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Data led Customer view

Track Consumption to last unit

The recent explosion of data in ecosystems around and internal to enterprises have given rise to a peculiar challenge as to what to measure. For only if the data gets measured, then managers can innovate and experiment to meet the goals. Our data led customer view – customer 360 helps build a scalable comprehensive view with frugal innovation and plug n play reference architecture.

A 360 degree view of customer data usually involves breaking down the CRM, ERP data siloes around the peripheral layers of systems and enabling creation, harmonization of connected customer data which can be measured and outlined with process throughput.

Techniques starting from frugal flow analysis to advance prescriptive analytics including association rule learning, cluster analysis, classification, and regression could be employed to present a singular view. Features and predictive models created over this can be automatically redesigned to reflect changing data, ensuring long-term relevance and continuous value.

Applications of a customer data view include determining segments most likely to respond to an offer, or market basket analysis to model the purchase behaviour of customers.

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Our Approach:

Big part of our approach lies in laying out simplistic data connective tissue view of the enterprise which will help to outline the nodes and dandelions of the data mesh. Our experts will analyse the current enterprise pyramid layered around systems of innovation, engagement and record and advice on a data view facing the customer. The below diagram outlines the tenets and premise of the Data view.

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How to achieve it:

Once the classification is outlined, the application stack is analysed and frugal innovation undertaken at each activity node. Each activity node is analysed under the layers of business value, top line potential and enterprise data visibility.

Benefits:

It places the enterprise data in the forefront of customer and allows each user interaction to be data enabled. This will allow each decision of the enterprise to be data optimized.


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