ra-engagement-tracker

name	ra-engagement-tracker
description	Tracks touchpoint frequency and recency across all channels for every stakeholder at every account. Computes engagement health per contact, detects declining patterns, and identifies accounts where the relationship is cooling before the health score reflects it. Use when asked to track customer engagement, monitor touchpoint cadence, identify engagement gaps, assess relationship activity, or when any workflow needs to know how recently and how frequently the CSM is engaging with their accounts. Also triggers for questions about touchpoint cadence, engagement health, contact activity, relationship frequency, or communication gaps.
license	MIT
metadata	{"author":"Stephen Rogan","version":"1.0.0","pillar":"relationship-architecture","category":"relationship-data"}

Engagement Tracker

Tracks touchpoint frequency and recency across all communication channels for every stakeholder. Computes engagement health per contact and per account. Part of the Relationship Architecture pillar.

This is a measurement and alerting skill. It tracks frequency -- how often and how recently have you engaged. It does not assess quality -- a weekly call where nothing meaningful is discussed scores the same as a weekly call that transforms the relationship. Frequency is necessary for healthy relationships; it is not sufficient. The CSM provides the quality assessment.

When to Run

• Continuous: Logs touchpoints as they occur from connected channels
• Scheduled: Weekly engagement health computation and gap detection
• On-demand: When a CSM requests engagement data for a specific account or contact

Core Execution Logic

Step 1: Log Touchpoints from All Channels

Every customer interaction is a touchpoint. Capture from all available sources:

Channel	Source	What Counts as a Touchpoint	What Does Not Count
Email	Email integration	Emails sent to or received from a customer contact (excluding automated sequences)	Auto-replies, system notifications, marketing emails
Meeting	Calendar integration	Completed meetings with customer attendees (not cancelled, not no-showed)	Internal-only meetings, cancelled meetings
Call	Call platform or CRM activity	Completed phone/video calls with customer contacts	Voicemails left without conversation, abandoned calls
Support	Support platform	Ticket interactions where the CSM or customer exchanges substantive communication	Automated ticket status updates, system notifications
Community	Community platform (if ca-community-monitor is active)	Customer posts or replies in the community	Passive viewing without posting
Product	Product analytics	Portal login or feature usage (passive engagement -- tracked but weighted differently)	API calls, automated syncs, background processes

For each touchpoint, log:

• Timestamp
• Channel
• Direction: inbound (customer-initiated) or outbound (CSM-initiated)
• Contact(s) involved
• Type: scheduled (planned touchpoint) or unscheduled (ad hoc)

Step 2: Compute Per-Contact Engagement Metrics

For each contact in ra-stakeholder-mapper:

Metric	Computation	Why It Matters
Days since last touch	Calendar days from most recent touchpoint to today	Recency -- is the relationship current?
Average touchpoint frequency	Mean days between touchpoints over trailing 90 days	Cadence -- how often are you engaging?
Touchpoint trend	Frequency this 30-day period vs. previous 30-day period	Direction -- is engagement increasing, stable, or declining?
Channel distribution	Percentage of touchpoints per channel	Diversity -- single-channel engagement (email only) is less robust than multi-channel
Inbound ratio	Inbound touchpoints / total touchpoints	Reciprocity -- a high inbound ratio suggests the customer is engaged. A zero inbound ratio suggests you are chasing
Response latency	Average time from CSM outreach to customer response	Responsiveness -- increasing latency is an early cooling signal

Step 3: Classify Engagement Health

For each contact, compare engagement metrics against the expected cadence for their stakeholder type (from ra-stakeholder-mapper):

Health Level	Criteria	Signal
Strong	Last touch within expected cadence. Trend stable or improving. Inbound ratio >0.3. Multi-channel	Relationship is active and reciprocal
Adequate	Last touch within expected cadence but one or more secondary metrics weakening (declining trend, single-channel, low inbound)	Relationship is maintained but showing early signs of cooling
Declining	Last touch within 1.5x expected cadence. Trend declining for 2+ consecutive periods. Or inbound ratio dropped to zero	Relationship is cooling. Not yet a gap but heading there without intervention
Gap	Last touch >2x expected cadence	Contact is not being managed. Coverage has lapsed
Lost	No engagement across any channel in 90+ days	Contact may have left, changed roles, or fully disengaged. Route to ra-stakeholder-change-detector for investigation

Step 4: Compute Per-Account Engagement Health

Aggregate contact-level health into an account-level engagement score:

Weighted by stakeholder type:

• Champion engagement: 35% weight (the most important relationship)
• Economic Buyer engagement: 25% weight
• Executive Sponsor engagement: 15% weight
• Technical Lead engagement: 15% weight
• All other contacts: 10% weight

