At-Risk Accounts Surfaced Before They Churn
"Which accounts are sliding?" "What's renewing next quarter and how does each stage look?" "Who's a champion-led expansion play?" "Which handoffs are still waiting on AE context?" — Mango CS Agent answers all of it in chat, against the canonical CRM and renewal pipeline data. Strictly read-only — actual save/escalate/expand actions stay in the CSM workflow surface.
HOW IT WORKS
How it catches an at-risk account
From the first usage dip to renewal prep — using the same health-scoring matrix, renewal pipeline, and CSM workflows you already configured. It works the portfolio before risks become churn.
1. Detect
A usage drop, a support spike, a contract approaching renewal. The loop reads the signal before the CSM has to look.
2. Decide
Component-scores health (usage + support + sentiment + contract), ranks risk severity, surfaces expansion candidates alongside churn flags.
3. Act
Drafts CSM briefings, schedules renewal prep, routes expansion plays to AEs — outright when trust is high, with CS lead sign-off when the level is lower.
4. Log
Every score change, briefing, and handoff lands in one audit trail tied to the account. NRR-defensible evidence + QBR-ready by default.
HOW IT OPERATES
Runs on a managed cadence
Mango CS runs on a managed schedule, not a per-tenant dial. Health scoring + risk + expansion signals run continuously; the actions that reach a customer (briefings, expansion plays) stay confirmation-gated before anything goes out.
Scores continuously
Component health (usage + support + sentiment + contract), risk, and expansion signals scored on a managed schedule.
Surfaces on the console
Every at-risk account + expansion candidate surfaces on the CS console for a CSM to act on.
Confirmation-gated outreach
Briefings + expansion plays that reach a customer are confirmation-gated — the CS lead signs off first.
Read-side runs unattended
Scoring, renewal-pipeline rollups, and at-risk detection run unattended; only customer-facing actions need a human.
Every account the loop touched gets an "AI handled" badge
Accounts the loop scored carry an "AI scored" badge with the component breakdown (usage, support, sentiment, contract). Briefings the loop drafted show an "AI drafted briefing" tag. Expansion plays the loop routed show an "AI routed to AE" tag.
- "AI scored · 54 overall" on accounts the autopilot evaluated.
- "AI drafted briefing" on accounts the loop prepped for the CSM.
- "AI routed to AE" on expansion plays the loop handed off.
- Component summary on every score — usage, support, sentiment, contract.
One console — CS's home for portfolio autopilot
The Mango CS console is the buyer-facing landing for CS leaders and CSMs. At-risk account count sits front and center with a per-tier sparkline (green / yellow / red distribution). The "AI handled" feed shows what fired across the portfolio in the last day. The "Waiting on you" queue surfaces approval-gated briefings + plays. Renewal radar surfaces upcoming contract dates.
- Hero metric + trend — at-risk accounts + tier-distribution sparkline.
- "AI handled this" feed — scores, briefings, and handoffs in the last day.
- "Waiting on you" queue — approval-gated briefings + plays approved or rejected inline.
- Renewal radar — accounts the loop flagged as approaching renewal, surfaced before the cycle.
- Managed cadence — scoring runs on schedule; customer-facing actions stay confirmation-gated.
Why At-Risk Accounts Get Spotted Too Late
Mango CS Agent surfaces all four in one chat — against the canonical health scoring, renewal pipeline, and expansion-signal services. Read-only by design; the agent identifies the conversation, the CSM owns it.
Health Scores Show Up On A Dashboard Nobody Opens Daily
The score went from 78 to 42 over four weeks. The CSM didn't notice until QBR prep. By that point the champion has already left, the usage drop is structural, and the renewal conversation isn't a renewal conversation — it's a save conversation.
"What's In My Renewal Pipeline?" Means A Saved Filter In A Dashboard
Pipeline by stage, by window, by ARR — the CSM lead wants it weekly, the CRO wants it monthly, and the CSM has to maintain three different saved views just to keep the conversation moving. The answer should be a chat message; today it's a calendar reminder.
