Acquire, grow and retain customers with IBM Big Data & Analytics - Client Examples

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Acquire, grow and retain customers with IBM Big Data & Analytics - Client Examples .... Are you effectively converting your audience insights into added value for your consumers? 80% of CEOs believe they deliver a superior customer experience, but only 8% of their customers agree. With IBM Big Data & Analytics solutions you can acquire, grow, and retain customers by improving customer interaction, building long term relationships and realizing value from customer sentiment.

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© 2013 IBM Corporation
Big Data & Analytics
Acquire, Grow, & Retain Customer Greatest Hits
October, 2013

Acquire, grow and retain customers with IBM Big Data & Analytics - Client Examples

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To get value out of today’s big and fast data, organizations must evolve beyond traditional analytic cycles that are heavy with data transformation and schema management. The Hadoop revolution is about merging business analytics and production operations to create the ‘as-it-happens’ business. It’s not a matter of running a few queries to gain insight to make the next business decision but, to change the organization’s fundamental metabolic rate. It is essential to take a data centric approach to infrastructure to provide flexible, real-time data access, collapsing data silos and automating data-to-action for immediate operational benefits.

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Emerging technologies are transforming every aspect of the insurance business. Property and casualty insurers are adapting InsurTech capabilities to be more customer-centric, to optimize costs, and to improve operational efficiency. Transformational moves by P&C insurers include the use of connected devices to mitigate risk, exploring new business models, value chain process automation across using Artificial Intelligence (AI) and Robotic Process Automation (RPA), and blockchain (distributed ledger) technology. They are also leveraging drones for efficient property assessment, Application Programming Interfaces (APIs) for seamlessly integrating with other stakeholders, and advanced analytics to provide personalized offerings and improve underwriting operations. Most of the Insurers prefer to collaborate with InsurTech firms for inculcating InsurTech capabilities and for quick deployment and efficient maintenance of the new systems, they are focusing on a cloud-native approach.

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Today’s data-driven organisations are turning to Databricks for a cloud-based, open, unified platform for data and AI. Yet many companies struggle to unlock the value of the data they have in Databricks. To capitalise on the promise of a competitive edge through increased efficiency and insight, data scientists are turning to location to make sense of massive volumes of business data. Watch this on-demand to hear from The Spatial Distillery Co. and Databricks on how to leverage advanced location intelligence and enrichment solutions in Databricks to: - Simplify the complexity of location data and transform it into valuable insights - Enrich data with thousands of attributes for better, more accurate analytics, AI, and ML models - Leverage the power of Databricks to integrate geospatial data into business processes for real-time answers - Create more meaningful and timely customer interactions by streamlining customer-facing and operational tasks

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Executives are still waiting on our “Big Data Deep Insights”. Many of us are down the path of collecting, extracting, and analyzing our ever-growing data in Hadoop environments. We are building our data science expertise and expanding data governance. Yet still we are not getting what we are waiting for.This talk is about: 1. Getting to the right questions 2. Setting expectations with the executive team 3. The unintentional consequence of suddenly having lots of data 4. Framing the boundaries of our data science 5. Pragmatic data governance 6. Looking outside your data to 3rd party data

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IoT is fundamentally revolutionizing the automotive insurance space, by enabling insurers to gain powerful insights into the behavior, risk, and habits of individual drivers. With over 180 Billion miles of driving data analyzed from connected cars, Octo Telematics has emerged as the leading global provider of telematics and data analytics solutions for the auto insurance industry. Join Cloudera, Ovum and Octo Telematics for a joint webinar to learn more about how Octo built their next generation IoT & Telematics platform. In this session, Jonathan, the Global Chief Marketing Officer of Octo will share their transformational journey into how they are building the world’s largest insurance telematics database powered by analytics and machine learning. As part of this webinar you can learn more about: Octo’s transformation to the Next Generation Platform (NGP) for Telematics & IoT How they process and analyze data from 5.4 million connected cars every day How Octo implemented the data management and analytics infrastructure How they are using machine learning to analyze risks and driving behavior 3 things to learn: Octo’s transformation to the Next Generation Platform (NGP) for Telematics & IoT How they process and analyze data from 5.4 million connected cars every day How Octo implemented the data management and analytics infrastructure

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Data is so ubiquitous, we are sometimes oblivious to just how much of it we interact with—and how many companies are making it a core part of their product. Whether you’re aware of it or not, product leaders across industries are using data to drive engagement and prove value to their end-users. From Fitbit and Medium to Spotify and Slack, data is being leveraged not just for internal decision-making, but as an external product offering and differentiator. These data-as-product features, often displayed as user-facing dashboards, are known as “native analytics” because they are offered natively within the context of the customer experience. We’ve gathered 25 examples of native analytics in modern software to highlight their power and hopefully inspire their further adoption.

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This presentation looks at real-world cases of how organizations are using, or planning to use, big data technology to drive value. It looks at the different ways in which the technology is being used in a business context. Examples are drawn from Retail, Telco, Financial Services and Consumer goods. It also develops a range of business scenarios from simple cost reduction through to new business models specifically looking at how the business case has been built and what value has been realized. First presented by Richard Brown, Capgemini Program Lead for Business Information Management, at the IP Expo – Big Data Summit 2014. http://www.capgemini.com/big-data-analytics

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Big Data and advanced analytics are critical topics for executives today. But many still aren't sure how to turn that promise into value. This presentation provides an overview of 16 examples and use cases that lay out the different ways companies have approached the issue and found value: everything from pricing flexibility to customer preference management to credit risk analysis to fraud protection and discount targeting. For the latest on Big Data & Advanced Analytics: http://mckinseyonmarketingandsales.com/topics/big-data

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