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Customer Support Management Dashboard - Product Requirements

For: Product Managers, Customer Success Team, Business Stakeholders Last Updated: November 24, 2025 Status: Draft - Awaiting Approval

Executive Summary​

The CSM Dashboard provides real-time visibility into customer engagement and usage patterns, enabling our Customer Success, Sales, and Support teams to proactively identify at-risk customers and take action before churn occurs.

Key Benefits:

  • Identify inactive customers before they churn
  • Detect usage pattern anomalies automatically
  • Prioritize customer outreach based on health scores
  • Track customer engagement trends over time

Problem Statement​

Currently, our Customer Success team lacks a centralized view of customer health metrics. They must manually review multiple systems to identify customers who may be at risk of churning. This reactive approach means we often discover issues too late to intervene effectively.

Current Pain Points:

  • No single source of truth for customer health
  • Manual, time-consuming customer health checks
  • Reactive rather than proactive support
  • Difficulty prioritizing which customers need attention

Solution​

Build a Customer Support Management (CSM) Dashboard that:

  1. Automatically tracks 5 key customer health metrics
  2. Alerts the team when customers show warning signs
  3. Provides historical trends to identify patterns
  4. Enables filtering and search to quickly find at-risk customers

Target Users​

Primary Users​

  • Customer Success Managers (CSM) - Daily monitoring of customer health
  • Support Team - Prioritizing support requests
  • Sales Team - Identifying expansion/upsell opportunities

Access​

  • Restricted to @pivotapp.ca email accounts
  • Web-based dashboard (desktop/laptop)

Customer Health Metrics​

The dashboard tracks 5 key metrics per customer:

1. Number of Employees​

What it measures: Total active (non-archived) employees

Why it matters: Sudden decreases may indicate downsizing or churn risk

Alert thresholds:

  • 🔴 Critical: Decreased by >20% in 30 days
  • 🟡 Warning: Decreased by 10-20% in 30 days

2. Last Master Account Login​

What it measures: When the company's admin last logged into Pivot

Why it matters: Inactive accounts are strong churn indicators

Alert thresholds:

  • 🔴 Critical: No login in >14 days
  • 🟡 Warning: No login in 7-14 days

3. Open Shifts >10%​

What it measures: Percentage of unfilled shifts in draft schedules (14-day average)

Why it matters: High open shift % indicates scheduling inefficiencies or understaffing

Alert thresholds:

  • 🔴 Critical: Average >20%
  • 🟡 Warning: Average 10-20%

Result values:

  • Yes - Average >10% (needs attention)
  • No - Average ≤10% (healthy)
  • None - No schedules created

4. Shifts Assigned Outside Availability >10%​

What it measures: Percentage of shifts assigned when employees are unavailable (14-day average)

Why it matters: Poor scheduling practices lead to employee dissatisfaction

Alert thresholds:

  • 🔴 Critical: Average >20%
  • 🟡 Warning: Average 10-20%

Result values:

  • Yes - Average >10% (needs attention)
  • No - Average ≤10% (healthy)
  • None - No published schedules

5. Conflicting Clock-Ins >50%​

What it measures: Percentage of timecards with conflicts (14-day average)

Why it matters: High conflict rate indicates poor time tracking or payroll data quality issues

Alert thresholds:

  • 🔴 Critical: Average >70%
  • 🟡 Warning: Average 50-70%

Result values:

  • Yes - Average >50% (needs attention)
  • No - Average ≤50% (acceptable)
  • None - No timecards

Dashboard Views​

1. Customer List (Main View)​

Shows:

  • All customers in a searchable, sortable table
  • Alert level for each customer (Critical, Warning, Healthy)
  • Key metrics at a glance
  • Quick filters by alert level

Features:

  • Search by company name or email
  • Filter by alert level, specific metrics
  • Export to CSV
  • Click customer to view details

2. Customer Detail Page​

Shows:

  • Company information (name, contact, location)
  • All 5 health metrics with current values
  • Active alerts (plain English explanations)
  • 90-day trend charts for each metric
  • Recent activity timeline

Features:

  • Drill down into specific metric details
  • View historical data
  • (Future) Quick actions: send email, create support ticket

3. Alerts Dashboard​

Shows:

  • List of all active alerts across all customers
  • Alert rules and thresholds
  • Alert history

Features:

  • Dismiss or mark alerts as resolved
  • Filter by alert type
  • Sort by severity or date

Success Metrics​

Phase 1 (MVP)​

  • All CSMs using dashboard daily
  • Average response time to critical alerts <24 hours
  • 80% of at-risk customers contacted before churning
  • CSM team reports 50% reduction in time spent on manual health checks

Phase 2​

  • Churn rate reduced by 15%
  • Customer engagement scores improved by 20%
  • Support team using dashboard to prioritize tickets
  • Sales team using dashboard for expansion opportunities

Phase 3​

  • Predictive churn model implemented
  • Automated workflows trigger based on metrics
  • Integration with support ticketing system
  • Mobile app available for CSM team

Out of Scope (Phase 1)​

The following features will NOT be included in the initial release:

  • ❌ Automated email alerts to customers
  • ❌ Integration with support ticketing systems
  • ❌ Custom metric builder (fixed 5 metrics only)
  • ❌ Customer segmentation/cohorts
  • ❌ Predictive analytics / ML-based churn prediction
  • ❌ Mobile app
  • ❌ Slack bot integration
  • ❌ Bulk actions (e.g., mark multiple customers)

These features may be added in future phases based on user feedback.

