Build a Proof-Point Library (Stats, Cases, Awards)

You are a sales enablement librarian for a digital marketing agency. You convert messy raw proof (case studies, screenshots, dashboards, awards, emails, quotes) into a structured library reps can search in 10 seconds.

Agency: [AGENCY_NAME] — [SERVICES]
Raw proof inputs (paste everything you have): [RAW_PROOF_INPUTS]
ICPs we sell to: [ICP_LIST]
Most common sales objections we face: [OBJECTIONS]

Convert the raw inputs into a structured proof-point library. For each proof point, extract: (1) one-sentence proof statement with the number, (2) client name (or "undisclosed" if NDA), (3) ICP segment tag, (4) service line tag, (5) objection it answers, (6) where it's best used (cold email, proposal, landing page, sales call, deck). Group the final library by service line, then by ICP within each.

- Every proof point must include a verifiable number or named entity — drop anything vague
- Tag at least one objection per proof point so reps can pull by objection
- If a stat is older than 18 months, flag it with [STALE] so it gets refreshed
- No marketing language — just the fact, the source, the use
- Cap each proof statement at 25 words

## [Service Line 1]

### [ICP Segment A]
- **Proof:** [statement] | **Client:** [name] | **Objection:** [...] | **Best for:** [channel]
- ...

### [ICP Segment B]
- ...

## [Service Line 2]
...

At the bottom, list any gaps: "You have no proof for [ICP] x [Service] — collect this first."

• [AGENCY_NAME] — Your agency
• [SERVICES] — Your service lines
• [RAW_PROOF_INPUTS] — Dump everything: case study drafts, client quotes, dashboard stats, awards, press mentions, testimonials, retention numbers
• [ICP_LIST] — The ICP segments you sell into
• [OBJECTIONS] — Top 5-10 objections reps hear (e.g., 'price', 'timeline', 'team seniority')

Agency: Northway Paid Media. Services: Google Ads, Meta Ads, TikTok Ads. Raw inputs: 'Branch Basics — CAC down 31% in 4 mo, DTC supplements, Q1 2025'; 'Vendr — SQLs up 2.1x in a quarter, B2B SaaS, Q4 2024'; 'Won 2024 Google Premier Partner Award'; 'Quote from Jenny at Olipop: They paid for themselves in week 6'; '95% client retention 2024'. ICPs: DTC $3M-$15M, B2B SaaS Series A-B. Objections: price, timeline, attribution skepticism, team seniority.

## Google Ads & Meta Ads

### DTC Supplements / Beverage $3M-$15M
- **Proof:** Branch Basics blended CAC down 31% in 4 months. | **Client:** Branch Basics | **Objection:** attribution skepticism, timeline | **Best for:** sales call, proposal
- **Proof:** Olipop paid for the engagement back inside 6 weeks (founder quote on file). | **Client:** Olipop | **Objection:** price, timeline | **Best for:** cold email, landing page

### B2B SaaS Series A-B
- **Proof:** Vendr SQLs up 2.1x in one quarter. | **Client:** Vendr | **Objection:** attribution skepticism, MQL-vs-SQL | **Best for:** sales call, deck

## Cross-Agency Credibility
- **Proof:** 2024 Google Premier Partner (top 3% of US partners). | **Client:** N/A | **Objection:** team seniority | **Best for:** proposal, landing page footer
- **Proof:** 95% client retention across 2024 (book size 42 accounts). | **Client:** N/A | **Objection:** team seniority, partnership longevity | **Best for:** proposal, sales call

**Gaps:**
- No proof for B2B SaaS x Meta Ads — collect from your next 2 SaaS engagements.
- No proof for TikTok Ads at all — flag for delivery team to pull a case study.

• Store the library in Notion or Coda with the tags as filterable properties — reps will actually use it.
• Run this quarterly with delivery's input so wins from the last 90 days don't get lost.
• Use the 'Gaps' section as a roadmap for what to ask delivery to document next.