Clara

Prompt: Design a customer success framework for a B2B SaaS with 200 accounts. Include: segmentation model, health scoring criteria, playbooks for at-risk accounts, and QBR template. Focus on the SA mid-market context.

1️⃣ Executive Summary

A robust Customer Success Framework (CSF) turns a “one‑size‑fits‑all” support model into a proactive revenue‑protecting engine.

For a mid‑market B2B SaaS with ≈200 accounts in South Africa, the framework below delivers:

| Goal | How it’s achieved |

|------|-------------------|

| Targeted engagement | 3‑tier segmentation (High‑Potential, Standard, At‑Risk) + per‑account health score |

| Early churn detection | Health‑score dashboard, automated alerts on low NPS, support spike, usage drop |

| Revenue growth | Upsell & cross‑sell playbooks for high‑potential accounts; quarterly business reviews (QBRs) that surface expansion opportunities |

| Operational efficiency | Role‑specific templates (emails, scripts, tickets), single source of truth in a cloud platform (e.g., Cloudflare Workers + D1 or 2nth.ai backend)**

> Tip for SA: keep all monetary figures in ZAR, and include a local “payment‑late” alert at 30 days past due to match typical credit‑terms.

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2️⃣ Segmentation Model

2.1 Tiering by Account Value & Growth Potential

| Tier | ARR (ZAR) | Expected Annual Growth | Typical Use‑case | Primary CS Owner |

|------|-----------|------------------------|------------------|-------------------|

| High‑Potential (HP) | ≥ R 5M | 30 %+ | New pilots, flagship clients | Enterprise Success Manager |

| Standard (ST) | R 500K – R 4.9M | 10‑20 % | Stable mid‑market customers | Mid‑Market Success Lead |

| At‑Risk / Growth (AR/G) | ≤ R 499K or high churn risk | < 5 % | Early adopters, low usage | Dedicated Account Specialist |

Why ARR + Growth? In SA the bulk of revenue comes from a handful of mid‑market firms; growth potential is more predictive of upsell interest than raw size alone.

2.2 Granular Segmentation Variables

Use these dimensions for deeper targeting inside each tier:

| Variable | Why it matters in SA | Data source |

|----------|---------------------|-------------|

| Industry vertical (e.g., Finance, Retail, Manufacturing) | Different regulatory & adoption curves | CRM / Product usage API |

| Payment cycle (monthly vs quarterly) | Cash‑flow impact on renewals | Billing system |

| Support SLA tier (Standard vs Premium) | Service expectations | Ticketing system |

| Geographic region (Western Cape, Gauteng, etc.) | Local holidays & timezone impacts | CRM |

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3️⃣ Health Scoring Criteria

A weighted formula that maps raw signals into a 0‑100 score.

Score is calculated monthly and plotted on a heat‑map for the CS dashboard.

| Dimension | Metric | Weight | Thresholds |

|-----------|--------|--------|------------|

| Product Usage (30 %) | % of enabled features used / last 30 days | 30% | ≥ 80 % = green, 50‑79 % = yellow, < 50 % = red |

| Feature Adoption (10 %) | New feature adoption rate | 10% | ≥ 70 % = green, < 70 % = red |

| Support Health (20 %) | Avg. ticket SLA % >90 %, Ticket volume trend (+/-10 %) | 20% | >90 % SLA → green, >10 % spike → red |

| NPS / CSAT (15 %) | NPS score from monthly survey | 15% | ≥ 50 = green, 0‑49 = yellow, < 0 = red |

| Payment Health (15 %) | Days past due (30d+) and outstanding balance >10 % of ARR | 15% | ≤ 30 days → green, >30 days or high debt → red |

| Executive Engagement (10 %) | Meeting cadence met (% of scheduled QBRs) | 10% | 100 % → green, <80 % → yellow |

Health Score Formula (simplified):

``

Score = Σ (DimensionWeight × NormalisedMetric)

``

Normalisation: Convert each raw metric to a 0‑1 scale where 1 is best. For example, Usage %/30 days → (usage % / 100). If usage < 50 %, the value is scaled down accordingly.

Example

| Dimension | Raw | Normalised | Weight | Contribution |

|-----------|-----|------------|--------|--------------|

| Usage | 45 % | 0.45 | 0.30 | 13.5 |

| Feature Adoption | 60 % | 0.60 | 0.10 | 6.0 |

| Support Health | 85 % SLA, +12 % spike | 0.70 (because of spike) | 0.20 | 14.0 |

| NPS | –10 | 0.40 (negative NPS scaled) | 0.15 | 6.0 |

| Payment | 45 days past due | 0.50 | 0.15 | 7.5 |

| Exec Eng | 70 % meetings met | 0.70 | 0.10 | 7.0 |

| Total | | | | 54.0 |

Score of 54 → Yellow zone (warning).

> SA nuance: Adjust “Payment Health” weight if you have a large percentage of clients that typically pay at 60 days due to local credit terms.

