Analyst Webinar: Doing a 180 on Customer 360
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451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms.
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Analyst Webinar: Doing a 180 on Customer 360
- 1. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Doing a 180 on Customer 360
- 2. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 2 Presenters Steven Totman @StevenTotman Global Financial Services and Solutions Industry Lead Sheryl Kingstone @skingstone Research Vice President - Customer Experience & Commerce
- 3. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Pitfalls of Legacy Customer 360 applications New Technologies to Cultivate Customer Insights Identify Best Practices to Improve the Customer Journey Q&A
- 4. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 3 BUSINESSES MUST RESPOND TO THE PACE OF CHANGE
- 5. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Digital transformation is about the application and exploitation of technology in all aspects of an organization’s activity. … Success isn't only about the technology. It’s about rethinking strategy, culture, talent, operating models and processes. ˈdɪdʒɪt(ə)l/ adjective ˌtransfəˈmeɪʃ(ə)n nounDigital Transformation
- 6. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Reducing customer friction points 30% Managing data growth Simplifying operations to eliminate manual and paper-based processes 34%42% Pain points driving digital transformation
- 7. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 13 THOSE WHO OWN THE DATA WILL WIN EVERYONE ELSE WILL PAY FOR ACCESS TO IT
- 8. 8© Cloudera, Inc. All rights reserved. The most valuable companies are data-driven 0 200 400 600 800 1,000 1,200 1,400 1,600 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Market capitalization normalized growth ($B) 2007- 2017 Apple Google Microsoft Facebook Amazon S&P 500 Normalized 2007 =100
- 9. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Focusing on processes from the outside in is required in today’s complex customer journey
- 10. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved.
- 11. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved.
- 12. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Leaders embrace intelligent business applications and cloud to enhance ability to innovate Source: 451 Research’s 1H 2017 Voice of the Connected User Landscape: Corporate Mobility and Digital Transformation Survey, n= >500 ~30% IT and 70% line-of-business decision-makers
- 13. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Digital leaders capitalize on data and connected experiences to reimagine the future 89% are interested in using transaction data correlated with customer profile data for better offers and promotions 86% are interested in using machine learning to create personalized customer experiences 77% are interested in using location-based data correlated with customer profile data for contextually relevant communications
- 14. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Key CX use cases Micro-segmentation & targeting B2B prospect hub Attribution & retention Abandoned shopping cart analysis Customer journey optimization Customer survey & feedback analytics Matching anonymous web visitors to customers Deeper customer intelligence in CRM Personalized customer service Unified commerce
- 15. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Understanding alphabet soup
- 16. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. IT vs LOB finger-pointing and status quo must change Fragmented Customer DataIT’s Status Quo “We have a platform” Business’ Status Quo “Just do it” MDM and Data Warehouses Primarily structured data, designed to be system of record Data Lakes and Hadoop A dumping ground for data, not connected into business context IT approaches try to consolidate everything, but are designed to solve IT problems and address ALL data domains rather than solving real business problems. Data Visualization Tools An empty tool, designed to create dashboards Customer Analytics Tools Sophisticated analytics but poor data management, fragmented analytic types = disconnected insights Customer Data Platforms Easy to use SaaS offering but a black box for marketing with less robust machine learning Business approaches involve going outside of IT for the sake of ‘getting it done,’ but rush and underestimate data management. They have the wrong data for analysis and the wrong insights. CRM Systems of record designed for operational sales, marketing or service use cases
- 17. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Opportunity lost Customer Data Management …with self-service access to critical marketing data sources… ...build improved campaigns... BUT failed to capitalize on other use cases for customer service and commerce …with incomplete customer data from the data warehouse… …identified propensity to churn… BUT failed to unearth leading indicators, resulting in untimely predictions and inability to act Customer Analytic Tools …with un- synthesized customer data… …identified a cross- sell opportunity… BUT failed to do proper customer matching, resulting in duplicate offers and a lower response rate Data LakeMDM …with only structured master customer data… …prioritized service queues… BUT failed to factor in all customer data and relationships, resulting in providing poor service levels to valuable clients Visualization …with beautiful charts and graphs… …identified what-if scenarios… BUT failed to provide prescriptive insight and was only as good as the data driving it CRM …with customer profile data… …identified opportunities, campaigns and cases… BUT …failed to provide the next best action based on the full 360
- 18. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Today’s requirements for a true 360° view of the customer Demographics Contact details Products owned Social posts and profiles Relationships Service requests Interactions Transactions Sentiment Life events Personality Proximity and location events Inferred demographics (occupation, etc.) Customer journey insights Churn, risk and value Alerts Influencers
- 19. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Customer intelligence platforms for delivering contextual experiences
- 20. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. How is the market unfolding?
