Garbage In, Missed Deals Out: Data Quality for AI Qualification in Zoho

TL;DR

AI can not rescue messy data. Get enrichment, normalization, and consent right first. You will convert more with simpler models on clean data than complex models on noise.

Hygiene Must-Haves

• Normalize country/state, job titles, and industries
• Validate emails and phone numbers; append region and time zone
• Deduplicate on email + domain; avoid duplicate runs
• Capture consent per channel with timestamps and source

Ethical, Useful Enrichment

• Resolve company by domain; add size, industry, and tech signals
• Maintain an enrichment confidence score; never over-assert
• Cache enrichment for 24h to control cost

Zoho Fields to Standardize

• Enrichment Confidence (0–1)
• Normalized Job Function (Ops, Finance, IT, etc.)
• Region and Local Time Window
• Consent Status per channel with versioned policy

AI Qualification That Trusts the Data

• Short reasoning string lists top 3 evidence points
• Idempotent updates: never overwrite human notes
• Audit log references snapshot IDs and model version

Ops Guardrails

• Reject outbound without consent and outside quiet hours
• Backfill missing fields weekly; create views for exceptions
• Add tests for normalization functions (titles, countries)

Conversion Metrics to Watch

• Acceptance rate by enrichment confidence bucket
• Speed to first touch for normalized vs messy records
• Lift in qualified meetings after hygiene rollout

10-Day Implementation Plan

1. Define canonical picklists and normalization rules
2. Build enrichment service + caching; add consent fields
3. Backfill last 90 days; measure improvement
4. Turn on qualification with guardrails

Takeaway

Reliable AI starts with reliable data. Standardize and enrich ethically inside Zoho CRM to unlock consistent, compounding conversion gains.