customer-analytics skillA
customer-analytics is agent-read markdown (skill) from varunk130/ai-gtm-skill-library: Customer analytics framework - cohort retention, lifecycle funnels, engagement scoring, segmentation, and behavioral diagnostics for product and CS teams. Use when: customer analytics, cohort analysis, retention curve, engagement score, customer segmentation, behavioral analysis, lifecycle funnel, RFM, activation diagnostics, usage analysis..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Customer Analytics (LENS Framework) Design a customer analytics architecture that answers *which customers, doing what, are driving (or breaking) the business* - instead of dashboards full of vanity counts. LENS produces a defensible segmentation, a retention model, an engagement score, and a behavioral diagnostic loop that PMs and CS can act on weekly. ## Core Principle **Customer analytics fails when it stops at "users went up." LENS forces decomposition into *who*, *what*, *when*, and *why* - the four axes a dashboard usually collapses into one number.** ## The LENS Framework | Letter | Stage | The Question | |--------|-------|--------------| | **L** | Lifecycle Mapping | What are the named lifecycle stages and what does each one's "good" look like? | | **E** | Engagement Scoring | What weighted score combines depth, breadth, and recency of value events? | | **N** | Net Retention Decomposition | Where exactly is NRR coming from - new logo, expansion, contraction, churn? | | **S** | Segment Behavior | Which segments behave differently, and which behavioral cohorts predict outcomes? | ## Lifecycle Stages | Stage | "Good" Signal | Diagnostic | …
Read the whole file at its exact version.
How to install
mdr add varunk130/ai-gtm-skill-library/customer-analytics@git:20260625.9529148mdr add varunk130/ai-gtm-skill-library/customer-analytics@sha256:783f6a28d15243fbPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_pok4dzvjpljyersc)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260625.9529148 latest | 2026-06-25 | 9529148 | 5,673 B | A | view · diff |
| git:20260522.2e90392 | 2026-05-22 | 2e90392 | 5,675 B | A | view · diff |
| git:20260516.4225f52 | 2026-05-16 | 4225f52 | 5,713 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5673 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
varunk130/ai-gtm-skill-library · 6 stars · license MIT · pushed 2026-09-19 · branch master
API
GET https://markdownregistry.com/api/v1/artifacts/art_pok4dzvjpljyersc GET https://markdownregistry.com/api/v1/resolve?ref=varunk130/ai-gtm-skill-library/customer-analytics GET https://markdownregistry.com/api/v1/blob/783f6a28d15243fbd920e968d9791c3b00efc0ed65e7b91fa8ae062f43e66555
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