Jun 13 2017

Big Data Analytics, Big Data Solutions, Enterprise Big Data Applications #big #data, #big #data #applications,


Big Data Analytics

Creating a seamless customer experience in a digital world is a primary challenge that several organizations across the globe are grappling with. Customers today expect personalized service without compromise, and demand their providers to educate and inform them no matter what channel they choose to use. A move to customer centricity hinges on delivering better customer experience across all channels and providing value across the customer experience life cycle. Big Data Analytics is increasingly emerging as a key enabler in helping organizations achieve this. Creating a powerful customer value proposition requires understanding customer behavior, preferences and needs along with product/service lifecycle and linking these with ongoing operational transactions and past behavior.

How Wipro Helps

Wipro helps you leverage customer data on purchase patterns, preferences, feedback, wish lists, enquiries etc. to generate customer insights in real time. Our Big Data Analytics Service helps you:

  • Ensure a seamless customer experience across products, channels and lifecycle
  • Improve customer retention
  • Increase profitability by enhanced customer targeting through cross/up sell
  • Launch successful loyalty programs
  • Develop new products
  • Enhance customer lifetime value

Our Big Data Analytics Service puts in place data, processes, analytics tools and visualizations, coherently, by enabling faster time to insights, and enhancing the quality and reliability of insights through exploratory and self-learning models. We help you improve business outcomes through data driven decisions.

Differentiating features of our offering include:

  • Cloud-based Integrated Data and Analytics Platform
  • Analytics based on exploratory and Data Discovery approaches
  • Real-time analytical information and predictive/prescriptive models for better decision making
  • Builds on a machine learning mechanism that understands the behavioral aspects of decision making

The underlying core concept of our service is the use of data events that produce semantic information based on rules/patterns for identifying events of significance. The data layer is the engine driving this Analytics platform.

Following is a sequential detail of the Big Data Analytics platform:

  • Apart from internal data sources, our platform works with external data sources to build a 720 degree view of the customer and design tailored communications and proactive offers
  • Our Decision Management Hub interprets the large volumes of incoming data, including real time data streams. Mapping these insights over a 720 degree view of your customer helps identify and build unique customer experiences
  • Upon developing targeted campaigns and communication strategies for engaging your customers, we help you identify the best channel to reach them via email, direct call, mobile SMS etc. An automated and streamlined workflow for executing these actions through digital marketing platforms is a key feature of this platform

Industry-Focused Use Cases:

Actionable Insights for Financial Services (Industry applicability: Insurance wealth Management and Retail Banking): This solution spans multiple financial data domains offering components on data integration. data management and a set of analytical applications (models, rules, KPI and dashboards) in areas of customer retention, segmentation, risk analysis, voice analytics, pricing and cross sell / up sell. It helps improve customer centricity and reduces time to market.

Actionable Insights for Retail (Applicability for Retail and CPG): This is an integrated set of analytical applications for retailers embarking on integrated multi-channel marketing, real-time offerings or new market entry. The solution has unique features such as actionable insights on lead generation using third-party data along with CRM data (using universal persona technique), and attrition drivers using open source data.

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