AE→CSM Handoffs Land Without The Context That Matters
The deal closed. The handoff happened. But the discovery notes, the technical fit conversation, and the customer's executive sponsor — those didn't come across. The CSM walks into kickoff blind, and the customer notices.
Expansion Signals Live In Three Tools Nobody Cross-References
Healthy account approaching renewal? Champion contact going silent? Pricing-page repeat visits from someone in their org? Each lives in its own system. The CSM has to assemble the picture by hand — so the easy expansions get missed and the obvious risks get worked twice.
QBR Prep Eats A Half-Day Per Account
Monday morning before a customer business review, the CSM is pulling product-usage, ticket-volume, NPS, billing health, and exec-relationship notes into a deck. Each tab reload is a context switch; each chart is a screenshot. By the time the deck is ready the strategic narrative has been buried under the data-gathering tax.
Champion Departures Get Noticed After The Champion Is Gone
The economic buyer at a $480k account quietly updates their LinkedIn to a new company on a Thursday. The CSM finds out three weeks later — by which point the new VP has already had a competitor pitch and the renewal call has shifted from "expand" to "defend." A champion-watch signal would have triggered same-day outreach.
Mango CS Agent At A Glance
Mango CS AI
At-risk surfacing, renewal pipeline, expansion signals, handoff readiness.
Inside Mango CS Agent — The Actual Capabilities
Every block below maps to a real tool the agent calls against the canonical CS data — CRM accounts, renewal pipeline, AE→CSM handoff checklists, expansion signals, implementation projects. Nine tools, all read-only. State changes (open save play, log save outcome, escalate churn) stay in the Mango CS app surface.
At-Risk Accounts, With Component-Scored Health
The agent surfaces accounts whose latest health score is below 50 or whose lifecycle is flagged at_risk — ordered worst-first. For any single account, the agent breaks the score into its four components (usage, support, sentiment, contract risk), the raw inputs, and the weights — so the CSM can act on the actual signal, not a black-box number.
- At-risk shortlist via list_at_risk_accounts — health below 50 or lifecycle at_risk, sorted worst-first.
- Component-scored health via get_account_health — overall plus usage / support / sentiment / contract risk with raw inputs and weights.
- "My accounts" via list_my_accounts — full unfiltered CSM book, excluding churned, scoped to the user.
- Health math is canonical — the agent reads the same HealthScoreCalculator the app's dashboard renders; no parallel scoring.
Renewal Pipeline By Stage, Window, And Risk
The full renewal pipeline in chat — bucketed by pipeline stage (on_track, at_risk, expanding, churning) for a configurable 30 / 60 / 90-day window, plus summary counts for the CRO view. No more maintaining six saved filters; the CSM lead asks "what's in the 60-day window?" and gets the same answer their CRO will get next week.
- Upcoming renewals via list_upcoming_renewals — bucketed by stage, configurable 30/60/90-day window.
- Pipeline summary via get_renewal_pipeline_summary — total + per-stage counts for the CRO-level view.
- Pipeline stage is canonical — same RenewalPipelineService the app's renewal dashboard uses; no second source of truth.
- PII-masked on every prompt — account names and identifying detail are masked before any LLM call.
Expansion Signals And Handoff Readiness
The agent surfaces accounts showing expansion signals — either healthy (score ≥75) and approaching renewal, or with a champion contact who's gone quiet. Same chat, the agent lists the AE→CSM handoffs whose checklist is still pending and exactly which required fields are missing — so the CSM walks into kickoff with the context the AE had.
- Expansion candidates via list_expansion_candidates — healthy + approaching renewal, or champion contact with 30+ days quiet.
- Pending handoffs via list_pending_handoffs — AE→CSM checklists still missing fields, with the specific gap listed.
- Active implementations via list_active_onboarding — projects in implementation with stage, health, target go-live, session progress.
- Audit trail on every read — every tool call logs the requesting user, the tool, and the parameters, attached to the account record.
