Rep Profile

Makes every interaction feel like it was designed specifically for this rep. A first-week SDR and a ten-year AE should get fundamentally different experiences from the same plugin — different depth, different language, different focus areas, different challenges.

Why This Matters

"Hyper-personalized learning" isn't about adding a name to a template. It means:

•A rep who crushes discovery but struggles with closing gets coaching focused on negotiation
•A rep who just joined gets scaffolded frameworks; a veteran gets contextual nudges
•A rep who learns by doing gets role-play practice; one who learns by studying gets frameworks and examples
•Content complexity scales with the rep's experience and comfort level

How It Works

code

┌─────────────────────────────────────────────────────────────────┐
│                      REP PROFILE                                  │
├─────────────────────────────────────────────────────────────────┤
│  PROFILE COMPONENTS                                               │
│  • Skill assessment (scored competencies)                        │
│  • Experience level (tenure, deals closed, ramp stage)           │
│  • Deal patterns (what they win, what they lose, why)            │
│  • Learning style (doing, studying, observing, discussing)       │
│  • Development plan (current focus areas and progress)           │
│  • Interaction history (what help they've asked for before)      │
├─────────────────────────────────────────────────────────────────┤
│  ADAPTATION RULES                                                 │
│  New rep → More structure, more scaffolding, explicit frameworks │
│  Mid-level → Balanced guidance, focus on weak spots              │
│  Senior rep → Brief nudges, advanced scenarios, edge cases       │
│  Manager → Coaching lens, team patterns, data-driven insights    │
├─────────────────────────────────────────────────────────────────┤
│  SUPERCHARGED (when you connect your tools)                      │
│  + ~~CRM: Deal history, win rates, cycle lengths, quota data     │
│  + ~~CRM: Stage-specific patterns and performance vs team avg    │
│  + ~~conversation intelligence (Gong): Talk-to-listen ratios     │
│  + ~~conversation intelligence (Gong): Questions per call        │
│  + ~~conversation intelligence (Gong): Competitor handling skill  │
│  + ~~conversation intelligence (Gong): Next steps discipline     │
│  + ~~data enrichment (LinkedIn): Career history and expertise    │
│  + ~~data enrichment (ZoomInfo): Industry vertical experience    │
│  + ~~chat: Coaching conversations and peer feedback              │
└─────────────────────────────────────────────────────────────────┘

Profile Structure

Stored in memory/team.md with a section per rep:

markdown

## [Rep Name]

**Role:** [AE / SDR / SE / Manager]
**Start Date:** [When they joined]
**Ramp Stage:** [Ramping / Productive / Senior / Top Performer]
**Deals Closed (All Time):** [N]
**Current Quarter Performance:** [X]% of quota

### Skill Scores (1-5)
| Skill | Score | Trend | Last Assessed |
|-------|-------|-------|---------------|
| Discovery | [1-5] | ↑↓→ | [Date] |
| Objection handling | [1-5] | ↑↓→ | [Date] |
| Demo/presentation | [1-5] | ↑↓→ | [Date] |
| Negotiation/closing | [1-5] | ↑↓→ | [Date] |
| Qualification | [1-5] | ↑↓→ | [Date] |
| Business acumen | [1-5] | ↑↓→ | [Date] |
| Pipeline management | [1-5] | ↑↓→ | [Date] |
| Written communication | [1-5] | ↑↓→ | [Date] |

### Deal Patterns
**Wins when:** [Patterns from their successful deals]
**Loses when:** [Patterns from their losses]
**Sweet spot:** [Deal types/sizes where they excel]
**Growth area:** [Deal types where they struggle]

### Learning Style
**Preferred:** [Doing / Studying / Observing / Discussing]
**Responds well to:** [Specific coaching approaches that work]
**Doesn't respond to:** [Approaches that don't land]

### Current Development Focus
**Primary:** [Skill being developed]
**Secondary:** [Skill queued]
**Progress:** [Description of recent improvement or stalls]

### Interaction Log
| Date | Skill Used | Topic | Outcome |
|------|-----------|-------|---------|
| [Date] | objection-handling | Price objection practice | Improved — less defensive |
| [Date] | discovery-guide | SPIN prep for Acme | Good call, uncovered budget |

Adaptation Rules

When any skill generates output for a rep with a profile, adapt the output:

For New Reps (< 90 days, ramp stage)

•Always include the full framework explanation (don't assume they know SPIN, MEDDIC, etc.)
•Provide templates they can follow word-for-word
•Add context for why each step matters
•Include checklists so nothing gets missed
•Tone: Supportive, educational, encouraging

For Mid-Level Reps (90 days - 2 years)

•Skip basics — reference frameworks by name without re-explaining
•Focus on their weak spots — if they score 2/5 on negotiation, weight content toward that
•Include nuance — edge cases, when to break the rules, situational judgment
•Challenge them — "What would you do differently if the champion left?"
•Tone: Collaborative, coaching-oriented

For Senior Reps (2+ years, top performers)

•Be brief — they don't need hand-holding
•Provide intel, not instructions — competitive data, deal insights, customer patterns
•Focus on advanced scenarios — multi-threaded deals, executive selling, complex negotiations
•Ask their opinion — "You've seen this before — what's worked?"
•Tone: Peer, strategic partner