- 21. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Hybrid cloud Customer journey engagement Transparent data architecture Empowers IT and LOB collaboration Identity and machine learning synthesis Line of business data scientist Key areas of differentiation depend on maturity CDP SaaS Cross-channel marketing Black box Shadow IT Probabilistic matching/ID tagging Marketing user CIP Richer streaming real-time intelligenceMix of slow and fast
- 22. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. How: How is a CIP different than what I have? A CIP brings new capabilities to your solution architecture that complement those existing investments 1. Synthesis 2. Perspectives 3. Actionable insight
- 23. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. 451RESEARCH.COM ©2018 451 Research. All Rights Reserved. Where machine learning/artificial intelligence can help customer engagement
- 24. 24© Cloudera, Inc. All rights reserved. PATTERN RECOGNITIO N ANOMALY DETECTIO N PREDICTION SELF-SERVICE INTELLIGENCE SECURE REPORTING REAL-TIME ANALYTICS MACHINE LEARNING ANALYTICS Enterprise-proven machine learning and analytics 700+CUSTOMERS RUN ON 750+CUSTOMERS RUN ON
- 25. © Cloudera, Inc. All rights reserved.Big Data Analytics +-^x Data Science = ML ? AI The preferred path to customer insights
- 26. 26© Cloudera, Inc. All rights reserved. the modern platform for machine learning and analytics optimized for the cloud ENTERPRISE GRADE Secure Performant Compliant SCALABLE Elastic Cost-effective Lower TCO RUNS ANYWHERE Cloud Multi-cloud On-premises
- 27. 27© Cloudera, Inc. All rights reserved. Start with Customer <180 • Think Big • Start Smart • Iterate Often
- 28. 28© Cloudera, Inc. All rights reserved. Churn Prevention & Customer Retention Targeted Marketing & Personalization Proactive Care • Churn Modeling & Prediction • Rotational/ Social Churn • Customer Lifetime Value • Sentiment Analytics • Price Elasticity Modeling • Customer micro-segmentation • Next Best Offer • Campaign Analytics • Geo-Location Analytics • Recommendation Models • Proactive Care Dashboard • Customer Lifetime Value • Subscriber Analytics • QoS Analytics • Real-Time Alerts Customer 360 specific use cases
- 29. 29© Cloudera, Inc. All rights reserved. Cloudera enables customers to successfully use Customer 360 5-10% reduction in customer churn 300% increase in email campaign response rates 230% increase in purchases for targeted shoppers 17% increase in in-store sales >300% increase in customer conversion rates $100 mil savings through the use of campaign performance insights Leading North American Retailer exceeded 36 month membership target in 17 months reduced time to refresh sales data from weekly to every five minutes
- 30. 30© Cloudera, Inc. All rights reserved. CLOUDERA ENTERPRISE DATA PLATFORM The modern platform for machine learning and analytics optimized for the cloud HDFS WORKLOAD S DATA SCIENCE DATA WAREHOUS E OPERATIONA L DATABASE DATA ENGINEERIN G 3RD PARTY SERVICES COMMON SERVICES SECURITY GOVERNANCE LIFECYCLE MANAGEMENT CONTROL PLANE DATA CATALOG STORAGE KUDU Microsoft ADLS Amazon S3
- 31. 31© Cloudera, Inc. All rights reserved. Customer 360 powered by Zero2Hero
- 32. 32© Cloudera, Inc. All rights reserved. Interested in learning more? • Cloudera Vision Blog • Cloudera Solutions Gallery & Microsoft Azure Marketplace • November 28th webinar • January 10th webinar • customer360@cloudera.com
- 33. © Cloudera, Inc. All rights reserved. Thank You customer360@cloudera.com
Editor's Notes
- Ashley to open & give housekeeping
- Ashley to introduce and turn over to Sheryl
- Sheryl
- Digital transformation is real, and it’s happening – our data lends more insight to the state of the transition. It is an inescapable truth that every business is becoming a digital business controlled by software, which is the manifestation of these digital transformations. As businesses continue to align around a digital culture, they need to invest in new approaches to remain relevant in the eyes of their customers. The overall – but seldom-voiced – goal is survival; just ask some of those in industries that have already seen their physical products turned into digital ones and not survived the transformation. 451 Research defines digital transformation as the result of IT innovation that is aligned with, and driven by, a well-planned business strategy with the goal of transforming how organizations: Serve customers, employees and partners Support continuous improvement in business operations Disrupt existing businesses and markets Invent new businesses and business models (Sudesh speaks about ow its not just about technology factors)
- Sheryl (Steve to add on if needed)
- Steve to present How valuable? Well at Cloudera we analyzed the S&P 500 and five of the eight most valuable companies on the planet over the course of the past decade. Those five companies are Amazon, Apple, Microsoft, Google, and Facebook. The market capitalization growth of these companies has been extraordinary. And why is that? Well, it's simple, it's because these companies are data-driven. These companies make money by having more information about you, your buying habits, what you like to spend money on, what you don't like to spend money on, what music you listen to, and even who your friends are.
