Clean, de‑duplicated data
across Contacts, Companies, Deals, and custom objects
Standardized properties & naming
(lifecycle, lead status, pipeline stages, playbooks)
Process automation that mirrors reality
(clear triggers, owners, SLAs, error handling)
Reliable tracking & attribution
(UTM hygiene, ad syncs, offline conversions)
Governance & permissions
(least privilege access, audit trail, data retention)
Documented knowledge
that AI can use (playbooks, KB, meeting notes, ticket fields)
Common signs you’re not AI‑ready
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Multiple or conflicting lifecycle definitions (MQL/SQL) across teams
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10%+ duplicate rate or mismatched associations (Contacts ↔ Companies ↔ Deals)
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High % of empty required fields; inconsistent picklist values
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Unnamed or orphaned workflows, unclear triggers, no rollback logic
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UTM parameters vary per campaign; attribution reports don’t match ad platforms
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Admins with broad permissions; no data‑retention policy; missing consent records
What we review
- Duplicates by email/phone, merge rules, association integrity
- Property audit: usage %, null rates, validation rules, option normalization
- Company domain logic; parent/child hierarchies; record ownership
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Lifecycle + Lead Status mapping; definition alignment with Sales/CS
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Pipeline stages: entry/exit criteria, required fields, reasons
-
Naming conventions for lists, workflows, forms, and assets
- Trigger hygiene, concurrency risks, suppressions, failure notifications
- Sequences & handoffs; task queues; SLAs for MQLs & Tickets
- Data normalization workflows (capitalization, phone formats, country/state)
-
UTM conventions; default values; URL builders; ad account syncs
-
Offline conversions; meeting sources; call tracking; source deduping
-
Cookie consent + marketing contacts strategy
- Meeting Notetaker & call transcripts; knowledge sources for assistants
- Chatbot/Inbox setup; routing; identity capture before answers
- Predictive scoring prerequisites (volume, consistency, Enterprise limits)
- Permission sets & teams; super admin count; audit logs
- PII access, masking, and data retention rules
- Incident playbook: rollbacks, backup exports, change approvals
What we review
- Duplicates by email/phone, merge rules, association integrity
- Property audit: usage %, null rates, validation rules, option normalization
- Company domain logic; parent/child hierarchies; record ownership
-
Lifecycle + Lead Status mapping; definition alignment with Sales/CS
-
Pipeline stages: entry/exit criteria, required fields, reasons
-
Naming conventions for lists, workflows, forms, and assets
- Trigger hygiene, concurrency risks, suppressions, failure notifications
- Sequences & handoffs; task queues; SLAs for MQLs & Tickets
- Data normalization workflows (capitalization, phone formats, country/state)
-
UTM conventions; default values; URL builders; ad account syncs
-
Offline conversions; meeting sources; call tracking; source deduping
-
Cookie consent + marketing contacts strategy
- Meeting Notetaker & call transcripts; knowledge sources for assistants
- Chatbot/Inbox setup; routing; identity capture before answers
- Predictive scoring prerequisites (volume, consistency, Enterprise limits)
- Permission sets & teams; super admin count; audit logs
- PII access, masking, and data retention rules
- Incident playbook: rollbacks, backup exports, change approvals
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How it works
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Fit call (30 min). Goals, constraints, access needs.
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Discovery form. Business model, KPIs, lead flows, tool stack.
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Portal deep‑dive. Read‑only user + limited exports for analysis.
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Report & Scorecard. Findings, risks, and prioritized backlog.
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Readout workshop. Walkthrough with stakeholders and Q&A.
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