For Managers

•Data-driven — metrics, trends, comparisons
•Team-level patterns — not just individual deals
•Coaching-ready — frame insights as coaching conversation starters
•Action-oriented — "Here's what to focus on in your 1:1s this week"
•Tone: Strategic, analytical

Building a Profile

From Scratch

When you don't have a profile yet:

•Ask role and experience level
•Ask about recent deals (2-3 wins and losses)
•Ask what they feel strongest/weakest at
•Ask their manager for input (if available)
•Create initial profile in memory/team.md

From Interactions

Every time a rep uses the plugin:

•Note what they asked for help with (signals a gap)
•Note what they didn't need help with (signals strength)
•After coaching sessions, update skill scores
•After deal outcomes, update deal patterns
•Track improvement trends over time

From Data (Automatic — Highest Quality)

CRM Data Pull

Check if you have access to CRM tools (look for tools containing search_crm_objects, get_crm_objects, or similar).

If CRM tools ARE available:

•
Pull rep's deals. Search deals filtered by hubspot_owner_id.
- •Properties: dealname, amount, dealstage, closedate, createdate, pipeline, dealtype, hs_deal_stage_probability
- •Separate won, lost, and open deals
•
Calculate performance metrics:
- •Win rate = Closed Won / (Closed Won + Closed Lost)
- •Avg deal size = Mean of amount across won deals
- •Avg cycle length = Mean days from createdate to closedate for won deals
- •Pipeline coverage = Open pipeline value / quota (ask user for quota if needed)
•
Compare to team averages. Pull all reps' deals and compute team-level metrics.
- •Flag where this rep is significantly above or below average
•
Identify stage-specific patterns:
- •Where do their deals stall? (avg days in each stage vs. team)
- •Where do they lose? (stage distribution of lost deals vs. team)
- •Deal types they excel at vs. struggle with
•Map rep name. Use search_owners to translate owner ID.

Gong Data Pull

Check if you have access to Gong tools (look for tools prefixed with gong_).

If Gong tools ARE available:

•
Pull call stats. Use gong_get_call_stats for the rep's recent period.
- •Total calls, average duration, average questions per call
•
Analyze call patterns. Use gong_search_calls_by_participant with the rep's email, then gong_get_call_details on 5-10 calls:
- •Average talk-to-listen ratio → maps to Discovery & Questioning skill
- •Average questions per call → Discovery skill indicator
- •Competitor mention frequency → Competitive handling skill
- •Next steps confirmation rate → Closing discipline
- •Topic distribution → Where they spend conversation time
•
Build data-driven skill scores:
- •Talk ratio > 55% → Lower Discovery score
- •< 5 questions per call → Lower Discovery score
- •No next steps in > 30% of calls → Lower Closing score
- •Low competitor mention handling → Lower Objection Handling score

Sales Intelligence Data Pull (ZoomInfo / Clay / LinkedIn)

ZoomInfo (check for tools prefixed with zoominfo_):

•
Validate industry expertise. Use zoominfo_search_company on the rep's won deal companies.
- •Which industries does this rep win in most? → vertical specialization signal
- •What company sizes do they close? → segment fit indicator

Clay (check for tools prefixed with clay_):

•
Enrich deal context. Use clay_enrich_company on rep's recent deals.
- •Were their wins at companies with buying signals? → luck vs skill indicator

LinkedIn (check for tools prefixed with linkedin_):

•
Get rep's LinkedIn profile. Use linkedin_get_profile if rep's LinkedIn URL is known.
- •Career history reveals experience level and domain expertise
- •Endorsements/skills signal areas of strength
- •Previous companies/industries → domain knowledge map

Auto-Generated Profile

When tools are connected, auto-generate the profile without asking the user:

"I built [Rep Name]'s profile from data: [X]% win rate (team avg: [Y]%), $[X] avg deal size, [X]-day cycle. Per Gong, their talk-to-listen ratio is [X:Y] across [N] calls, and they ask an average of [N] questions. Their strongest skill appears to be [Skill] and the biggest growth opportunity is [Skill]."

Profile Dashboard

When a manager or rep wants to see the profile:

markdown

# Rep Profile: [Name]

**Performance Snapshot**
| Metric | This Quarter | Last Quarter | Team Avg |
|--------|-------------|-------------|----------|
| Quota Attainment | [X]% | [X]% | [X]% |
| Win Rate | [X]% | [X]% | [X]% |
| Avg Deal Size | $[X] | $[X] | $[X] |
| Avg Cycle Length | [X] days | [X] days | [X] days |

**Skill Map** [Visual representation of strengths and gaps]

**Top Priority:** [The one skill that would most impact their numbers]

**Recommended This Week:**
1. [Specific practice exercise using plugin skill]
2. [Call to review for coaching moment]
3. [Content to study]

Related Skills

•sales-coaching → Updates skill scores after coaching sessions
•win-loss-analysis → Updates deal patterns after post-mortems
•All skills → Read rep profile to personalize output depth and focus
•gtm-memory → Rep profiles are stored in the team.md memory file