- Steve – Importance of brining together “single view” of customer.
- Why are these areas so important- because they can separate leaders from laggards- with a 24 point gap differential in leaders embracing AI, Machine learning and Intelligent business applications- It’s not about the individual AI technology but the embedded intelligence in the applications that drive business decision making on a daily basis Other major differences include the ability for businesses to innovate, invest in intelligent personalization and prioritize shifting applications to the cloud.
- starting
- Sheryl It's important that marketing understand the alphabet soup differentiation. MDM, DMP, CRM, CDP and CIPs all offer a variety of benefits, and businesses are still searching for the 'holy grail' solution. It's very difficult to build a CIP from scratch that does more than just house the data but also acts on that data in real time for multiple use cases. Businesses must shift away from 'he who holds the most data wins' attitudes. It's important to plan for all potential intelligent business application use cases of a customer 360 throughout the customer journey. Advanced machine learning that can take action on signals with real-time decision-making for 'in the moment' execution across both physical and digital experiences is essential. Additionally, ensuring that a company is compliant with the GDPR will mean combing all customer data to account for a variety of factors, including where and how data is stored, and ensuring that businesses always have the most current information. Since complying with the GDPR can be a massive cost undertaking, having a single, real-time customer view can motivate a business to turn it into a profit-making activity instead.
- Steve to add on to Sheryl’s comments
- Steve to comment (cost, scope, etc)
- Sheryl However, past approaches by companies that used combinations of CRM systems, master data management (MDM) and data lakes to create a single source of truth have all struggled to live up to the expectations of front-line business users in areas such as marketing, customer care and digital commerce. Looking ahead, however, the new requirement will be investment in customer intelligence platforms (CIPs) that do more than consolidate a single view of the customer: they add a layer of data governance, synthesis and identity, which powers a dynamic customer graph to fulfill the vision of contextual experiences. The advancements in predictive ML intelligence build on a variety of algorithms to achieve real-time one-to-one capability (ideally in fewer than 20 milliseconds). Key advancements include data governance, synthesis and identity, which power a dynamic customer graph to fulfil the vision of contextual experiences. CIPs are not just about the data, but also the potential for delivery of dynamic rich media content, including images, videos and voice. A CIP must go a step further than a CDP by synthesizing data that dynamically links customer-customer and data-customers using an optimized mixture of matching techniques. It provides context from raw data for relationship discovery, with graphs, columnar data stores and in-memory high-performance indexes to drive multiple versions of the truth for different use cases. As it ingests and synthesizes more data into the customer 360, a CIP platform must also become more intelligent in identifying important trends and information for each customer, and better at summarizing the important intelligence for specific business users. Synthesis and reasoning must work in balance to ensure the CIP is usable; as more data is synthesized and the customer 360 becomes deeper and richer, the CIP must get better at summarizing the important intelligence for specific business users. Automated reasoning helps to make inferences and enrichments on each customer profile, and also helps line-of-business users predict the customer’s future actions such as churn, propensity to buy, proximity and location, etc. It provides a deeper understanding of individual customer journeys and unique interactions, combined with transactions, to accurately understand and improve customer experience.
