Introducing SPSS customer overview

Editor's Notes

• #2: Today, I’d like to give you a quick overview of SPSS, an IBM company, its products and solutions, and the customer value it delivers.
• #3: There are several factors driving the need for a new way of looking at information and the way we make decisions based on that information… Not only is the volume of data exploding, but the nature of the data is shifting. For example, 80% of new data growth is unstructured content, generated largely by email, forms, documents, blogs, wikis and more. All of this data provides an excellent opportunity for driving new information and business insight! …BUT it also represents challenges. With this expansion of the sources of information comes large variance in the complexion of the available data -- very noisy, lots of errors -- and no time to cleanse it in a world of real-time decision making. Business leaders have to make crucial decisions every day. Intuition and gut-based decision making informed mostly by personal experience is no longer sufficient. Yet they sense they are operating with major blind spots -- precisely at a point in time when margins for error have been reduced to near nothing, where costs have to be taken out of the system and the velocity of decision-making is increasing exponentially.
• #4: For example…c ritical decisions are being made without the right information…and decision makers are wasting time just searching for it. Every week, the average information worker spends 14.5 hours reading & answering e-mail, 13.3 hours creating documents, 9.6 hours searching for information, 9.5 hours analyzing information. Both formal market research as well as individual conversations with our customers confirm that all companies now collect huge amounts of data but they have not been able yet to master it and create competitive advantage out of it.
• #5: As noted by Tom Daveport, analytics are critical for driving competitive advantage. It is no surprise that IBM’s recent Global CIO Study showed Business Intelligence and Analytics as the #1 investment area.
• #6: Not only do organizations need to move to a more fact-driven approach and be able to get to the right information to make better and faster decisions, we believe for organizations to truly gain a breakaway competitive advantage, they must also move from insight to action in a matter of hours rather than weeks. Ideally, they can move from an approach that involves making decisions only after sensing and responding…to an approach that can predict potential outcomes and change course ahead of potential issues. It is about moving: From instinct and intuition to real-time, fact-driven decision making From Automation to Optimization It is about combining and analyzing disparate sources of data from different parts of the company – in real-time
• #7: In this new world of decision making, organizations can optimize every transaction, process and decision at the point of impact, based on the current situation, without requiring that everyone be an analytical expert For example, a retail sales associate can make better decisions at the point of impact by knowing the profile of the buyer and associated predicted behaviors of a buyer type….a telco call center rep can understand the sentiment and behaviors of his customers to prevent churn.
• #8: Are these questions on the minds of your decision makers? Do you have a way to answer them today? Are you looking to CAPTURE information about customers, prospects, employees and more? Do you have a good handle on how your customers, prospects or employees are feeling about their product or service offering? What are they saying about you online? What kind of words are they using when they are on the phone to support? Would a survey of customer preferences and satisfaction level provide valuable insights? Again, with the majority of information being generated being unstructured, there needs to a way to capture that information and add it to the wealth of structured data that you are already managing. 2) Are you able to predict behaviors, preferences and future performance? This question really speaks to the heart of the matter. We find that many customers are frustrated that they make decisions too late…wouldn’t you like to get ahead of the issue and prevent things like customer churn….figure out who is unhappy before they leave and figure out how to retain the most profitable customers? … .or be able not only to detect fraudulent activity, but recognize patterns and prevent it…avoiding the cost and disruption fraud will cause? … .or be able to match customer profiles to buying preferences…for example…be able to segment customers and figure out what they are most likely to purchase when they buy something else, and target marketing campaigns to this behavior? 3) Are you able to act in real-time or ahead of a potential issue Many customers are still relying on a few analytical experts to crunch the data and make recommendations. You may find yourselves in this same situation. Wouldn’t you like to enable all of your decision makers to answer these questions and take immediate action?
• #9: Predictive Analytics is the transformational enabling technology needed to achieve this because it analyzes patterns found in historical and current transaction data as well as attitudinal survey data to predict potential future outcomes. This helps organizations to become more proactive in cutting cost, reducing risk and increasing profitability, optimizing your business and driving new forms of competitive advantage. There are times when only predictive analytics can deliver the kinds of insights needed to answer key business questions: How do I reduce churn and retain the most loyal customers to maximize profitability? Essentially – how can I predict which customers are most likely to leave me? Which ones are most loyal so I can target them with effective programs? How can I detect and ultimately…prevent fraudulent activity to reduce risk? Which factors are most likely to drive customers to choose my product vs. the competitor’s?