Outcomes CSM Teams Can Measure
The agent's job is to put at-risk visibility one chat message away — so saves happen earlier, renewals don't slip, and expansion plays don't get missed. Measure against your pre-agent baseline.
- Time-to-risk-identification — days from the health-score drop to first save-play action by the CSM.
- Renewal pipeline coverage — share of renewing accounts where the CSM has reviewed health + pipeline stage in the last 14 days.
- Gross retention rate (GRR) — does earlier risk identification correlate with fewer churn surprises at renewal?
- Net retention rate (NRR) — share of expansion candidates surfaced that the CSM acted on within 30 days.
- Handoff completeness — share of AE→CSM handoffs going into kickoff with the checklist fully complete.
Intentionally Read-Only · PII-Masked
Mango CS Agent's RISKY_TOOLS list is empty by design. State changes — open a save play, log a save outcome, escalate churn, schedule a QBR — stay in the Mango CS workflow surface where the CSM's notes, sentiment captures, and forecast updates are recorded against the canonical account. The agent surfaces the signal; the CSM owns the action.
- Zero write tools — RISKY_TOOLS = []. No state changes on accounts, no forecast updates, no save plays opened by the agent.
- Permission-aware — users see only the book of business their role allows; the agent never bypasses scope.
- PII Protection on every prompt — account names, contact emails, and identifying detail are masked before any LLM call.
- Canonical-source pattern — every tool is a thin wrapper around the same HealthScoreCalculator, RenewalPipelineService, ExpansionSignalDetector, HandoffChecklist scopes the app uses.
WHAT TEAMS TRY INSTEAD
The four alternatives — and why none of them see health, renewal, and expansion in one place
Most CS leaders reach for one of these four before considering an embedded agent. None of them stick because none of them combine product usage, support tickets, billing signal, and contract terms with the canonical health-score logic.
ChatGPT or Claude on a quarterly CS export
General-purpose AI on a stale CSV
- Reads live health, renewal pipeline, and expansion signal — not last quarter's snapshot
- Returns account-level answers tied to the actual customer record, not a snippet
- Honors CSM book-of-business scoping so reps don't see accounts they don't own
Gainsight AI, Catalyst AI, ChurnZero Drive AI
Vendor-trapped AI inside the CS platform
- Reads usage, support, billing, and contract data directly — no third-party CS platform to sync with first
- Uses your canonical HealthScoreCalculator, not a Gainsight-rules engine that requires admin tuning
- Surfaces handoff and onboarding checklists in the same surface as the renewal pipeline — not three tools deep
A CS ops analyst with Salesforce + Looker
An analyst building the QBR deck the night before
- Answers in chat in seconds — no Salesforce report, no Looker explore, no ticket in the BI queue
- Joins product-usage, billing, and ticket data the warehouse rarely has fresh enough
- Same answer every time — the agent uses the same scoring definitions, not a one-off SQL guess
The manual fallback — "the CSM checks the dashboard"
A weekly book-review meeting and a spreadsheet
- Surfaces at-risk and expansion-ready accounts daily, not weekly — before the renewal date is two weeks out
- Standardizes the handoff and onboarding checklist so every CSM works the same playbook
- Deflects "what's the health score on Acme?" questions a CS leader shouldn't be a router for
PLATFORM LEVERAGE
Mango CS Agent inherits everything the platform already runs
A standalone CS platform has to plumb each of these. The agent gets them for free because the platform already does.
Canonical health-score source
Wraps the same HealthScoreCalculator the CS app uses — no parallel scoring rules, no drift between the agent and the rule of record.
Cross-app context
Joins product usage, support tickets, billing signal, and contract terms in one call — a CS-only platform sees one slice at a time.
Book-of-business scoping
CSMs see only the accounts their role allows; the agent never returns accounts outside the rep's book.
PII masking on every prompt
Account names, contact emails, and identifying detail are masked before any LLM call. The model sees structure, not identity.