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4️⃣ At‑Risk Playbook

4.1 Identification & Triggering

| Signal | Frequency | Action |

|--------|-----------|--------|

| Score < 55 % (Yellow) for > 30 days | Weekly | Auto‑generate “AT‑RISK” ticket + notify CS Lead |

| Support tickets > 10 % spike in last 15 days | Daily | Notify CS Rep + add to queue |

| Payment > 30 days past due & Score < 70 % | As soon as detected | Escalate to Finance; start renewal outreach |

4.2 Step‑by‑Step Response

| Step | Owner | Timing | Deliverable |

|------|-------|--------|-------------|

| 1. Outreach | CS Rep | Within 48 h of alert | Personalized email/phone + “We’re concerned your usage dropped” |

| 2. Issue Mapping | CS Rep | 24‑hr after outreach | Structured interview form (usage pain points, feature gaps) |

| 3. Coaching Session | Product Engineer / Trainer | 1–2 hrs within 5 days | Live demo + walk‑through of missing features |

| 4. Upsell/Engagement Offer | CS Lead | Within 7 days | Targeted bundle or advanced module based on pain points |

| 5. Follow‑Up & Closure | CS Rep | 14 days after session | Summary email, action items checklist, new health score |

4.3 Email / Call Script Templates

> Subject: “Quick check‑in – help us improve your experience at [Company]”

> Hi [First], I noticed a dip in usage on our dashboard and wanted to see if anything’s blocking your team from getting value. Could we hop on a 15‑minute call next week? Here’s my calendar link…

> On‑call Note: Use the “Issue Mapping” form. Record key themes (e.g., “Feature X is too complex”) → triggers training or feature enhancement tickets.

4.4 KPIs to Measure Playbook Success

| KPI | Target |

|-----|--------|

| % of AT‑RISK alerts resolved within 10 days | ≥ 80 % |

| NPS increase after playbook completion | +5 points |

| Renewal rate in AT‑RISK tier | ≥ 70 % |

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5️⃣ Quarterly Business Review (QBR) Template

Designed to be a 30‑minute virtual deck with the client’s key stakeholders.

| Slide | Purpose | Key Questions | Data/Visuals |

|-------|---------|---------------|--------------|

| 1. Executive Summary | One‑liner of value & next steps | “What did we accomplish this quarter?” | High‑level KPI bar chart |

| 2. Business Objectives Review | Align product usage with business goals | “How are we helping you hit X target?” | Goal vs Actual line graph |

| 3. Product Usage Snapshot | Adoption heat‑map by feature | “Which modules are under‑utilised?” | Usage matrix, % of enabled features |

| 4. Success Stories & ROI | Concrete wins | “What tangible outcomes have you seen?” | Case studies + metrics (e.g., cost savings) |

| 5. Pain Points & Road‑Map Alignment | Capture feedback | “Where are the gaps?" | Issue list + product roadmap icons |

| 6. Expansion Opportunities | Upsell / cross‑sell proposals | “What additional value can we bring?” | Bundle comparison table |

| 7. Action Items & Owner Assignments | Clear next steps | “Who does what by when?" | Gantt‑style checklist |

| 8. Q&A | Open discussion | Any concerns? | N/A |

Pre‑QBR Prep Checklist (30 days before):

• Pull latest health score & usage data.
• Review any recent support tickets or incidents.
• Confirm meeting time with all stakeholders (account, finance, tech lead).
• Draft 2–3 expansion proposals aligned to their objectives.
• Send “What we’ll cover” agenda email + pre‑survey.

Post‑QBR Follow‑Up:

• Distribute minutes & action items within 24 hrs.
• Update CRM playbook with new pain points.
• Flag any high‑value upsell opportunity to Sales with a timestamped note.

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6️⃣ Implementation Roadmap (0–6 months)

| Month | Milestone | Deliverable |

|-------|-----------|-------------|

| 1 | Data audit & integration | Identify all data sources (CRM, Billing, Usage API) and map fields for health score |

| 2 | Segmentation & scoring engine | Deploy a Cloudflare Worker + D1 database to calculate scores daily; set up alert thresholds |

| 3 | Playbook templates & training | Create email/Call scripts, train CS team on at‑risk playbook |

| 4 | QBR deck template & cadence | Roll out QBR process to 50% of accounts (HP tier) |

| 5 | Automation pilot | Auto‑email outreach for AT‑RISK alerts; test ticket routing |

| 6 | Full roll‑out & KPI monitoring | Launch framework to all 200 accounts, review KPIs, refine weighting |

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7️⃣ South Africa‑Specific Considerations

• Currency & Pricing – Always convert ARR/usage metrics into ZAR for local dashboards; keep a USD/ZAR conversion table in the score engine (update monthly).
• Regulatory Compliance – For finance or health verticals, add a “Compliance Health” sub‑metric: % of data protected per POPIA & PCI requirements.
• Payment Terms – Most SA customers pay 30–60 days. Adjust “Payment Health” weight and threshold accordingly (e.g., 45 days past due).
• Local Holidays – Disable automated outreach during public holidays (e.g., Heroes’ Day, Freedom Day) to avoid missed follow‑ups.
• Language & Tone – Use local idioms when appropriate; keep communications clear for multi‑lingual teams if needed.

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📌 Quick Reference Cheat Sheet

| Item | Tool/Method |

|------|-------------|

| Health score calculation | Cloudflare Worker + D1 schema (health_score table) |

| Alerting | Workers publish to Queue → email/SMS via Twilio or Slack webhook |

| Ticket integration | Zoho Desk / Shopify Support API |

| Data visualisation | 2nth.ai dashboard (Grafana‑style) or PowerBI for SA data |

| Training docs | Confluence space + SharePoint PDF decks |

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With this framework you’ll turn each of the 200 accounts into a scalable success engine: predict churn before it happens, nurture high‑potential customers with tailored engagement, and secure renewals & expansions through data‑driven QBRs—all while respecting South Africa’s unique market nuances. Good luck!