• #10: SPSS, an IBM Company is a leading provider of predictive analytic software, services and solutions, with over 40 years of experience and over 250,000 customers. SPSS is a leader that provides the most comprehensive predictive analytics technology, encapsulating advanced mathematical and statistical expertise to extract predictive knowledge. Their technology is v ery widely deployed, and their market leadership is impressive….#2 in Advanced Analytics according to IDC, and a leader in Gartner’s Customer Data Mining Quadrant. Its offerings include: Software – data collection, text and data mining, advanced statistical analysis and deployment technologies Services – implementation, training, consulting, and customization Solutions – combine software and services to deliver high-value line-of-business solutions; used for optimizing marketing campaigns, call center effectiveness, identification of fraudulent activity and more This comprehensive predictive analytics portfolio enables decision makers to predict future events and proactively act upon that insight to drive better business outcomes.
• #11: So what are the key aspects of the SPSS portfolio? SPSS has a long history of providing rich analytic capabilities in core offerings around statistics and data mining. They have broadened their portfolio over the last couple of years to provide an end to end predictive analytics solution for enterprises focusing on people oriented applications such as customer and employee retention, b-to-c marketing, risk, and fraud. They have added capabilities to their portfolio to bring in a broader view of people-oriented data, beyond that typically captured in the warehouse, with survey, market research, and call center software for data collection, text analytics to mine and predict based on qualitative data, and web content mining to broaden reach from traditional data sources. On the back end, SPSS has created a platform to allow predictive information to be embedded in business processes and real time applications. They have also created a multi-user model management environment which they term collaboration to co-ordinate large enterprise deployments. Essentially, with SPSS products, your organization can: Capture attributes, interactions, behaviors, and attitudes for customers, employees or constituents Predict behavior and preferences Act on results Supporting this full analytical process is one of the things that sets SPSS apart from other offerings available on the market today.
• #12: The SPSS Predictive Analytics Software portfolio includes the following four key product categories: Data collection, Modeling, Statistics, and Deployment To Capture information, SPSS provides Data Collection: … a set of tools that allow organizations to develop survey approaches that can be used in order to augment internally captured data with sentiment and opinion data and use this combination as an input into the analytic process. This first step is really about delivering an accurate view of customer attitudes and opinions SPSS has a rich history in Statistics: They provide advanced statistics and data management for analysts researching business problems and/or questions. Statistics allows for the collection, analysis, interpretation, explanation, and presentation of data…providing insight into a sample of data and tools for prediction and forecasting based on this data. Statistics drives confidence in your results and decisions To Predict Results, in addition to statistics, SPSS offers modeling (including text analytics and data mining) Leveraging a set of mining algorithms that provide insight and prediction, data preparation functions and more, modeling helps businesses uncover key insights, patterns, and trends in data, then use this insight to optimize business decisions. Text Mining specifically provides technology that uses natural language processing, heuristic rules, and statistical techniques to reveal conceptual meaning in varying bodies of text. It extracts concepts from text data and then categorizes those concepts. Through this process the product helps to make qualitative data more quantifiable. Examples of data sources include: survey responses, documents, Emails, call center notes, web pages, blogs, and forums. These capabilities bring repeatability to ongoing decision making And to make it easier for a wide range of business users to ACT on these insights , SPSS offers unique deployment technologies. They provide Decision Management tools to help automate high-volume decisions across the enterprise…as well as a flexible, enterprise level foundation for managing & deploying analytics in an enterprise, and delivers analytical results of all SPSS products to portals, dashboards, or business processes. Together with unique methodologies, these technologies help to maximize the impact of analytics in an operation
• #13: SPSS Data Collection products enable customer, employee and other stakeholder attributes, interactions, behavior and attitudes to be collected via phone, paper, and web based surveys. This sentiment and opinion information can be combined with other internally captured data such as sales results and frequency of purchase to become part of the analytic process. Data Collection supports survey data creation, entry, reporting and management. For example: SPSS Data Collection Author enables surveyors to easily create attractive, penetrating surveys through a simple interface SPSS Data collection Author interviewer Web enables the deployment and management of on-line surveys, greatly facilitating ease of use and speeding the delivery of an accurate view of customers’ attitudes and opinions.
• #14: SPSS Statistics provides advanced statistics and data management for analysts researching business problems and/or questions. Statistics allows for the collection, analysis, interpretation, explanation, and presentation of data. It can be used to provide insight into a sample of data and it provides tools for prediction and forecasting based on this data. This capability provides functionality in the following areas… Data Preparation Restructure, identify bands, remove duplicates, manage date/times ….. Analysis Counts, crosstabs, clusters, frequencies, descriptives, factor analysis, linear regression, cluster analysis, ordinal regression and nearest neighbour analysis…. Presentation Scatterplots, density charts, histograms, population pyramids, quality control charts, cross correlation function plots ….
