Rupesh N. Chavan Collate.io · Process

The full process

The research, personas and flows behind Collate.io. The case study covers the decisions; this is the work underneath them.

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02 · User Research

User Persona & Goals

Three C-suite and senior enterprise stakeholders who define how Collate is evaluated, adopted, and scaled. Each bringing completely different success criteria and risk tolerances to the platform.

👤
Aditya Shah
Chief Data Officer, 46
Goals
  • Company-wide data strategy visibility and oversight
  • AI-powered insights to drive executive decision-making
  • Regulatory compliance across all data assets
Pain Points
  • Siloed data teams with no unified health dashboard
  • No executive-level view of data governance posture
🧑
Preethi Ramesh
Enterprise Data Architect, 35
Goals
  • Manage data contracts and govern data products
  • Integrate with existing enterprise systems without additional IT configuration
  • Build scalable, future-proof data architecture
Pain Points
  • Complex migration from legacy governance tools
  • Vendor lock-in limiting architectural flexibility
👩
Sameer Mathur
VP Engineering, 40
Goals
  • SLA-backed data platform with measurable reliability
  • Scalable infrastructure that grows with the business
  • Cost governance and clear ROI visibility
Pain Points
  • High operational overhead from current tooling
  • Unclear ROI metrics make budget justification difficult
03 · Business Challenges

Core Challenges

CHALLENGE 01
Enterprise-Scale Governance Complexity
At enterprise scale, data governance involves thousands of assets, hundreds of policies, and dozens of regulatory frameworks. All requiring simultaneous enforcement without creating workflow paralysis.
CHALLENGE 02
AI Integration with Existing Stacks
Collate's AI capabilities needed to augment existing enterprise tools rather than replace them. Requiring deep integration architecture that fit into established workflows without disruption.
CHALLENGE 03
Proving ROI to C-Suite
Abstract data governance value needed concrete financial framing. C-suite buyers required measurable ROI evidence before committing enterprise-level budgets. The brand had to do this work before the sales call.
CHALLENGE 04
Multi-Cloud Data Orchestration
Modern enterprises run data across AWS, Azure, GCP, and on-premise simultaneously. Collate needed to unify governance across all environments without requiring a single cloud migration commitment.
04 · Secondary Research

Market Insights

FINDING 01
87%
Enterprise Data Initiatives Stall on Governance

87% of enterprise data transformation initiatives stall or fail due to governance gaps, not technical limitations. Governance is the primary execution bottleneck in data strategy.

FINDING 02
60%
AI Reduces Data Incident Resolution Time

AI-augmented data catalogs reduce data incident resolution time by 60%. A measurable operational ROI that translates directly into executive-level business value justification.

FINDING 03
$3.1M
Annual Cost of Poor Data Quality

The average enterprise loses $3.1 million annually to poor data quality. Through bad decisions, regulatory fines, and operational inefficiency. This is the problem Collate is positioned to solve at scale.

07 · User Flow

The Journey

01
Onboard Enterprise
Dedicated onboarding team connects enterprise SSO, configures RBAC, and maps existing data estate
02
Connect Data Estate
All data sources, warehouses, lakes, BI tools, connected via native connectors across cloud and on-premise
03
Define Governance Policies
Data stewards configure policies, data contracts, and quality thresholds through a visual policy builder
04
Monitor Quality
Automated quality checks run continuously with real-time alerts for breaches and SLA violations
05
AI-powered Insights
AI surfaces anomalies, usage patterns, and governance gaps in a CDO-level executive dashboard
06
Generate Compliance Reports
One-click automated compliance reports for GDPR, HIPAA, SOC 2, and regulatory audit submissions
08 · Toolkits

Tools & Workflow

Tools and methods used throughout the design process, from stakeholder interviews and brand strategy through to interactive prototypes and final production handoff.

🎨FigmaUI Design
🗺️MiroJourney Mapping
📋NotionDocumentation
🧪MazeUsability Testing
🎬PrinciplePrototyping
Design Process

From strategy
to shipped product

A five-phase process that began with stakeholder interviews across the C-suite and engineering teams, and ended with a production-ready design system and website that served both audiences with precision.

01
Stakeholder Interviews
C-suite and data engineering interviews. Dual persona mapping. Buyer journey documentation across both audience types. Competitive audit of 12 enterprise data platforms.
02
Messaging Architecture
Developed a layered messaging hierarchy, single overarching brand statement, distinct value props per audience, and a trust-building sequence that addressed both ROI buyers and technical evaluators.
03
Information Hierarchy
Designed page architecture and content flow. Hero for top-of-funnel awareness, trust architecture above the fold, feature depth below. Navigation designed to serve both audience entry points without compromise.
04
Visual Design
Indigo AI palette. Intelligent grid aesthetic. Space Grotesk + subtle monospace pairing. Sophisticated without science-fiction clichés. Built for credibility, not spectacle.
05
Interactive Showcases
Feature visualization through interactive UI demos, not static screenshots. Compliance badge architecture. Customer proof sequencing. Technical depth sections for engineer evaluation without alienating executives.
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