Why Apache Spark is the right way to get a real-time customer 360 view

Why Apache Spark is the right way to get a real-time customer 360 view for your business

By Saurabh Dutta | Jan 07, 2019

A survey by Bain & Co. reveals that more than 89% of organizations believe that customer service plays a critical role in staying ahead of the competition. The key to transforming customer experience is having a consistent, complete, and real-time view of customers across systems and channels.

As customers interact with businesses from multiple devices and platforms, companies have huge data available from various sources like website analysis, search results, engagement applications, CRM systems, etc. Customers expect immediate responses to their needs with real-time relevance at every point of engagement.

One of the biggest challenges that any organization faces is having a unified view of their customers to understand what they want, at the right moment. While huge amounts of data flow into the system from multiple sources, often, the data is in silos, making it difficult to stitch it all together to create a complete picture of the customer.

What is Customer 360?

Customer 360 is a strategic approach to enable businesses to identify actionable insights from multichannel data to offer the best customer experience across all channels. By having a unified view of all customer touchpoints, customer 360 tracks the journey and experience of a customer with a business to stitch an end-to-end picture.

Having a real-time 360-degree view of the customer can help businesses to:

  • Personalize the customer experience
  • Deliver the right services at the right time
  • Predict customer behavior
  • Target new customers
  • Retain customers

Research shows that 25% of customers will defect after one bad experience. Customers accustomed to the personalization and ease of dealing with digital natives such as Google and Amazon now expect the same kind of service from established players.

While the expectation of customer to have an end-to-end satisfaction is valid, various factors contribute to playing spoilsport in having a ‘wow’ experience. While the reasons are many, some of them are:

  • Fragmented systems with no true single unified view
  • Processing workloads in batches and not in real-time
  • Scalability of systems to accommodate and process extensive data
  • Minimal application of machine learning applied to Customer 360
  • In-house talent still centered around traditional data warehouse

To address these challenges, Apache Spark is becoming a de-facto engine. It can help businesses build an accurate customer 360 view and to deliver compelling experiences now.

How can Apache Spark help with Customer 360?

With its ability to handle end-to-end needs for data processing, analytics, and machine learning workloads, Apache Spark has the following capabilities to be the right candidate to get a real-time customer 360 view for your business:

  • Provides a solid always on unified view of the past, present, and future
  • Capable of predictive and prescriptive modeling based on all customer signals including text and NLP
  • Accurate and trustworthy
  • Goes beyond data integration, offers complete information integration
  • Always ON system
  • Provides a view that is recent, comprehensive, relevant, and sensitive to privacy concerns

To learn more about how Apache Spark-based architecture addresses the data challenges of real-time customer 360: Watch the webinar – Transforming Real-time Customer 360 with Apache Spark

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