customer-lifetime-value-optimizer

name	customer-lifetime-value-optimizer
description	Segment ecommerce customers by repeat behavior, margin quality, membership depth, and churn or return risk, then turn rough order-history notes into a prioritized LTV growth plan. Use when CRM, membership, lifecycle, or retention teams need segment-specific growth actions without live CDP, ESP, or data-warehouse integrations.

Customer Lifetime Value Optimizer

Overview

Use this skill to convert customer-segment notes, order-history summaries, gross-margin signals, and retention context into a practical LTV action plan. It is built for operators who need fast prioritization across new-customer nurture, repeat purchase growth, margin protection, and winback strategy.

This MVP is heuristic. It does not connect to live CRM, CDP, ESP, loyalty, or analytics systems. It relies on the user's segment notes, exported summaries, and lifecycle context.

Trigger

Use this skill when the user wants to:

• identify which customer segments deserve the most retention investment
• design different lifecycle moves for high-value, price-sensitive, dormant, or return-risk customers
• rank LTV levers such as repeat rate, AOV, margin mix, or churn reduction
• turn rough order-history notes into a CRM or membership action brief
• separate revenue growth ideas from margin-quality and retention-quality risks

Example prompts

• "Which segments should we prioritize to improve LTV this quarter?"
• "Create a retention plan for VIP, new, and dormant customers"
• "How can we grow LTV without overusing discounts?"
• "Turn these order and membership notes into an LTV roadmap"

Workflow

1. Capture the customer segments, order behavior, and whether the main tension is repeat rate, AOV, churn, or margin quality.
2. Normalize the likely LTV signals: order history, repurchase cycle, segment mix, return behavior, and offer sensitivity.
3. Separate customer groups into different action lanes instead of giving one generic lifecycle answer.
4. Rank the highest-value LTV levers and attach practical plays, owners, and success metrics.
5. Return a markdown plan with segment diagnosis, lever ranking, and action packages.

Inputs

The user can provide any mix of:

• customer segments or membership tiers
• order history and repeat-cycle notes
• AOV, gross margin, bundle rate, or attach-rate context
• churn, dormancy, or lapsed-customer notes
• refund or return-risk observations
• lifecycle messaging constraints and incentive constraints

Outputs

Return a markdown plan with:

• a segment diagnosis table
• ranked LTV levers
• action packages by segment
• short, medium, and longer-horizon priorities
• measurement notes, assumptions, and limits

Safety

• Do not claim access to live CRM, ESP, loyalty, or analytics systems.
• Do not auto-send discounts, coupons, or lifecycle messages.
• Keep revenue lift and margin impact separate in the recommendations.
• Downgrade certainty when user-level order history is incomplete.
• Treat financial LTV models and operator-facing lifecycle plans as related but not identical.

Best-fit Scenarios

• CRM and membership planning for ecommerce teams
• repeat-purchase and lifecycle improvement reviews
• retention strategy design when data is partial but usable
• operator-led businesses that need an action plan before building a deeper model

Not Ideal For

• formal finance-grade LTV forecasting
• automatic customer scoring or trigger orchestration
• businesses with no segment or order-history visibility at all
• scenarios that require privacy-reviewed activation logic

Acceptance Criteria

• Return markdown text.
• Include segment diagnosis, lever ranking, action packages, and limits.
• Show at least one short-term, one medium-term, and one longer-term move.
• Keep the plan practical for CRM, lifecycle, and retention operators.