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Data platform: cloud data warehouse, ETL/ELT pipelines, curated analytics data sets
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Customer data platform: unified profiles, audience management, activation connectors to CRM, email, and digital channels
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Analytics & ML: propensity and churn models, model registry, batch and near-real-time scoring
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Integration: APIs for CRM and campaign tools, secure data exchange with core banking and channel systems
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Governance: data catalog, quality checks, consent and contact policy enforcement in the data layer
Customer 360 That Powers Real Offers
At a glance
CLIENT
A regional retail bank
SERVICE
- Data & Analytics, Cloud Data Migration, CX+, CX Strategy & Design, Next-Gen Marketing, Digital Transformation
INDUSTRY
- Financial Services / Retail Banking
A regional retail bank was competing with digital-native players for everyday banking, cards, and consumer loans. Product teams ran separate campaigns for cards, deposits, and loans, each using its own lists and rules. Customer data lived in core banking, card processors, loan systems, web analytics, and call-center logs with no single source of truth. As a result, offers were generic, contact policies were inconsistent, and reporting on campaign performance took weeks.
LeanCoded partnered with the bank to design and implement a Customer 360 and analytics platform for personalized offers. Over 14 months, we built a cloud-based customer data platform (CDP), unified profiles across channels, deployed propensity models for key products, and integrated the platform with existing CRM and campaign tools. The program combined digital transformation services, enterprise software solution design, and targeted software development services to turn fragmented data into a practical engine for personalization.
When “Personalization” Means One Generic Offer for Everyone
Initial discovery showed that most campaigns used broad, static segments such as “salary clients” or “card holders”. Target lists were prepared manually in spreadsheets or by ad-hoc SQL, often based on incomplete data. There was no consistent way to see a customer’s full relationship with the bank—products, balances, digital behavior, and service interactions—on one screen. LeanCoded analyzed data flows from more than ten systems and confirmed that duplicates, inconsistent IDs, and missing consent flags made precise targeting and contact governance nearly impossible.
At the same time, marketing and product teams wanted to move towards always-on, event-driven offers: pre-approved limits, cross-sell nudges in mobile banking, and churn-risk mitigation. Doing so required a modern data foundation, not just more rules in existing tools. LeanCoded designed a Customer 360 architecture built on a cloud data platform, combining data analytics consulting services, big data consulting services, and custom software development for integrations. This architecture became the backbone for both batch campaigns and real-time in-app personalization.
From Raw Data to Customer 360
LeanCoded started with a clear data product mindset: define what a “customer 360 profile” should contain and which use cases it must support in the first release. Together with business stakeholders, we agreed on a core set of attributes—identifiers, products, balances, limits, interaction history, digital events, and consent status. Data engineers then implemented ingestion pipelines from core banking, card systems, loan engines, the mobile app, and the website into a centralized warehouse and CDP layer.
On top of this foundation, our data science team built and industrialized propensity models for three priority products: credit cards, consumer loans, and savings accounts. Using AI software development services, we trained models to predict likelihood to buy and preferred channel for each customer segment. The models were exposed through APIs and integrated into existing CRM and campaign tools, so the bank did not have to replace its entire martech stack to start using advanced analytics.
Business use cases and KPIs first
Unified customer identities and data quality
Data platform and CDP implementation
Propensity models and decision logic
Activation, reporting, and feedback loops
How LeanCoded Turned Data into a Personalization Engine
The bank did not need another dashboard—it needed a way to connect data, models, and channels into a repeatable system. LeanCoded combined engineering, analytics, and change management to make Customer 360 part of daily work for product and marketing teams.
- One profile across products and channels
Customer-facing and analytics teams now work from a single, consistent profile per customer, reducing manual reconciliation and conflicting views of the relationship. - Models embedded into existing tools
Propensity scores are available directly inside CRM and campaign tools, so relationship managers and marketers can use advanced analytics without switching systems. - Faster path from idea to campaign
With reusable segments, audiences, and data sets prepared by the platform, new campaigns can be launched in days instead of weeks, using the same underlying data logic. - Governance built into the data layer
Consent flags, contact limits, and exclusion rules are enforced in the data platform, reducing the risk of over-contacting customers and making compliance checks easier.
Impact on Sales, Efficiency, and Insight
Within the first year after go-live, the bank moved from ad-hoc list building to a structured, data-driven approach for key campaigns. Card and loan cross-sell initiatives using propensity-based targeting delivered higher response rates compared to previous broad segments, while requiring fewer manual steps from analysts. Time to prepare and launch campaigns was reduced significantly thanks to ready-made data sets and reusable audiences in the CDP.
Equally important, product and marketing teams gained a shared language and set of metrics for customer behavior. Instead of debating whose spreadsheet was correct, they now rely on common dashboards built on the same Customer 360 profile and data pipelines. By combining data analytics consulting services, big data consulting services, AI software development services, and focused software development services, LeanCoded helped the regional retail bank turn its scattered customer data into a practical personalization engine that can support future products and channels.