Account engagement score = weighted sum of contact engagement scores (each contact scored 0-100 based on health level: Strong=90, Adequate=70, Declining=45, Gap=20, Lost=0)

Account engagement classification:

Score	Classification	Interpretation
75-100	Healthy engagement	Key contacts are actively engaged. Cadence is being maintained
55-74	Adequate engagement	Most contacts engaged but some weakening. Monitor and address gaps
35-54	Declining engagement	Meaningful engagement gaps exist. Investigate and intervene
0-34	Critical engagement failure	Multiple key contacts disengaged. Relationship infrastructure is at risk

Step 5: Detect Patterns and Generate Alerts

Pattern	Detection	Alert
No-reply streak	3+ outbound emails to the same contact with no response	CSM alert: "[Contact] has not responded to last 3 emails. Consider calling or approaching through a different contact"
Meeting cancellation pattern	2+ meetings cancelled or no-showed by the same contact in 30 days	CSM alert: "[Contact] cancelled or missed 2+ meetings. Engagement is declining"
Inbound engagement drop	Account's inbound ratio drops from >0.3 to <0.1 over 60 days	CSM alert: "[Account] has stopped initiating contact. All recent touchpoints are outbound"
Champion cooling	Champion contact moves from Strong to Declining engagement health	CSM + manager alert: "Champion [name] engagement declining at [account]. [Specific metrics]"
Complete silence	Zero touchpoints across all channels for an account in 30+ days	CSM alert: "[Account] has had no engagement of any kind in [X] days. Investigate immediately"

Step 6: Generate Engagement Report

Per-CSM weekly engagement summary:

{
  "csm": "Jane Doe",
  "report_date": "2026-03-10",
  "portfolio_engagement": {
    "total_accounts": 42,
    "engagement_distribution": {
      "healthy": 28,
      "adequate": 8,
      "declining": 4,
      "critical": 2
    },
    "avg_engagement_score": 72
  },
  "alerts_this_week": [
    {
      "type": "no_reply_streak",
      "account": "Gamma Corp",
      "contact": "Lisa Park (VP Eng)",
       
       
    
    
       
       
       
       
       
    
  
   
     
             
    
     
             
    
  
   
     
     
     
     
               
    
  

Handoff to Human

Decision Point	Context Provided	What the Human Decides
Declining engagement response	Specific contacts, metric trends, pattern details	How to respond -- call, email, approach through another contact, escalate to manager, or wait. The approach depends on the relationship
No-reply interpretation	Streak length, contact role, prior engagement pattern	Whether the silence means disengagement, a busy period, a personnel change, or deliberate avoidance. Each has a different response
Cadence adjustment	Current engagement frequency vs. expected cadence	Whether the expected cadence is right for this contact. Some contacts prefer less frequent engagement. The cadence rules are defaults, not mandates
Engagement quality assessment	Frequency and recency data	Whether the touchpoints are meaningful. A CSM meeting weekly with a customer but never advancing the relationship has a perfect engagement score and a failing relationship. The human layer is essential
Alert triage	Multiple alerts across the portfolio	Which declining engagements to address first, given limited CSM time and competing priorities

Confidence and Limitations

• High confidence for touchpoint logging and frequency computation -- structured event data from connected systems
• High confidence for engagement health classification -- deterministic comparison of metrics to defined thresholds
• Medium confidence for pattern detection (no-reply streaks, cancellation patterns) -- these are reliable signals but have multiple possible interpretations
• Medium confidence for inbound ratio as an engagement quality proxy -- a declining inbound ratio is a meaningful signal, but some customers are naturally passive communicators. Benchmark against the contact's own historical pattern, not a universal standard
• Low confidence for engagement quality assessment. This is the fundamental limitation: the skill tracks frequency, not depth. A 15-minute status call and a 2-hour strategic planning session count the same. The CSM provides the quality layer
• Cannot track engagement that happens outside connected systems (in-person meetings, conferences, informal conversations, personal phone calls)
• "No inbound engagement" is a strong disengagement signal in most cases, but some customers only engage reactively and have always done so. The baseline matters more than the absolute number

Dependencies

Required:

• CRM API (activity data, contact records)
• Calendar integration (meeting data)
• Email integration (email activity data)

Strongly recommended:

• ra-stakeholder-mapper (stakeholder types and expected cadence for health computation)
• Call platform integration (call data)
• Support platform (support interaction data)
• ca-community-monitor (community engagement channel)

Downstream consumers:

• bi-health-score (engagement data feeds the engagement component -- 25% default weight)
• ra-stakeholder-mapper (engagement status per contact)
• bi-risk-detector (declining engagement as a risk signal)
• lo-check-in-scheduler (cadence compliance data)
• cc-report-generator (engagement metrics for CSM and manager reports)

References

• references/engagement-methodology.md -- Channel definitions, health classification thresholds, and cadence baseline calibration