- Steve
- When we talk about machine learning, we mean three buckets of things: pattern recognition, anomaly detection, and ultimately, prediction. On the other hand are what you do with analytics. This is about providing self-service intelligence, increasing productivity for all your knowledge workers, not just data scientists. And lastly, secure reporting. About 700 of our customers today – roughly 2/3 - are running SPARK in their Cloudera environments. Meanwhile, 750-plus are using Cloudera for analytic workloads leveraging Impala. So, we have a high percentage of our customers already using the latest and greatest technologies for both machine learning and analytics.
- We deliver the modern platform for machine learning and analytics that's been optimized for delivery via the cloud. And you see the word that's highlighted here is "platform." That's the business that we're in. We don't make end solutions here at Cloudera, but we do build a platform for deriving value from your data. It's modern because it's based on the latest open source technologies. It's about machine learning because Cloudera has been doing machine learning for many, many years at a production level for hundreds of our customers. And it's about analytics because you can leverage what you're doing in SQL today but move beyond structured data and rigid monolithic database architectures. And last, but certainly not least, everything that we do with a name like Cloudera, you may guess, has been optimized for delivery via the cloud. Whatever we build has to be enterprise grade. It must be scalable. And last, it has to be available to run anywhere, whether that's on-premises, in the cloud, or in some combination thereof, in a hybrid or multi-cloud type of environment.
- Steve
- Steve
- STEVE TO COVER PACKAGED VS. CUSTOM BUILT Here’s an expanded view of how we see the world. We like to refer to Cloudera Enterprise as the modern platform for ML and analytics optimized for the cloud Modern is not just a current statement but a future statement as well. Want to continue evolving and innovating. Want to make sure our customers can continue to deploy new use cases as they need. We’ve observed that the most interesting business applications today actually require 2 if not 3 or 4 of these different analytic capabilities in order to accomplish the end goal Example: Suppose a manufacturing company wants to analyze the continuous stream of data coming off the factory floor to improve their business. Well, First, the plant manager will probably want a real-time view of everything happening in the plant (requires Operational Database) Second, you’ll probably want a historical view as well for comparison purposes (requires Data Engineering) Third, you’ll want a predictive model to predict outages and downtimes (requires Data Science) Fourth, you’ll want to run a bunch of reports to enable the corporate team to analyze waste over last days and months, compare the plant vs. other plants, etc. (requires Data Warehousing capabilities) Finally, you’ll likely want to visualize the results of those reports (requires integration with third-party BI applications) And that is just one example from one industry – many more can be found in other industries as well For example, a retailer might…. Now, that’s a really hard application to build if you are trying to cobble together 4 different systems to do the work – even if they are from one vendor, but especially if from different vendors You’ll have to setup completely different pipelines to ingest, store, and secure data and you’ll have a heck of a time building a consistent catalog of schema and other metadata But with Cloudera, we’ve built all of this functionality into a single, unified platform such that each of our 4 core services share a common data storage, ingestion, security, and governance layer That makes it really easy to build multi-function applications like I’ve described Furthermore, that makes it really easy for different teams and departments within an enterprise to collaborate on all of these business’s data in an organized and scalable manner We call this unique capability SDX for Shared Data Experience
- Steve Also mention there are Azure cloud credits available when proceeding with this path.
- Steve We’ve covered a lot of information, but I wanted to share additional resources to help you learn more. Regardless of where you are in your big data or Customer 360 journey, these assets will help you position your organization for success. -Later today, we will post a Cloudera Vision Blog written by 451 Research’s Sheryl Kingstone that continues to dialogue from this discussion. -If you’re interested in learning more about the Customer 360 powered by Zero2Hero solution you can visit the Cloudera solutions gallery or Microsoft Azure Marketplace -On November 28th, we will have another webinar, this time focused on our SDX. During this webinar we will go into more detail around running Customer 360 workloads -On January 10th, we will host yet another webinar highlighting how Cloudera uses analytics and machine learning to inform marketing and sales strategy. This is a great webinar to attend if you want to hear a success story. -And of course, if you have any questions you can reach out to us at Customer360@cloudera.com -Let’s now open it up for questions.