analytics-tracking
When the user wants to set up, improve, or audit sales metrics and pipeline tracking. Also use when the user mentions "sales metrics," "pipeline tracking," "CRM setup," "sales dashboard," "activity tracking," "conversion tracking," "win rate," or "sales reporting." For testing sales approaches, see ab-test-setup.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/louisblythe/sales-skills --skill analytics-tracking- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads analytics-tracking automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Sales Analytics & Pipeline Tracking
You are an expert in sales analytics and pipeline management. Your goal is to help set up tracking systems that provide actionable insights for improving sales performance, forecasting accurately, and coaching effectively.
Initial Assessment
Before implementing sales tracking, understand:
-
Business Context
- What decisions will this data inform?
- What are your key sales stages?
- What questions need answering?
-
Current State
- What CRM/tools are in use?
- What's being tracked today?
- What's working/not working?
-
Team Context
- Sales team size and structure?
- Who needs access to what data?
- What's the reporting cadence?
Core Principles
1. Track for Decisions, Not Data
- Every metric should inform an action
- Avoid vanity metrics
- Quality > quantity of data points
2. Start with the Questions
- What do you need to know?
- What will you change based on this data?
- Work backwards to what you need to track
3. Make Data Entry Easy
- Reps won't track what's painful
- Automate where possible
- Minimize required fields
4. Maintain Data Quality
- Regular data hygiene
- Clear definitions for each field
- Accountability for accuracy
Essential Sales Metrics
Activity Metrics
Outbound Activity
- Emails sent
- Calls made
- LinkedIn touches
- Meetings booked
- Demos scheduled
Activity Ratios
- Emails to reply
- Calls to connect
- Connects to meeting
- Meetings to opportunity
Why Track: Identifies effort vs. results gaps, coaching opportunities, and capacity planning.
Pipeline Metrics
Volume Metrics
- Total pipeline value
- Number of opportunities
- Pipeline by stage
- New pipeline created (weekly/monthly)
Velocity Metrics
- Average deal size
- Win rate
- Sales cycle length
- Stage-to-stage conversion rates
Coverage Metrics
- Pipeline coverage ratio (pipeline ÷ quota)
- Weighted pipeline
- Commit vs. upside
Why Track: Predicts revenue, identifies bottlenecks, informs forecasting.
Conversion Metrics
Funnel Conversions
- Lead to opportunity
- Opportunity to proposal
- Proposal to closed won
- Overall lead to close
Stage Conversions
- Discovery to demo
- Demo to proposal
- Proposal to negotiation
- Negotiation to close
Why Track: Shows where deals stall, where to focus improvement efforts.
Outcome Metrics
Revenue Metrics
- Closed won revenue
- Average deal size
- Revenue by segment/product
- New vs. expansion revenue
Efficiency Metrics
- Win rate (overall and by stage)
- Sales cycle length
- CAC (Customer Acquisition Cost)
- Revenue per rep
Why Track: Measures ultimate success, informs strategy and hiring.
Pipeline Stage Definitions
Define Clear Exit Criteria
Each stage needs clear criteria for what qualifies an opportunity to move forward.
Example Stage Definitions:
| Stage | Exit Criteria | Required Fields |
|---|---|---|
| Prospect | Identified potential fit, initial outreach planned | Company size, industry, contact info |
| Discovery | Had discovery call, qualified BANT/MEDDIC | Pain identified, budget range, timeline |
| Demo | Completed product demo | Decision makers identified, use case clear |
| Proposal | Sent formal proposal | Pricing confirmed, legal review status |
| Negotiation | Active negotiation on terms | Final objections, expected close date |
| Closed Won | Contract signed | Signed contract, payment terms |
| Closed Lost | Deal lost | Loss reason, competitor if applicable |
Common Stage Frameworks
Simple (4 stages): Qualified → Demo → Proposal → Closed
Standard (6 stages): Prospect → Discovery → Demo → Proposal → Negotiation → Closed
Complex (8 stages): Lead → Qualified → Discovery → Demo → Technical Eval → Proposal → Negotiation → Closed
Stage Probability Mapping
Assign win probability to each stage for weighted pipeline:
| Stage | Typical Probability |
|---|---|
| Discovery | 10-20% |
| Demo | 20-40% |
| Proposal | 40-60% |
| Negotiation | 60-80% |
| Verbal Commit | 80-90% |
Adjust based on your actual historical conversion rates.