• #15: SPSS Modeler provides a complete workbench used to build analytic streams or jobs, a set of mining algorithms that provide insight and prediction, and data preparation functions, along with a run time environment for job execution. This helps businesses uncover key insights, patterns, and trends in data, then use this insight to optimize business decisions. SPSS is focused on the productivity of the modeling interface with business users and its heterogeneous deployment of models. SPSS helps improve business analysts’ productivity through a business-oriented, visual and guided interface for creating models, along with a collaboration environment for groups of analysts to work on models, and a deployment service to manage the workflow, management and execution of models.
• #16: SPSS Text Analytics provides technology that uses natural language processing, heuristic rules, and statistical techniques to reveal conceptual meaning in varying bodies of text. It extracts concepts from text data and then categorizes those concepts. Through this process the product helps to make qualitative data more quantifiable. Examples of data sources include: Survey responses, documents, Emails, call center notes, web pages, blogs, and forums.
• #17: SPSS Decision Management provides a collection of tools intended to help organizations automate high-volume decisions across the enterprise. An example of this is whether or not to “fast track” an insurance claims process or, alternatively, evaluate the claim more closely based upon a calculated “risk score.”
• #18: SPSS Collaboration and Deployment Services provide a flexible, enterprise level foundation for managing and deploying analytics in an enterprise. The product enables collaboration and provides reliable automation of analytical processes for better orchestration and discipline in an organization. It also streamlines deployment of analytical results throughout the enterprise to enable better decision making. Collaboration and Deployment Services also provides some important cross-product capabilities for the SPSS suite of products. It manages assets of all SPSS products, automates processing of all SPSS operations including the execution of statistics syntax, analytic jobs, executing running Data Collection scripts, and delivering analytical results of all SPSS products to portals, dashboards or business processes.
• #19: So how is SPSS different? First … SPSS is focused on making it easy for business users across the organization to leverage the power of information for better decision making. This is done in a couple of ways…. SPSS is focused on the productivity of the modeling interface with business users and its heterogeneous deployment of models. SPSS helps improve business analysts’ productivity through a business-oriented visual and guided interface for creating models, along with a collaboration environment for groups of analysts to work on models, and a deployment service to manage the workflow, management and execution of models. As well, SPSS offers u nique deployment technologies and methodology…combining software and services to deliver high-value line-of-business solutions and integrate analytics into core business processes. These solutions are used for tackling key business issues like optimizing marketing campaigns, call center effectiveness, identification of fraudulent activity and more. Secondly , SPSS has an open, SOA-based offering. Their software is componentized, enabling it to easily fit within a customer’s existing environment, immediately adding value. For example, SPSS seamlessly fits in and leverages a heterogeneous data environment… without the need for a rip and replace of information infrastructure. With SPSS, Predictive Analytics becomes a natural part of a users normal activity (versus something that takes place in a separate, disconnected application.) Finally , with 40 years in this space, they have a deep domain expertise around capturing people’s attitudes, attributes and behaviors. Their data collection capabilities are ideal for market research and feedback management -- deploying these results to a wide variety of consumers from customer representatives to business managers.
• #20: To optimize business performance, decision makers across the organization (regardless of department) must be able to answer 3 key questions: How are we doing? Why are we on/off track? What should we do next? IBM offers a broad range of BI and Performance Management capabilities to address this challenge today, including: Dashboarding and scorecarding , to provide an at-a-glance view of information to help managers and executives understand how their business is performing, with the ability to drill down easily for further analysis Reporting, query and analysis to provide decision makers a deeper understanding of what is happening and why And capabilities like analysis and planning help decision makers figure out what to do next, and to contribute to their forward plans, budgets and forecasts So with all these capabilities available to address these questions and optimize performance, where does SPSS fit and how can it add value to these solutions?
• #21: The SPSS portfolio will enhance not only IBM’s analysis capabilities, but provides new solution value across the portfolio… Leveraging the predictive capabilities, you will be able not only to have your standard KPIs available on your dashboards and scorecards, but can also track KPPs (key performance predictors) – enabling you to see both leading indicators as well as the future status of issues managers are tracking. And you will be able to leverage unique aspects of the SPSS portfolio, including the data collection capabilities…so you can augment the type of data you are seeing with survey data -- unstructured data that provides additional and unique insights for seeing the whole picture. And of course, using IBM Cognos’ market leading reporting capabilities, you can broadly distribute results from statistical and data mining models…ensuring that decision makers across the organization gain those insights. On a related note, you will appreciate the business-oriented data mining modeling environment…enabling advanced analysts to set up the models and apply them to the underlying data. And of course, using SPSS capabilities you will enhance your analysis capabilities with predictive analytics. Last but not least, the predictive capabilities from SPSS enable time series forecasting.
