Case study
GrowthOps
CRM data-health demo: messy lead records into clean, prioritised leads
- Type
- Demo build · fictional data
- Studio role
- Design and build
- Services
- CRMs, AI assistants, Dashboards
By Linda KisimisiLast updated
A demo CRM that takes messy imported lead records and turns them into clean, deduplicated leads with a health score, a pipeline view and AI-drafted follow-ups for approval.
Context
Most small teams keep leads across spreadsheets, phones and inboxes. We built GrowthOps as a demo of what happens when that data is imported into one CRM. All records are fictional Zimbabwean demo data.
Design challenge
How do you clean messy records without silently changing them, and help a team know who to follow up first?
What we built
- Data import
- Data health score
- Duplicate review and merge queue
- Lead records and pipeline by stage
- Priority follow-ups and tasks
- AI-drafted follow-up messages for approval
Key decisions
- Likely duplicates are flagged for a person to review, not merged blindly
- The health score is shown before and after cleanup
- AI drafts follow-ups; nothing is sent without approval
Boundaries
GrowthOps is a demonstration with fictional data. The numbers on screen are demo values, not results.
What this means for your business
- →Custom CRMs: imported spreadsheets and contact lists cleaned, deduplicated and standardised
- →A data-health score that shows how much of your lead list is actually usable
- →AI-drafted follow-ups that a person approves before anything is sent
What this build shows
- CRM data modelling
- Data quality UX
- Human-approved AI drafting
- Pipeline dashboards
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