CRM Setup Best Practices
Required Fields (Keep Minimal)
On the Account:
- Company name
- Industry
- Employee count / revenue range
- Website
On the Opportunity:
- Deal name
- Amount
- Close date
- Stage
- Primary contact
- Source (how they entered pipeline)
On the Contact:
- Name, email, phone
- Title / role
- Buyer persona
Recommended Fields (For Analysis)
On the Opportunity:
- Loss reason (picklist)
- Competitor (if applicable)
- Use case / product interest
- Champion identified (checkbox)
- Decision process documented
On the Activity:
- Activity type
- Outcome
- Next step scheduled
Field Design Principles
Use picklists over free text
- Enables reporting
- Ensures consistency
- Faster to fill out
Make important fields required
- But only truly important ones
- Every required field reduces compliance
Add validation rules
- Amount can't be $0
- Close date can't be in the past (for open deals)
- Stage changes require certain fields
Activity Tracking
What Activities to Track
Minimum:
- Emails (auto-logged from email integration)
- Calls (manual or auto-logged from dialer)
- Meetings (auto-logged from calendar)
Recommended:
- LinkedIn messages/connections
- Demo completions
- Proposal sends
- Contract sends
Activity Outcomes
Track outcomes, not just activities:
| Activity | Outcome Options |
|---|---|
| Call | Connected, Voicemail, No Answer, Wrong Number |
| Sent, Replied, Bounced | |
| Meeting | Completed, No Show, Rescheduled |
| Demo | Completed, Partial, No Show |
Automation Opportunities
Auto-log from integrations:
- Email sync (Gmail, Outlook)
- Calendar sync
- Dialer integration
- LinkedIn Sales Navigator
Auto-create tasks:
- Follow-up after meeting
- Check in after proposal
- Re-engage after quiet period
Sales Dashboards
Rep Dashboard (Daily View)
Activity Section:
- Emails sent today/this week
- Calls made today/this week
- Meetings completed
- Activity vs. target
Pipeline Section:
- My open pipeline (total value)
- Deals closing this month
- Overdue tasks
- Stale opportunities (no activity in X days)
Manager Dashboard (Weekly View)
Team Activity:
- Activity by rep
- Activity trends (week over week)
- Activity to result ratios
Pipeline Health:
- Total team pipeline
- Pipeline by stage
- Pipeline created this period
- Deals at risk (stale, pushed, etc.)
Forecast:
- Commit vs. target
- Best case vs. target
- Weighted pipeline
Executive Dashboard (Monthly View)
Results:
- Closed won vs. target
- Win rate trends
- Average deal size trends
- Sales cycle trends
Forecast:
- Current quarter forecast
- Pipeline coverage
- Forecast accuracy (predicted vs. actual)
Efficiency:
- Revenue per rep
- CAC trends
- Ramp time for new reps
Win/Loss Tracking
Loss Reason Categories
Create a picklist of loss reasons:
Competitive:
- Lost to [Competitor A]
- Lost to [Competitor B]
- Lost to incumbent/status quo
Fit Issues:
- Budget constraints
- Timeline mismatch
- Feature gap
- Wrong use case
Process Issues:
- No decision made
- Champion left
- Priorities changed
- Went dark
Our Issues:
- Poor sales execution
- Pricing/packaging
- Implementation concerns
Win Analysis
Track what contributed to wins:
- Primary use case
- Key differentiators that resonated
- Competitive situation
- Champion persona
- Decision process
Using Win/Loss Data
Monthly review:
- Loss reasons by frequency
- Competitive win/loss rates
- Patterns by segment, rep, product
Action from insights:
- Lost on price → Review packaging
- Lost on feature → Inform product
- Lost to competitor → Update battlecards
- Went dark → Improve follow-up
Forecasting Framework
Forecast Categories
Commit:
- High confidence (90%+)
- Verbal agreement or contract in progress
- Known close date
Best Case:
- Medium confidence (50-90%)
- Demo completed, positive signals
- Potential to close this period
Pipeline:
- Lower confidence (<50%)
- Early stage or unknown timing
- Requires work to close
Forecast Methodology
Bottom-up (rep-driven):
- Reps categorize each deal
- Manager reviews and adjusts
- Roll up to total
Weighted pipeline:
- Stage probability × deal amount
- Sum across all deals
- Adjust for historical accuracy
Historical trend:
- Look at past conversion rates
- Apply to current pipeline
- Sanity check against rep forecast
Forecast Accuracy Tracking
| Metric | Calculation |
|---|---|
| Forecast Accuracy | Actual ÷ Forecasted |
| Coverage Accuracy | Deals won from commit ÷ Total commit |
| Call Accuracy | % of deals forecasted correctly |
Track over time to improve forecasting skill.
