Seller Playbook Builder
Resolve every Phoenix ID for a seller once — and make every account research run that follows instant.
All 7 competitor vendorIds resolved — with displacement angles and ICP signal products
Competitors mapped. Intent topics pre-loaded.
Signal products catalogued for ICP detection.
| What's resolved | Downstream benefit |
|---|---|
| 7 competitor productIds | FAI installed-base detection at any prospect |
| 8 intent topic IDs | Skip list_intent_topics on every brief run |
| 6 ICP signal products | Detect ecosystem fit via company_technographic |
Overview
Before your reps can run account research for a seller, someone has to resolve all the Phoenix IDs — which vendors compete, which categories to search, which products signal ICP fit. This workflow does that once and saves it. Give it a seller name; get back a ready-to-use seller-context document with resolved taxonomy, competitor displacement angles, 6-8 intent topic IDs, and a 'looking for signals' product list — so every subsequent research run for that seller is instant.
Use cases
Arm your team before they run their first brief
Before your AEs run Account Research Briefs for a seller's territory, someone has to resolve all the Phoenix IDs — which vendors compete, which categories to search, which products in a prospect's stack signal ICP fit. This workflow does that resolution work once, up front. The output is a seller-context document your whole team can point their brief runs at — so the first rep who hits it doesn't spend 20 minutes on `get_vendor_information` calls that every other rep will duplicate.
Build ICP signal detection for a new territory
When you onboard a new seller or expand into a new vertical, the hardest part isn't writing the brief — it's knowing what to look for. The 'Looking for Signals' section identifies 5–8 products that, if detected in a prospect's stack via `company_technographic`, mean the prospect probably has the use case and budget maturity you're targeting. One workflow run gives your seller a tuned ICP detector they can apply to every account in the territory.
View workflow prompt
# Seller Playbook Builder
## Parameters
- `{{seller_company}}` *(required)* — The seller to build the playbook for (company name). Example: `Meltwater`
- `{{vertical_overlay}}` *(optional)* — Optional vertical focus (e.g. "BFSI" for Banking/Financial Services/Insurance). Example: `BFSI`
## Purpose
Build a seller-context document for {{seller_company}}. Pre-resolve all Phoenix IDs (vendorIds, productIds, categoryIds, intent topicIds) and build ICP signal context so downstream account research runs are instant. Cite every ID to its source tool. If {{vertical_overlay}} is provided, apply it where relevant throughout the document.
## Process
1. **Seller profile** — `get_vendor_information` for {{seller_company}}. Capture vendorId, productIds, categoryIds. Supplement with 2 parallel `web_search` calls: (a) "{{seller_company}} overview headquarters employees founded revenue" and (b) "{{seller_company}} Gartner IDC Forrester recognition awards 2025 2026".
2. **Competitor discovery** — `web_search`: '"{{seller_company}}" top competitors alternatives 2025 2026'. Extract 5–7 names. `get_vendor_information` for each in parallel — capture vendorId + productIds overlapping the seller's service area. For each: "where they win" + seller displacement angle.
3. **Category validation** — `list_product_categories` for each category from step 1. Use exact names and IDs verbatim.
4. **Intent topics** — `list_intent_topics` with 6–8 queries: primary category name, adjacent category, buyer use-case terms, value outcome terms, platform/tech terms. Capture topicId + exact name + category.
5. **Signal products** — 5–8 complementary products whose presence signals ICP fit (NOT competitors — ecosystem signals: a CRM = mature GTM, a BI tool = data-driven culture). `get_vendor_information` for each in parallel.
6. **Pricing** — `web_search`: '"{{seller_company}}" pricing ACV site:vendr.com OR site:g2.com OR site:trustradius.com'. Extract ACV ranges by deal size.
## Output Format
Produce a Markdown document with these sections in order:
- `## ABOUT THE SELLER` — company overview, quick facts (HQ, founded, employees, revenue), key products
- `## SERVICE AREAS` — table: Service Area | Description | Typical ACV Range
- `## ICP` — size thresholds, 6–10 target industries, anti-ICP (3–5 bullets), pain points
- `## TARGET CATEGORIES` — validated categoryIds from step 3 (name | id | source)
- `## COMPETITIVE LANDSCAPE` — per competitor: product, vendorId, productId, "where they win", displacement angle
- `## LOOKING FOR SIGNALS` — table: Product | Vendor | vendorId | productId | Why it signals ICP fit
- `## FAI PRODUCT IDS` — seller products array + competitor products array, labeled separately
- `## INTENT TOPIC IDS` — table: Topic Name | Topic ID | Category
- `## BUYER PERSONAS` — table: Service Area | Primary Titles | Secondary Titles
- `## SIZING BENCHMARKS` — table: Deal Type | ACV Range | Notes
- `## DISCOVERY QUESTION TEMPLATES` — 5–7 questions; at least 3 with `{{finding:}}` placeholders tied to tech signals
- `## VERTICAL OVERLAY` — {{vertical_overlay}}-specific ICP and title adjustments. Omit this section entirely if {{vertical_overlay}} is not provided.
- `## RESOLUTION SUMMARY` — resolved vs. unresolved counts per ID type
## Quality Checklist
- Every vendorId / productId / topicId cites the tool that returned it + "resolved this run"
- No IDs fabricated — all UNRESOLVED items flagged with a reason
- Signal products named with why each signals ICP fit, not just what the product is
- Discovery questions include ≥3 with `{{finding:}}` placeholders referencing tech-stack or competitor signals
- ACV data cites source URL + access date
- Competitive landscape includes a displacement angle for every competitor, not just a name list