The Data Bottleneck No One Talks About (Until It Hits the Boardroom)
How fragmented customer data stalls growth-and the playbook that turned chaos into 10X ROI.
When I joined the data leadership team at a major fintech, our biggest challenge wasn’t a lack of data—it was the opposite. Customer data was everywhere and nowhere, fragmented across disparate pods and tables. The journey from that chaos to real-time activation was complex, but the results were transformative, and the blueprint is one I’ve seen work across both financial services and any CPG or retail organization.
The Silos That Slowed Us Down
Our customer information was spread across at least five major systems: Marketing systems and MarTech, product analytics tables, CRM, Datawarehouse, and various engagement platforms. Each team—marketing, product, risk, and data science—was looking at their own slice of the customer, resulting in inconsistent profiles, conflicting priorities, and disconnected personalization efforts.
Marketing would target a user based on campaign clicks, Lifecycle PODS will send 5 differnt email campaigns on the same daay, while the risk team flagged the same user for a behavior product analytics hadn’t even seen yet. The customer journey was a broken mirror, reflecting a different reality for every team. The cost was clear: high acquisition costs, frustrated users, and missed revenue opportunities.
Key Bottlenecks and the Buy-In Needed
The major bottleneck was both technical and cultural.
Technical : Our identity resolution was weak. We couldn’t confidently stitch together a user’s journey from anonymous web visit to logged-in app activity without creating duplicates or privacy risks. We also had a challenge of more than one legal entity, so combining identity was a major bottleneck as the data needed to be unified in a consistent manner.
Cultural : Teams were protective of their data and tools. There was no shared playbook or single source of truth, so marketing and product couldn’t fully trust the data they were given to activate. Being a digitally native organization every pod and team was enabled with data capabilities, which created a challenge for adoption of central infra.
A critical breakthrough came when we secured executive sponsorship including the CEO, who became strong supporter of the capability. We stopped talking about “data projects” and started framing the initiative around a unified customer experience, with shared KPIs for both tech and marketing. This aligned incentives toward building a single, trusted view of the customer. This drove consistent experiences for the customers.
Tactical Steps That Worked
With executive buy-in, we took three concrete steps:
1. Implemented Enterprise CDP Architecture: This Enterprise CDP Architecture enabled us to handle the realtime Data, non-realtime data, it helped us to create User 360 and also enable personalization for digital marketing. This allowed us to link real-time event streams from our app, lead gen business and website directly with our consented identity graph fast database and data warehouse. This approach was more flexible, cost-effective, and reduced data latency from days to minutes.
2. Prioritize the Identity Resolution:We invested heavily in building and maintaining a robust, privacy-compliant identity graph. This became our “single source of truth” for customer data, improving our trusted data coverage to over 85% of our user base. The Identity resolution helped us to address the use cases where we needed very high confidence (deterministic) also address use cases where a probability match was acceptable.
Identity Resolution for Financial Services and D2C Organizations
3. Redefine the Activation Journey: We mapped out the entire customer journey and identified key activation points where real-time data could make a difference—like personalizing an offer at the moment of intent or signup, sending an email with potential offer the user has received near realtime.
Board-Level ROI and Impact
The results were fast and significant. Within 12 months of implementing this blueprint:
• Acquisition costs dropped by 5X because we could target high-intent users with personalized offers instead of broad, generic campaigns (CAC).
• Personalized conversion rates doubled as we began to anticipate customer needs in real time, present them something relevant (Conversion).
• The revenue lift exceeded 10X in the first year, driven by higher engagement and loyalty (LTV).
• The App engagement increased by 20% for monthly users (MAU)
Equally important, the board began to see transparent dashboards tied directly to these KPIs. Data activation was no longer a vague “tech project” but a core business capability driving measurable growth.
Conclusion
Enterprise data activation is more than just technology. Its an active strategy rooted in executive sponsorship, cross-team alignment, a commitment to data governance and privacy, and a relentless focus on board-visible ROI. This blueprint of unifying data around a trusted identity core and enabling real-time activation can be adapted to any sector looking to transform fragmented data into a revenue-driving engine and growth.
About the Author:
Mr. Amit Kurhekar
Fractional Chief Data & Digital Officer
TransformTechX
Mr. Amit Kurhekar drive $100M+ enterprise growth by turning data into boardroom revenue.
Mr. Amit Kurhekar with 20+ years across Data, AI, and Digital Strategy, he has led transformation at global scale—working with CEOs, CTOs, and product leaders to turn fragmented data into intelligent growth engines.
At MoneyLion as Head of Data & AI Solutions (reporting to the Global CTO), Mr. Amit Kurhekar led the CEO-sponsored Enterprise CDP and User 360 strategy—the foundational layer for our digital marketing, CX, and GenAI ambitions. This initiative:
– Delivered 10X uplift in revenue through personalization and full-funnel automation
– Enabled 2M new user acquisitions at the lowest CAC in our category
– Achieved a 5X reduction in CAC via ML-powered audience segmentation and Martech integration
Before that, at Yodlee, Mr. Amit Kurhekar built a scalable Financial Data Enrichment Platform using ML/DL techniques, enabling AI-driven personalization for global financial institutions.
Mr. Amit Kurhekar led the deployment of several AI/ML solutions—spanning peer benchmarking, credit ready data, and smart categorisation—driving over $8M in measurable value across products and partnerships.
Mr. Amit Kurhekar worked with CPG giant Procter & Gamble for over a decade.
At P&G Mr. Amit Kurhekar pioneered Industry 4.0 AI/ML adoption in manufacturing. In 2017, Mr. Amit Kurhekar piloted one of the industry’s first prognostics ML solutions on the shop floor – improving asset availability from ~60% to 85% (+25%). This made a financial impact of $15M
Through this cross-industry lens, Mr. Amit Kurhekar operate at the intersection of CDO, CAIO, and CTO mandates- blending architecture, governance, and growth strategy into scalable impact.
Today, Mr. Amit Kurhekar share his frameworks and field-tested playbooks through TransformTechX – a content ecosystem for leaders building the next generation of AI-powered enterprises.
Mr. Amit Kurhekar‘s Core Skills:
Data Strategy | Generative AI | AI/ML Architecture | Digital Marketing | Cloud Platforms (AWS, Snowflake) | Martech | | AI Governance | Executive Stakeholder Management
Mr. Amit Kurhekar is Bestowed with the following Licences & Certifications :
https://www.linkedin.com/in/am
Mr. Amit Kurhekar is Accorded with the following Honors & Awards :
https://www.linkedin.com/in/am
Mr. Amit Kurhekar can be Contacted at:
LinkedIn | Official E-mail | Personal E-mail | Blog | Mobile : +601136271953
To Book a 20‑min CDO Audit : https://topmate.io/amitkurheka