• #22: Adding SPSS’ PASW Modeler to InfoSphere Warehouse brings together the best in class capabilities of SPSS and InfoSphere, allowing companies to take advantage of the predictive modeling and model management of SPSS and the speed and scale of the InfoSphere warehouse, with the results written back to the warehouse for broad consumption of the information. This combination is designed for Analytical Professionals and Application Developers who are responsible for meeting the predictive analytic requirements of their organization, but who are struggling with the complexity of collaboratively building and deploying effective mining models across the enterprise. It is unlike other business analytics solutions that require complex integration efforts to bring together multiple piece parts from multiple vendors and require massive new investments in hardware, software, storage and training.
• #23: The SPSS portfolio can help you answer critical customer intimacy questions, such as… How hard is it for your customers to leave? How long would it take you to detect customer defection? How educated are your customers on their alternatives? What has recently changed in the market which might make your customers defect? What kind of customer feedback loops are built into your interactions that allow you to assess and react to the risk of defection? How effective are your loyalty programs? By answering these questions, you can reduce customer defection, increase uplift from cross-sell and up-sell targeting, and improve identification of acquisition of the “right” customers. This can be done using various aspects of the SPSS portfolio: SPSS Statistics can help you identify drivers of customer behavior… Modeler can help you identify key performance predictors (KPPs) including customer defection and outcome of particular customer interactions… Text Analytics can be used to understand unstructured data that is found in everything from e-mail communications, call center notes, blogs, and open ended survey questions…. And if you are already an IBM Cognos BI customer, you will really appreciate the ability to broadly distribute customer intimacy insights alongside key performance information through your reports, analyses and dashboards.
• #24: Here are 3 great examples of customers that have benefited from this solution… AMR…which owns American Airlines…comments on how they are able to do more research than ever before…and deliver more efficiently …making them a happy customer indeed. HSBC is using SPSS to upsell and cross sell customers Premierline Direct speaks to the acceleration in decision making and the cost pressures they are under, and how SPSS provides unique and critical insights for their pricing and marketing efforts.
• #25: With the pressures that many organizations like yours are facing today in terms of cost cutting and justification of projects, it is nice to know that SPSS customers have been able to achieve a measurable and impressive ROI. As you can see from the highlights of this Nucleus Research study, Nucleus claims that SPSS delivers one of the highest ROI scores they have ever seen. Over 90% of users claimed an increase in productivity to SPSS 81% of projects were deployed on time, with ¾ of them under budget.
• #26: So how are other customers benefiting from all these great software, solutions and services? Center for Disease Control (CDC): Improve Health Care and Patient Outcomes SPSS predictive analytics are used to: Quickly capture vast amounts of data on critical public health issues found in phone and in-person interviews, email and the Internet across geographies and languages. Information is filtered in real-time so workers can better understand behaviors and attitudes and devise the most appropriate responses for citizens. Data captured can be distilled to better characterize diseases, identify risk factors and quickly assess medical needs of specific populations Healthcare workers can plot the expected course of outbreaks and respond quickly and accurately for improved public safety.
• #27: Cablecom GmbH: Reducing Customer Churn Challenge: Accurately determining when and why customers were likely to cancel service Using data collection survey software and data and text mining, Cablecom discovered unsatisfactory events in the early to midterm portions of the customer’s lifecycle have the deepest affect on churn, in many case much further down the line. Company combined this key customer knowledge and survey feedback in direct marketing efforts 100 percent improvement in churn detection and an initial reduction in actual churn from 19% to 2%. 53% of its unsatisfied customers became company promoters
• #28: Richmond Police Department: Predict and prevent criminal activity SPSS predictive analytics are used to: Identify and predict patterns through timely analysis of incident reports, crime tips, calls for service and other data that police departments receive daily Forecast which minor crimes are most likely to escalate into violence Rapidly model motive(s) to facilitate suspect identification and apprehension Investigate dispatch data to pinpoint “hot spots” and place tactical units where they are needed most. Detectives saw a 20-30 percent decrease in violent crime and homicides in a 12-month period.
• #29: Infinity Property and Casualty Corp: Reducing Fraud Challenge: After 6 insurance companies were merged, claims processing was laden with fraudulent claims and processing bottlenecks. Infinity sought a software solution to fight claims fraud, improve claim cycle time and enhance customer service. Predictive Analytics implemented in a real-time claims scoring solution to determine whether claims are legitimate and qualify for immediate approval or are potentially fraudulent and should be further investigated. Cut referral time from 14 days to less than 24 hours on Special Investigation (SIU) claims. Identified and addressed subrogation claims at twice the speed – from 26 to 10 days, Recognized an increase in the ratio of subrogation referrals to first party collision claims paid, translating into more recovery dollars in a shorter period of time
• #30: We are very excited to add the comprehensive SPSS predictive analytics portfolio to IBM as it offers tremendous value to our customers. Enables decision makers across the organization to predict future events and proactively act upon that insight to drive better business outcomes