Build a Personalization Variable Library

You are the RevOps lead at a digital marketing agency. You build the libraries that make every SDR sound 30% smarter on day one.

Agency: [AGENCY_NAME] — [SERVICES]
Raw inputs (paste anything relevant — case studies, sales call transcripts, ICP doc, common objections, vertical notes, tech stack observations):
[RAW_INPUTS]
Verticals served: [VERTICALS]

Extract and organize a structured personalization library that the team and future AI prompts can pull from. Group by snippet type. Each entry must be self-contained, verifiable, and tagged.

- Only include snippets traceable to [RAW_INPUTS]. Never invent stats, client names, or quotes.
- Each snippet must be tagged with: vertical(s) it applies to, snippet type (proof_point, observation, objection_handler, trigger_event, common_pain), and source line from [RAW_INPUTS].
- Proof points must include the metric + timeframe + client (or anonymized descriptor if client is confidential).
- Mark anything anonymized or sensitive with [INTERNAL ONLY].
- If [RAW_INPUTS] is thin in a category, output "GAP: need more raw material for [category]" rather than padding.

# Personalization Variable Library — [AGENCY_NAME]

## Proof Points
- ID: PP-001 | Vertical: [v] | [metric + timeframe + client] | Source: "[source line]"
...

## Trigger Events
- ID: TE-001 | Vertical: [v] | Trigger: [e.g., hired a CMO] | Why it matters: [1 line] | Source: "..."

## Common Pains
- ID: CP-001 | Vertical: [v] | Pain: [...] | Language buyers use: [...] | Source: "..."

## Objection Handlers
- ID: OH-001 | Objection: [...] | Response: [...] | Source: "..."

## Observations (vertical-specific, non-proof)
- ID: OB-001 | Vertical: [v] | Observation: [...] | Source: "..."

## GAPS
- [list of categories where raw inputs were too thin]

• [AGENCY_NAME] — Your agency
• [SERVICES] — Services
• [RAW_INPUTS] — Paste of case studies, sales call notes, ICP docs, win/loss notes, vertical research
• [VERTICALS] — Comma-separated list of verticals you target

AGENCY_NAME: Northpoint Digital
SERVICES: SEO + content
VERTICALS: B2B SaaS, DTC ecommerce
RAW_INPUTS:
- Glowbar (DTC skincare, Shopify) — +112% organic sessions in 5 months from collection-page SEO.
- Latchpad (B2B SaaS) — +34% organic in 6 months.
- Sales call w/ Priya at Quotient HR: "we're skeptical SEO can move fast enough".
- Common DTC pain: brands burn $30k+ on agencies that publish blog posts no one searches for.

# Personalization Variable Library — Northpoint Digital

## Proof Points
- ID: PP-001 | Vertical: DTC ecommerce | +112% organic sessions in 5 months — Glowbar (Shopify skincare brand) | Source: "Glowbar (DTC skincare, Shopify) — +112% organic sessions in 5 months from collection-page SEO"
- ID: PP-002 | Vertical: B2B SaaS | +34% organic in 6 months — Latchpad | Source: "Latchpad (B2B SaaS) — +34% organic in 6 months"

## Trigger Events
- GAP: need more raw material for trigger_events

## Common Pains
- ID: CP-001 | Vertical: DTC ecommerce | Pain: burning $30k+ on blog posts no one searches for | Language: "agencies that publish blog posts no one searches for" | Source: raw_inputs note 4

## Objection Handlers
- ID: OH-001 | Objection: "SEO can't move fast enough" | Response: cite PP-001 — Glowbar moved in 5 months on collection-page work, not blog posts | Source: "sales call w/ Priya at Quotient HR"

## Observations
- GAP: need more raw material for observations

## GAPS
- trigger_events
- observations

• Re-run this quarterly — your proof points drift and your objections evolve.
• Tag each snippet with an ID so other prompts in your stack can reference them (e.g., "use PP-001 if vertical=DTC").
• The GAPS section is the most valuable output — it tells you what to ask reps for at the next pipeline review.