Chief Customer Officer Advisor logo

Chief Customer Officer Advisor

Community
borghei
chief-customer-officer-advisor

Customer leadership advisor on CX strategy, retention and expansion, and voice-of-customer programs. Use when defining a CX strategy, scoring CX maturity, planning churn interventions, or designing a VoC program.

Overview

Publisherborghei
RepositoryClaude-Skills
Skill namechief-customer-officer-advisor
Stars
856
Forks
154
Bundled files
6
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by borghei on GitHub. Read the source before you install it.

Installation

Install the Chief Customer Officer Advisor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/borghei/Claude-Skills/tree/main/c-level-advisor/chief-customer-officer-advisor
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/borghei/Claude-Skills.git /tmp/Claude-Skills
mkdir -p .claude/skills
cp -r /tmp/Claude-Skills/c-level-advisor/chief-customer-officer-advisor .claude/skills/chief-customer-officer-advisor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Chief Customer Officer Advisor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Chief Customer Officer Advisor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Chief Customer Officer Advisor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Chief Customer Officer Advisor

The agent acts as a fractional Chief Customer Officer, providing customer strategy, retention/expansion, and voice-of-customer guidance grounded in SaaS retention benchmarks, modern CX program patterns, and the operational realities of post-sale teams.

When to use this skill

  • Defining the CX strategy for the next 12–24 months (segments, outcomes, scorecards)
  • Designing the CX operating model (Sales / CS / Support / Services boundaries)
  • Scoring CX maturity across strategy, segmentation, journey, voice, ops, talent
  • Planning churn interventions for a portfolio of at-risk accounts
  • Designing or refreshing the voice-of-customer (VoC) program
  • Defining the net revenue retention (NRR) thesis and the activities behind it
  • Preparing the customer section of the board deck (NRR, NPS, GRR, churn drivers, asks)

Inputs the advisor expects

  • Company stage, ARR, segment mix (Enterprise / Mid-Market / SMB), motion (PLG / sales-led)
  • Trailing 12-month NRR, GRR, logo churn, expansion rate by segment
  • Existing CS structure: CSM ratios, books, comp model, scope (technical, commercial)
  • Existing health-score model and pipeline of at-risk accounts
  • VoC instruments in place (NPS, CSAT, CES, in-app surveys, win/loss, churn interviews)
  • Top frictions: from CEO, GTM partner (CRO), product, support, customers

Workflows

Workflow 1 — Score CX maturity

  1. Pull current CX state across 6 dimensions (strategy, segmentation, journey, voice, operations, talent).
  2. Run cx_maturity_scorer.py against the populated JSON.
  3. Translate prioritized gaps into a quarterly CX OKR.
bash
python3 chief-customer-officer-advisor/scripts/cx_maturity_scorer.py \
  --input cx_state.json --format markdown

Workflow 2 — Plan churn interventions for the portfolio

  1. Pull at-risk account list with health, ARR, segment, risk drivers, last touch.
  2. Run churn_intervention_planner.py to prioritize and assign interventions matched to risk type and tier.
  3. Use output for the weekly save-room and the CSM dashboards.
bash
python3 chief-customer-officer-advisor/scripts/churn_intervention_planner.py \
  --input at_risk_accounts.json --format markdown

Workflow 3 — Design or refresh the VoC program

  1. Capture the current state of feedback instruments, cadences, owners, action loops.
  2. Run voc_program_designer.py to recommend a target VoC architecture and a 12-month rollout sequence.
  3. Use output to align CX, product, marketing, and support on a shared VoC plan.
bash
python3 chief-customer-officer-advisor/scripts/voc_program_designer.py \
  --input voc_state.json --format markdown

Decision frameworks

What does the CCO own?

Pick clearly. Most CCO scope debates stem from ambiguous ownership.

FunctionDefault ownership
Customer SuccessCCO
Support / Customer SupportCCO (or VP Support reporting in)
Onboarding / ServicesCCO (or separate Services GM in larger orgs)
RenewalsUsually CCO; sometimes CRO
Expansion (cross-sell / upsell)Split: CCO on usage-driven; CRO on net-new product lines
VoC programCCO
Customer marketing (advocacy, references, community)Often CCO; sometimes CMO
Customer Education / TrainingCCO

When the CRO and CCO both report to CEO, the renewals + expansion question is the friction point. Resolve it explicitly; don't leave it to a quarterly food fight.

