Why bring customer data together?

Your business descisions are as good as your understanding of the customer.

A Customer Data Platform

  • Is critical for seamless customer engagement, providing you the ability to deliver a consistent customer experience across all touchpoints
  • Provides better context, richer analytics and personalization based on cross-channel behavioral data
  • Impacts multiple parts of your business, not just marketing. e.g. customer service, location analytics, pricing, assortment planning

Manthan improves the quality of customer data and brings in third party data sets, to help surface opportunities and enhance the quality of insights

Having all the data is pretty useless if business users can’t access it seamlessly

Manthan CDP serves the needs of enterprise users, and makes it easy for you to comply with GDPR and other data privacy requirements

  • Serves as a repository of all your first party data organized with customer at the center
  • Core infrastructure for analytical workloads
  • End to end data ingestion, data management and data serving capabilities
  • Puts business users in control, not the IT department
  • Can be onboarded within 4-6 weeks, unlike others that take over 8 months

How does Manthan CDP work

Data Ingestion

  • Capture operational, technical and business metadata
  • Batch & real-time data sync

Data Management

  • Optimized data model specific to your industry
  • Data quality checks and corrections
  • Cost effective, hybrid and real-time
  • Create complete customer identity graph

Data Serving

  • Serve various user groups: business, data analysts, data scientists
  • Support marketing, customer journeys, enterprise analytics
  • Applications in personalization, customer service, business intelligence

Manthan CDP meets the data management needs of different user groups

Raw data

As was, unclean

Long-term data storage

Curated/ Transformed data zone

Data structures and relationships defined

Most relevant for data scientists and analysts who are trying to understand long term business trends, and run heavy algorithmic workloads

Business storage

Summarized, purpose built

- Most relevant for business users (marketers, clientelling apps)
- Data marts that store last 2-3 years of data necessary for business planning, comparisons, customer micro-segmentation

In-memory

Very recent or recently used

- Temporary or in-memory cache
- Data extracts designed for highly interactive what if analyses and quick responses

Real-time

Personalization engines

- NoSQL lookup of customer data, most relevant for API to API integration with personalization engines
- Not always a component of CDP

METADATA

Semantic layer, Authorization

Semantic layer that provides data governance capabilities, and allows business users to interact with the data without knowing SQL

Create better customer engagement with a unified, enriched view of the customer

  • Growth in loyalty program member base for a Mexican supermarket chain

  • Jump in website traffic through targeted mails for a US supermarket chain

  • Revenue retained through predictive churn modelling for a Singapore retailer

  • Increase in campaign response rate for a coalition loyalty program in Asia

Manthan CDP is built for B2C verticals – Fashion, Grocery, Food & Beverage, E-commerce and Loyalty programs

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Customer Data Platforms
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