.svg){kind=icon}
.svg){kind=icon}
LatentView Analytics
LatentView Analytics has been helping enterprises make smarter, data-driven decisions for 20+ years. Founded in 2006 by Venkat Viswanathan and Pramad Jandhyala, the company has grown into one of the world’s leading digital analytics firms — and became the first analytics company in India to go public in 2021.
LatentView brings deep expertise in end-to-end data engineering, business analytics, GenAI, and predictive modeling to 50+ Fortune 500 clients across tech, retail, financial services, and CPG. The company’s work spans everything from AI-powered sales forecasting and customer lifetime value modeling to large-scale data platform builds and GenAI implementation.
A publicly traded company serving the US, India, Canada, Europe, and Singapore, LatentView has been recognized in Forrester’s Customer Analytics Service Providers Landscape and among India’s Best Workplaces for Millennials. In 2024, the company expanded its capabilities through the acquisition of Decision Point Analytics, adding Revenue Growth Management and GenAI product solutions to its portfolio.
LatentView’s insights are shaped by real client engagements across industries — from building ML frameworks for telecom network reliability to developing guest lifetime value models for leading cruise lines. The perspectives shared on this blog draw from that hands-on experience working at the intersection of data, AI, and business strategy.
Learn more at latentview.com.
Blogs
Customer Segmentation in Banking: Models, Strategies Benefits and Framework
This guide is written for CDOs, Heads of Customer Analytics, and VPs of Retail Banking who need to understand how
How CPG Brands Use Media Mix Modeling to Measure Cross-Channel ROI and Optimize Spend
This guide is written for VP Marketing, CMOs, and Heads of Analytics at CPG and FMCG companies who need to
Churn Prediction for Marketing Retention Campaigns: How to Reduce Customer Attrition With Predictive Analytics
This guide is written for CMOs, VP Marketing, and Heads of CRM and Customer Analytics at enterprise organizations who need
RFM Segmentation for Targeted Campaigns: A Practical Guide to Scoring, Segments, and Campaign Strategy
This guide helps CRM managers, marketing analytics leads, CMOs, and growth marketers understand how RFM segmentation works, how to score
Lookalike Modeling for Customer Acquisition: How to Find More of Your Best Customers at Scale
This guide helps CMOs, growth marketers, and demand generation leads understand how lookalike modeling drives customer acquisition, how to build
MMM vs Multi-Touch Attribution: Key Differences, Use Cases and Which Your Marketing Strategy Actually Needs
This guide helps CMOs, heads of media, marketing analytics leads, and growth marketers understand what MMM and multi-touch attribution each
Operationalizing ECL and CECL: A Smarter Framework for Loss Provisioning
This guide helps CROs, CDOs, and credit risk leaders at banks and capital-markets firms understand what ECL and CECL require
Bayesian Marketing Mix Modeling: A Practical Guide For Analytics Leaders
For analytics and marketing leaders choosing a modeling approach, or reviewing work a team has already built. This covers how
Marketing Mix Modeling For Financial Services: A Strategic Guide For Marketing And Analytics Leaders
For marketing and analytics leaders at banks, lenders, card issuers, and wealth firms. In financial services the model competes against
Marketing Mix Modeling In Insurance: A Strategic Guide For Carrier Marketing Leaders
For carrier marketing leaders and the finance partners who sign off on the number. This covers how an insurance marketing