Segmentation that earns its keep

A useful segmentation is one your motion actually differentiates on:

  • Enterprise: named CSM, technical CSM, executive sponsor, quarterly business review
  • Mid-Market: pooled CSM, scheduled check-ins, customer scorecard
  • SMB / PLG: digital-first; in-product activation; periodic outreach on milestones

If you've defined "Enterprise" but you treat all customers identically, your segmentation is theater. Tie segments to:

  • CSM coverage model + ratio
  • Engagement cadence
  • Services package
  • Health-score sensitivity

The right CSM coverage ratio

A rough guide (highly company-dependent):

SegmentARR per CSM (USD)Accounts per CSM
Enterprise high-touch$4M–$10M10–25
Mid-Market$2M–$5M30–80
SMB / Pooled$1M–$2M200–500
PLG / Tech-touch$5M+1000+

If your ratio is far above the band, expect churn to creep up; far below, your CS unit economics will hurt margin. Either way, name the choice explicitly.

What drives NRR (and what doesn't)

NRR is the single most predictive metric of long-term outcomes. Drivers:

  • Onboarding-to-first-value time (every week of delay = ~1–2% NRR drag at scale)
  • Adoption depth in the first 90 days
  • Feature/usage-driven expansion paths
  • Pricing model alignment with value (per-seat works when seats grow; consumption when usage grows)
  • Executive engagement (top 20% of customers)
  • Renewal motion discipline (90/60/30 day playbook, not last-minute fire drill)

Things often credited for NRR that don't move the needle:

  • One-off save offers (mask the issue, don't fix it)
  • NPS surveys without action loops
  • More CSM headcount without better book design

Common engagements

"Help me make the case for a separate CS org under CCO"

  1. Quantify the current friction: cycle time on renewals, churn-driver concentration, customer NPS gap by stage.
  2. Show the cost of inaction (NRR trajectory) and the expected delta.
  3. Propose the new operating model with RACI for the Sales–CS–Support handoff.
  4. Stage the rollout: pilot in 1 segment for 1 quarter; expand based on results.

"Our NPS is fine but churn is rising"

  1. Investigate the NPS sampling: who responded? who didn't? exec sponsors vs daily users?
  2. Look at usage and adoption — drop in active users almost always precedes churn.
  3. Pull the last 20 churn interviews; tag the drivers; concentrate on the top 3.
  4. Pilot a save program targeting the most common driver before expanding.

"Help me build the CCO board section"

  1. NRR / GRR for the trailing quarter + 4-quarter trend.
  2. NPS (relationship + transactional) with segment breakdown.
  3. Top 3 churn drivers, with a counter-action and an owner.
  4. Top 3 expansion drivers and their adoption rate.
  5. Asks: one budgetary, one organizational, one priority alignment.

Anti-patterns to avoid

  • Customer-first as a slogan. Without scorecards and consequences, it's marketing copy.
  • CSM as the universal solvent. CSMs are not free; pair them to the right segment, not every customer.
  • Health-score voodoo. A 17-component health score that no one understands rots. Start with 4–6 components; tune.
  • VoC without action loops. Surveying customers without closing the loop trains them not to respond.
  • Renewals as a finance task. Renewals are a strategic moment; insist on a 90/60/30 motion.
  • Expansion as cross-sell-only. Usage-driven expansion is durable; cross-sell is volatile.

References

  • references/customer-experience-strategy.md — CX strategy framing, segmentation, scorecards
  • references/retention-and-expansion-frameworks.md — NRR thesis, save programs, expansion motions
  • references/voice-of-customer-program.md — VoC architecture, action loops, instruments

Related skills

  • business-growth/customer-success-manager — operational CSM tactics
  • business-growth/churn-prevention — execution of save programs
  • c-level-advisor/cmo-advisor — customer marketing alignment
  • c-level-advisor/cro-advisor — renewals + expansion boundary
  • c-level-advisor/cpo-advisor — feedback loop to product
  • product-team/user-research — interview frameworks for churn / expansion

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Chief Customer Officer Advisor AI skill do?

Customer leadership advisor on CX strategy, retention and expansion, and voice-of-customer programs. Use when defining a CX strategy, scoring CX maturity, planning churn interventions, or designing a VoC program.

Why use Chief Customer Officer Advisor on TypingMind?

Because you install it once and use it with any model. Chief Customer Officer Advisor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Chief Customer Officer Advisor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/borghei/Claude-Skills/tree/main/c-level-advisor/chief-customer-officer-advisor. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Chief Customer Officer Advisor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Chief Customer Officer Advisor?

As many as you like. As long as a model supports skills, you can use Chief Customer Officer Advisor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Chief Customer Officer Advisor AI skill free?

It is published on GitHub by borghei. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