Audit trail & retention
Every tool call lands in AiApiLog with the same retention and eDiscovery posture as the rest of the platform.
RubyLLM-grounded model tiering
Nano / small / medium / standard tier selection routes routine pulls to cheap models and reserves the big ones for cohort and risk reasoning — automatically, per call.
INDUSTRY FIT
Industries where embedded CS intelligence moves the most weight
Mango CS Agent matters most where retention and expansion run the business.
B2B SaaS
Calls renewal risk and expansion readiness daily across the CSM book — not in the post-quarter retrospective.
Subscription Services
Joins recurring billing, usage cadence, and support load to surface dormant accounts before the renewal email goes out.
Marketplaces & Platforms
Tracks two-sided engagement signal (supply and demand activity) — most CS platforms only see the paying side.
B2B Services & Agencies
Pulls project burn, retainer pacing, and stakeholder engagement to call account risk before the QBR.
Financial Services
Tags every health and renewal answer with source and computation so audit and the CRO can defend the number.
EdTech & Public Sector
Runs entirely inside FedRAMP-eligible deployment options with full audit logging — no customer data leaving the tenant boundary.
WHY MANGOAPPS WINS
An embedded CS agent beats a chatbot, a CS-platform add-on, or a custom build on every axis
The argument finance, CS, RevOps, and IT all share — and the one a horizontal AI or single-vendor assistant structurally cannot answer.
Cheaper than the alternatives
No Gainsight or Catalyst SKU, no per-seat ChatGPT license, no six-month CS-platform implementation, no extra CS ops headcount for ad-hoc questions.
More secure
PII masking pre-prompt, book-of-business scoping, and AiApiLog audit trail mean customer detail never leaves the tenant boundary in plaintext.
Easier to deploy
Already deployed if Mango CS is enabled. Turn the agent on, point it at the role scopes you already configured, and it's running the same day.
Easier to use
Lives in chat next to every other CS conversation — no separate platform UI, no Salesforce report, no QBR deck assembly.
Easier to manage
Per-business book-of-business rules, masking policy, and audit retention sit in the same admin console as every other app's settings.
Easier to extend
Shares the agentic tool framework with every other MangoApps agent. New health signals, expansion signals, and renewal motions ship as tools, not rewrites.
AI is actually better
A horizontal or CS-platform AI can show a health score. Only Mango CS Agent can also join product usage, billing, and contract terms to explain why it moved — and act on the next step.
At our head office within HR, marketing, and finance, we use ChatGPT quite a bit, and MangoApps AI Helper is a useful tool for us. As I go around to the stores, I’ve been showing them how the AI Intranet Helper can find things and answer plain language questions about our resources, and they’re quite excited about that.
Alison van Zijl
Head of Human Resources
Full House
Customer Success
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Frequently Asked Questions About Mango CS Agent
Nine read-only tools — list_at_risk_accounts, list_upcoming_renewals, list_pending_handoffs, list_expansion_candidates, get_account_health, list_active_onboarding, list_my_accounts, get_renewal_pipeline_summary, plus the unfiltered CSM book.
No. RISKY_TOOLS = [] — Mango CS Agent is strictly read-only. Open a save play, log a save outcome, escalate churn, schedule a QBR, update a forecast — all of that stays in the Mango CS workflow surface where the CSM's notes and sentiment captures are recorded against the canonical account.
It doesn't — it surfaces what the canonical HealthScoreCalculator already returns. Four components: usage (40%), support (20%), sentiment (20%), contract risk (20%). For any account, get_account_health returns the overall score plus the per-component breakdown plus the raw inputs that fed each component. No parallel scoring, no black box.
PII Protection runs on every prompt — account names, contact emails, and identifying detail are masked before any LLM call. Permission scope is enforced — non-CSM users hit the same app permissions; managers see only the book their role allows. The agent never bypasses scope to surface an account the user can't otherwise see.
Time-to-risk-identification, renewal pipeline coverage, GRR, NRR, and handoff completeness. Compare against your pre-agent baseline before drawing conclusions.
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