Customer 360 view: 2-Wk implementation

The changing customer behavior poses significant challenges, particularly in a post-pandemic landscape. With the widespread digital transformation, numerous aspects have shifted online, resulting in an expansion of customer touch-points and a continuous growth of interaction channels. As a result, the unification of customer data has become an ongoing and persistent challenge to identify the customer behavior. When you possess a deep understanding of your customers, you have the power to deliver exceptional service that exceeds their expectations.

Our Customer 360 solution will let you know your customers better from the hidden data. The solution streamlines the process of bringing in customer data from diverse sources, including transactional, behavioral, internal, and external data sources. Moreover, the solution employs data standardization techniques and leverages various AI models to seamlessly match and merge customer records, creating a unified and comprehensive customer profile. With the added extensibility to Azure ML, businesses can unlock limitless possibilities for tailored analytics, such as churn ratio analysis, customer lifetime value (CLV) prediction, sentiment analysis, and personalized product recommendations, among others.

Benefits:

1. Unlock your data to engage with customer with a purpose. 
2. Create more strategic sales with dynamic targeting.
3. Drive marketing efficacy. 
4. Deliver end-to-end customer experiences. 
5. Strengthen customer relationships and earn loyalty.
6. Boost advertising effectiveness.

Technical components:

1. Your source/s of data
2. Azure Synapse Analytics
3. Azure Data Lake Storage
4. Azure Machine Learning
5. Dynamics 365 Customer Insights
6. Power BI

Examples:

1. Customer 360 view for financial institutions like Banks, Mutual Fund companies
2. Patient 360 view for hospitals and healthcare companies.
3. Similar for manufacturing companies, retail, e-commerce, pharma, educational institutes etc

P.S: Connecting to different data sources, cleansing the data takes most of the time, so the timeline may vary depending on the state of data.