy: referrals and reviews from happy users.
   8. Resurrection: reactivating dormant users, saving cancellations, and recovering failed payments.
4. Start with the minimum viable set: activation, onboarding, trial conversion if there is a trial, failed-payment recovery, and win-back. Add expansion and advocacy once these work.
5. For an audit, rank findings by leverage: the revenue or retention at stake, against the effort to fix. Show the evidence for each.
6. For a build, produce a roadmap in stages. For each program, give the trigger, the number and timing of touches, the data it depends on, and the check that shows it is working.
7. Define the success measure for each program before it runs, such as activation rate, trial conversion, or recovered payments.

Output

• The data-layer findings, first, with each gap and its fix.
• The retention reading and what it implies.
• The journey map, with the stage of each program marked.
• An audit ranked by leverage, or a staged roadmap with triggers, touches, data prerequisites, and success measures.

Quality bar

The data layer is checked before any program is designed. Each program names its trigger and its data source. The retention curve is read before prescriptions. Success is measured before launch. Watch for campaigns built on untracked events, win-back flows with no data behind them, and lifecycle programs designed for an acquisition problem that is really a retention problem.