Client Pain Points and Our Solutions

Confusion Around Data & Technology Investments

Uncertainty around whether the right data and technology investments are being made.

Reporting processes feel manual, messy, and inefficient, leading to wasted resources.

Manual, Inefficient Business Processes
Business operations rely heavily on manual spreadsheets and fragmented systems.

Multiple people manually input the same data, leading to inefficiencies and duplicated work.

Inadequate or No Solution Architecture Strategy
No strategy to streamline data flow and architecture, leading to operational bottlenecks.

Unclear technology infrastructure to support data and information flows across departments.

Inability to Scale Due to Fragmented Systems
Multiple systems with manual processes prevent scaling and automation.

Need to automate workflows and integrate disparate data sources into a single, unified interface.

Operational Data Silos and Fragmentation
Different departments and systems are disconnected, causing data silos.

People operate in silos, leading to inconsistent data inputs and outputs, impeding operational efficiency.

No New Product Development with Data at its Core
Lack of guidance on developing new data-driven products (e.g., analytics platforms, recommendation engines).

Need for data as a product (DaaP) strategy to provide actionable insights for customers.

No Data Monetization Strategy or Plan

Data is not being leveraged to generate new revenue streams.

Inability to translate data insights into measurable business outcomes.

Lack of understanding on how to create value from existing data assets.

Business decisions are made without fully realizing the economic potential of data.

 No Data as a Product Plan 

 Lack of strategy to offer data-driven products and services to customers.

No framework to create insights, analytics platforms, or recommendation engines for external use.

Difficulty in identifying how to turn data into a saleable product offering.

Missed opportunities to differentiate in the market by offering innovative data-based services

Lack of Marketing Accountability & Attribution
Marketing has little credibility due to poor accountability and lack of measurable KPIs.

No clear way to justify marketing spend without an econometrics model or proper attribution framework.

Absence of Personalization Strategy & Customer Journeys
No clear customer journey map or personalization plan, leaving untapped potential in customer relationships.

Lack of CRM system or uncertainty on which CRM to choose.

Poor Data Governance & Data Quality Issues
Data governance is lacking, leading to untrustworthy data and compliance risks.

Existing data structures (data warehouse, data lake) need an in-depth audit and optimization.

No Strategic Segmentation or Personas
Current customer segmentation is outdated or non-existent.

Lack of well-defined customer personas limits targeted marketing and sales strategies.

• Customer Journey Models
• Lifetime Value Models, Lookalike Models
• Predictive Models - Prospect Models, Churn Models, Lead scoring Models
• Attribution, Econometrics and Marketing Mix Modelling
• Credit Risk Scorecard Development and Deployment
• Commercial Modelling