Reporting Cadence
Daily (Rep Self-Management)
- Activities completed
- Tasks due today
- Deals with meetings today
Weekly (Team Meeting)
- Pipeline created
- Deals won/lost
- Activity vs. targets
- Forecast update
- Deals to discuss
Monthly (Leadership Review)
- Results vs. target
- Win rate and cycle time
- Pipeline health
- Rep performance
- Forecast for next period
Quarterly (Business Review)
- Trend analysis
- Win/loss insights
- Process improvements
- Territory/segment performance
- Headcount and capacity
Data Quality Management
Regular Hygiene Tasks
Weekly (Rep):
- Update close dates on all deals
- Clear completed tasks
- Update deal stages
Monthly (Manager):
- Review stale opportunities (no activity in 30+ days)
- Audit high-value deals for completeness
- Check for duplicate records
Quarterly (Ops):
- Clean up inactive records
- Review and update picklists
- Audit stage definitions
Data Quality Metrics
| Metric | Target |
|---|---|
| Opportunities with next step | >90% |
| Opportunities with close date in past | <5% |
| Contacts with email | >95% |
| Deals with loss reason (when lost) | 100% |
Tool Integration
Core Stack
CRM: Salesforce, HubSpot, Pipedrive
- Single source of truth
- All deal and contact data
Email Integration: Native or Outreach/Salesloft
- Auto-log emails
- Sequence tracking
Calendar Integration: Google/Outlook sync
- Auto-log meetings
- Availability for scheduling
Dialer: Aircall, Dialpad, native
- Call logging
- Recording for coaching
Analytics Layer
Built-in CRM reporting: Good for basics BI tool (Looker, Tableau): For advanced analysis Rev ops tools (Clari, Gong): For forecasting and insights
Implementation Checklist
Before Launch
- Define sales stages with exit criteria
- Identify required vs. optional fields
- Set up loss reason picklist
- Create basic dashboards
- Document data entry expectations
- Train team on new process
After Launch
- Weekly data quality review
- Monthly reporting accuracy check
- Quarterly process refinement
- Ongoing training for new reps
Questions to Ask
If you need more context:
- What CRM are you using?
- What's your sales process (stages)?
- What decisions will this data inform?
- What's your current forecasting accuracy?
- How large is your sales team?
- What's already being tracked?
Related Skills
- ab-test-setup: For testing sales approaches
- cold-outreach: For outbound activity tracking
- discovery-calls: For tracking discovery metrics
- deal-acceleration: For pipeline velocity
FAQ
What does the analytics-tracking skill do?
When the user wants to set up, improve, or audit sales metrics and pipeline tracking. Also use when the user mentions "sales metrics," "pipeline tracking," "CRM setup," "sales dashboard," "activity tracking," "conversion tracking," "win rate," or "sales reporting." For testing sales approaches, see ab-test-setup.
How do I install analytics-tracking?
Run npx skills add https://github.com/louisblythe/sales-skills --skill analytics-tracking in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/analytics-tracking/ (personal) or .claude/skills/analytics-tracking/ (project).
Which AI agents can use analytics-tracking?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is analytics-tracking safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains analytics-tracking?
It is published by louisblythe in louisblythe/sales-skills. It has 425 recorded installs.
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