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SERVICES_CATALOG_AUDIT_README_2026-02

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Services Catalog Audit: Mapping to Catalog Categories

Source: Notion export (Services Catalog CSV). Output: SERVICES_CATALOG_AUDIT_MAPPED_2026-02.csv with same columns plus Catalog Category, Live Ready, and Gaps.
Rule: If we cannot answer every question in the table (all interrogative columns filled), the service is not live. Use Live Ready and Gaps to decide what to fix before promoting.

How the table is used

  • Same columns as the original CSV; two columns added:

  • Interrogative columns that must be answerable for a service to be Live:

    • Primary Outcome
    • Pricing Model
    • What are the key steps in how we deliver this (from start to finish)?
    • What does the client actually walk away with?
    • What problem does this service actually solve?
    • When would you not recommend it?
    • Who is this service really for (title, company size, or situation)?
    • Why does that problem matter for our clients right now?
    • Can you share one real example or story of this service in action? (or Examples)

Catalog categories (canonical — do not change without careful review)

All services in the CSV roll up into these categories. Source: PRICING_AUDIT_OFFERS_AND_MATRIX_2026-02.md §1.4.

Catalog Category
1. Data Audit & Tracking Validation (Marketing, Product, dbt)
2. Data Tool Implementation & Full Data Stack (single layer or full)
3. AI Copilot Integration Sprint & Custom Context Graphs
4. Full Data Platform Assessment & Implementation
8. Tech-Enabled Platform Build
9. Full-Service Data Management
10. Dedicated Resource Retainers
Training & Enablement

Summary of audit results

  • Live Ready = Y (3): Edge to Activation Service, Digital Ads Visibility Audit (added row—named offer not in source CSV), dbt audit. All have full fill from our named offers and catalog.
  • Marked Live in source but Live Ready = N (5): Product Analytics, Customer Data Optimization (CDP Sprint), Contextual Inflow Automation, AI Literacy & Training, Product Analytics Sprint. Gaps listed in Gaps column; until filled, treat as not live per the rule.
  • In Development / Not started: All set to Live Ready = N with Gaps noted. Use Gaps to prioritize which columns to fill first (e.g. Key steps, Client walk away, What problem, Who for, When not recommend, Why now).

Not started rows (decisions applied)

Three rows were removed (unnamed placeholder; CRO Sprint merged into CDP Sprint; AI Strategy Workshop merged into Executive AI Enablement). Four kept and slotted into existing categories: Execution SOP → Training & Enablement; Retail Analytics → Product Analytics Platform Build; Customer Experience AI → AI Copilot; Lifecycle Strategy Audit → Product Analytics (Analysis Layer). See NOT_STARTED_ROWS_DECISIONS_2026-02.md. No new service categories; all services roll up into the categories in this README.

Next steps

  1. For each row with Live Ready = N: Fill the missing cells listed in Gaps (and any other empty interrogative column). Re-run the rule: if all required columns are filled, set Live Ready = Y and Status = Live where appropriate.
  2. Sync with Notion: Once rows are complete, update the source Notion Services Catalog so Status and content match this audit. CSV stays the source of truth; easily transferable to CRM, Notion, or other tools.

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