Customer 360

Customer 360

What is Customer 360?

Customer 360 is a collection of analytics use-cases developed for our customers to understand their customers. They come in handy across the lifecycle of a customer in the evolution from the lead stage to the maturity stage.
B2C businesses across domains have different names for customers. The customer can be a viewer for a media company, subscriber for a telecom company, users for an app company, traveller for a travel company.

To understand your customers better

How Customer 360 Works

Run all the campaigns in parallel by calling the on-demand prediction models. Engagement campaigns need not wait for Acquisition campaigns to complete. A retention program need not be sequenced strictly after a cross-sell program. Customer 360 allows you to execute programs at the right time, and not wait for one campaign to complete to kickstart the other.

The customer moves across multiple phases of the customer journey and gives feedback all along. Capture each of the customer’s action and non-action data points in big data systems to be utilized in enriching the customer profile.

Data from disparate sources like CRM, POS systems, web and app analytics tools, campaign managers, marketing automation tools can be integrated into a data lake and transformed to provide insights.

Customer insights stand-alone is just like a recipe on paper, they are advantageous only if the right ingredients are provided at the required stage in the required shape. We help you integrate the insights (scores, lists, characteristics, metrics) to your systems,

risk score in the application panel

Say a prospect’s risk score in the application panel

A buyers’ favorite categories

A buyers’ favorite categories at the POS terminal

personalised message in the messaging systems

The list of customers with the personalised message in the messaging systems

customers segments

The customers segments and customer deep dives in the campaign managers

Customer dashboards anytime in your browse

Customer dashboards anytime in your browser









Deep Learning

Applications of Customer 360

Whom to target – for acquisition, retention

New customers list, Existing customers list

What segments exist in your business? Profiles of each segment?

Behaviour, Demographics, Transactional; RFM, ML based clustering

Which customers have high propensity to churn?

Customer list with their probability to churn

What products to cross-sell? Whom to cross-sell

Customer list with next best product(s) recommendation

How much business will the customer give you?

Lifetime value for customer in dollars

Who are your loyal customers? Tier Thresholds and business value

Customers by different tiers. Thresholds for the tiers

What to position and sell together?

Transactions data

Which marketing channels have the highest RoI?

Marketing spend and sales data

Dynamically figure out what ads/content to show to customers?

Behaviour, Demographics, Transactional; RFM, ML based clustering


Value Proposition

We help you answer the following questions to overcome your business challenges:


Whom to acquire?

What to sell?

when to sell customer 360

When to sell?

What are the segments?

How to personalise- customer - 360

How to personalise?

recommended products - customer-360

What are the recommended products?

customer be with us- customer 360

How long will the customer be with us?

lifetime value customer 360

What is the customer’s lifetime value?

Whom to retain - customer 360

Whom to retain?

To make the customer journey never-ending, companies are constantly looking for techniques to engage the customers. Here are a few examples of what our clients look to achieve:

  • If the company is a multi-product company, then get the customer to try as many products.
  • If it is a company that offers few products, then get the customer try it as frequently as possible.
  • If it is a one-time purchase, then transform the customer to an ambassador.

This is where Customer 360 comes into play and helps with – Acquiring, Segmenting, Engaging, Campaigning, Recommending & Retaining.

Algorithms – Neural Networks






Linear Regression





Collaborative filtering-customer-360

Collaborative Filtering