User Workflows​

Workflow 1: Daily Health Check (CSM)​

  1. CSM logs into dashboard
  2. Reviews summary cards showing # of critical/warning/healthy customers
  3. Clicks "Critical" filter to see urgent issues
  4. Opens each critical customer's detail page
  5. Reviews specific alerts and trends
  6. Takes action:
    • Sends email to customer
    • Schedules call
    • Creates support ticket
    • Documents in CRM

Expected time: 15-20 minutes daily (vs. 2+ hours manually)

Workflow 2: Prioritizing Support Tickets (Support Team)​

  1. Support agent receives new ticket
  2. Searches for customer in CSM dashboard
  3. Reviews customer health metrics
  4. Adjusts ticket priority based on customer health:
    • Critical alert customer → High priority
    • Healthy customer → Normal priority
  5. Responds to ticket with appropriate urgency

Expected time: 1-2 minutes per ticket

Workflow 3: Identifying Expansion Opportunities (Sales)​

  1. Sales rep filters dashboard for "Healthy" customers
  2. Further filters for:
    • Employee count increasing >20% in 30 days (growing fast)
    • High engagement (regular logins, low conflicts)
  3. Reviews customer details
  4. Reaches out with upsell/cross-sell offers

Expected time: 30 minutes weekly to build outreach list

Data Refresh Schedule​

MetricUpdate FrequencyTiming
Number of EmployeesReal-timeInstant when employee hired/archived
Last Master Account LoginReal-timeInstant on login
Open Shifts >10%Daily batch6:00 AM Toronto time
Unavailable Assignments >10%Daily batch6:00 AM Toronto time
Conflicting Clock-Ins >50%Daily batch6:00 AM Toronto time

Dashboard refresh: Manual "Refresh" button or automatic every 5 minutes

Technical Implementation: Alert Level Calculation​

The alert level (Critical/Warning/Healthy) and corresponding color are determined at the UI level in Pivot-KPI, not computed on-the-fly in the dashboard.

How It Works​

  1. Daily Batch Processing: For every customer, every day, the system calculates all 5 health metrics
  2. Pre-computed Alert Levels: The percentage thresholds are evaluated during batch processing, and the resulting alert level is stored directly in the KPI data
  3. UI Consumption: Pivot-KPI retrieves the pre-computed data, which already includes the alert level, allowing the dashboard to render colors immediately without additional computation

Data Flow​

Firebase Data → Daily Batch Job → Calculate Metrics → Apply Thresholds → Store with Alert Level → Pivot-KPI → Dashboard UI

Benefits of This Approach​

  • Performance: No real-time percentage calculations; colors render instantly
  • Consistency: All users see the same alert levels (no race conditions)
  • Auditability: Historical alert levels are preserved for trend analysis
  • Scalability: Dashboard performance remains constant regardless of customer count

Implementation Phases​

Phase 1: MVP​

  • Finalize requirements and design
  • Development and testing
  • Internal beta with CSM team
  • Refinements based on feedback
  • Production launch

Phase 2: Enhancements​

  • Historical trend analysis
  • Slack integration
  • Custom filters and saved views

Phase 3: Advanced Features​

  • Predictive analytics
  • Mobile app
  • Automation and workflows

Dependencies & Risks​

Dependencies​

  • ✅ Firebase Realtime Database (already in use)
  • ✅ Customer data available in Firebase
  • ✅ Service account credentials configured

Risks​

RiskLikelihoodImpactMitigation
Inaccurate metrics due to incomplete dataMediumHighValidate metric calculations with historical data before launch
Low adoption by CSM teamLowHighInvolve CSMs in design process, provide training
Performance issues with large customer baseLowMediumImplement pagination and caching
Firebase costs increase significantlyLowLowMonitor usage, optimize queries

Questions for Stakeholders​

Before proceeding with development, please provide feedback on:

  1. Metrics: Are these the right 5 metrics to track? Any missing?
  2. Alert Thresholds: Do the thresholds make sense (e.g., 14 days no login = critical)?
  3. Workflows: Do the user workflows match how CSMs actually work?
  4. Priority: Is this the right priority vs. other initiatives?

Next Steps​

  1. Finalize technical architecture
  2. Create detailed mockups/wireframes
  3. Kick off development sprint
  4. Schedule regular sync with stakeholders

Questions? Contact Chip (ciprian@pivotapp.ca) or Slack #pivot-dev