Partner Account Mapping — SOP Summary
Owner: Partnerships / Sales | Version: 2.0 | February 2026
1. Overview
Unified system: SOP + Spreadsheet Template + Cursor Automation
- Process (this SOP) — Step-by-step from intake to partner meeting
- Spreadsheet —
partner_account_mapping_template.xlsx(7 tabs, INDEX/MATCH, Google Sheets compatible) - Cursor Automation —
partner_account_mapping_automation.py+config.yaml; drop CSV in, get scored mapped list out
All three share the same scoring logic, same 12 match layers, and same tier thresholds. config.yaml is the single source of truth for scoring weights.
Trigger: New partner AE relationship, new account list received, or quarterly refresh.
Output: Prioritized, scored, tiered account mapping table ready for partner review meeting.
2. Prerequisites
- Partner AE account list (CSV or Excel)
- Your account list from CRM
- Optional: active campaigns, case study index, contacts
- System files: template, script, config.yaml, cursor_automation_guide.md
- Dependencies:
pip install -r requirements.txt(pandas, openpyxl, pyyaml, requests, fuzzywuzzy, python-Levenshtein)
3. Folder Structure (Automation)
partner-mapping/
├── input/ ← Partner CSVs
├── my-data/ ← my_accounts.csv, my_contacts.csv, my_case_studies.csv, my_campaigns.csv
├── output/ ← MAPPED_<name>.xlsx (7 sheets)
├── partner_account_mapping_automation.py
├── config.yaml
└── enrich_partner_list_apollo.py (optional, when domain column present)
4. 7-Tab Workbook
| Tab | Purpose |
|---|---|
| 1 Partner List | Raw input from partner AE |
| 2 My Accounts | Your book of business (CRM export) |
| 3 My Case Studies | Case study index by industry |
| 4 My Campaigns | Active/planned campaigns |
| 5 My Contacts | Relationships for warm path |
| 6 CONFIG | Scoring weights, geos, ICP, tier thresholds (= config.yaml) |
| 7 MAPPED OUTPUT | Scored, tiered accounts with actions |
Script output is a 7-sheet workbook matching this structure.
5. Six-Step Process
- Ingest & standardize — Partner list in input/; CRM export in my-data/. Script auto-normalizes names, industry, city.
- Run 12-layer matching —
python partner_account_mapping_automation.py --partner-list input/<file>.csv - Score, tier & generate actions — Automatic. Tier 1: 8+; Tier 2: 5–7; Tier 3: 2–4; Tier 4: 0–1.
- Enrich with AI (Step 4) —
--enrich→ openoutput/ENRICH_TASKS.mdin Cursor → paste prompt from enrichment-agent-prompt.md (web search + optional Apollo MCP subagent) → fill Context Brief with 8 signal types →--merge-enrichment. - Partner meeting prep — Sort by score; talking points per Tier 1; case studies; follow-up cadence.
- Post-meeting — Update mapping, log Tier 1 in CRM, share case studies, schedule next sync.
6. Step 4 Signal Types (Context Brief)
- Leadership changes
- Industry news
- Funding / growth
- Hiring signals
- Earnings / financial
- Tech announcements
- Event presence
- Competitive moves
7. CONFIG Reference
Edit config.yaml (and Tab 6 in spreadsheet if using both). Scoring weights, tier thresholds (tier_1: 8, tier_2: 5, tier_3: 2), geographies, ICP (employee_min, employee_max, industries).
8. Files in This System
| File | Purpose |
|---|---|
| SOP (this summary) | Process playbook |
| partner_account_mapping_template.xlsx | 7-tab spreadsheet |
| partner_account_mapping_automation.py | Automation script |
| config.yaml | Scoring, tiers, geos, ICP |
| cursor_automation_guide.md | CSV specs, 12 layers, prompts |
| enrich_partner_list_apollo.py | Optional Apollo enrichment (domain column) |
| enrichment-agent-prompt.md | Prompt for Cursor Step 4 (web search + Apollo subagent) |
See HOW_TO_RUN.md for step-by-step run instructions and cursor_automation_guide.md for full CSV specs and match layers.