Mk 386

---
name: mk-386
description: "High-Value Member Selection. Use when work requires candidates assessed jointly on frequency, amount, and recency; process the specified inputs using this method and verify the deliverable"
---

# MK-386 | High-Value Member Selection

For ordinary chat, upload `packs/mk-386.md`, which includes the shared rules, this method, and required references

## Purpose

This skill delivers: **Candidates assessed jointly on frequency, amount, and recency**

Do not rank RFM results from different observation periods as if they shared one basis; separately verify the purpose and authorization for any list export or use

## Required inputs


Available raw records: approved RFM mapping, orders and refunds, contribution, intended benefits and costs, contact eligibility, and product cycles

## Method Steps

1. Use the brand's RFM mapping, valid-order/refund rules, and intended benefit to find loyal, lapsed-loyal, and high-potential candidates. Without a mapping, report raw RFM rather than inventing a weighted total
2. Separate high revenue, actual high contribution, current need, and contact eligibility. A large basket with high returns or fulfillment costs does not automatically justify the most expensive benefit
3. Retention prioritizes members qualifying under existing rules with a relevant need and contact eligibility. Winback targets previously loyal members overdue under the applicable cycle; unresolved complaints call for service first
4. Compare available contribution and benefit costs by person/group, and check the total budget. Without costs, deliver candidates and allocation formulas and request only the benefit cost affecting eligibility
5. Re-evaluate inclusion after refunds, contact eligibility, or cycle corrections. Keep official membership tiers separate from campaign eligibility rather than rewriting policy for one activity

## Calculation and Interpretation

Recalculate R/F/M under existing definitions. Campaign cost = group headcount × per-person benefit and fulfillment cost + fixed costs. State the horizon of historical contribution; unknown future incremental purchases are not guaranteed spending capacity

Check example (hypothetical): A has annual revenue of 20,000 but only 200 contribution after refunds and costs; B has 10,000 revenue and 3,000 contribution. A provided benefit rule requiring at least 1,000 contribution selects B. Correcting A's refunds raises contribution to 2,000 and restores eligibility

Decision rules authored by ThinkWithBlack, 2026-10-14; original course sources remain below

## Required output fields

| Order | Field | How to fill it in |
|---:|---|---|
| 1 | Candidate | Original evidence, intermediate method results, or an explicit unknown; do not fabricate |
| 2 | Eligibility | Original evidence, intermediate method results, or an explicit unknown; do not fabricate |
| 3 | Relevant evidence | Original evidence, intermediate method results, or an explicit unknown; do not fabricate |
| 4 | Task fit | Original evidence, intermediate method results, or an explicit unknown; do not fabricate |
| 5 | Limitations / resources | Original evidence, intermediate method results, or an explicit unknown; do not fabricate |
| 6 | Priority | Original evidence, intermediate method results, or an explicit unknown; do not fabricate |
| 7 | Tradeoff rationale | Original evidence, intermediate method results, or an explicit unknown; do not fabricate |
| 8 | Missing items | Original evidence, intermediate method results, or an explicit unknown; do not fabricate |

## Validation cases

**MK-386-C05｜Only two valid candidates exist**

Expected: deliver the two items and their limitations; do not invent other candidates to meet a quota

## Method sources

Original file: 營業額提升主要關鍵（二）社群/會員經營技巧

Source locator: RFM

Source basis: extracted from course materials

Original URL: https://docs.google.com/presentation/d/1ZYpstuVAXGk9KdZt1QZm2OQ7ozpYYtfrBf0Xsy7kRx8/edit

English translation of source excerpt retained in the master sheet:

> Use RFM rules for segmentation to turn new customers (one purchase) into returning customers (more than one purchase)