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Go Beyond Pretty Graphs
The document discusses actionable customer insights derived from big data, highlighting challenges such as customer spamming and marketing inconsistencies that affect engagement. It emphasizes the importance of 'customer DNA,' a structured dataset that allows businesses to better understand consumer behavior and preferences to enhance customer relationships and increase value. Case studies from top banks illustrate the effectiveness of real-time insights in improving customer satisfaction and marketing efficiency.
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Go Beyond Pretty Graphs
- 1. Go Beyond PrettyGraphs – Gaining Actionable Customer Insights from Your Bank’s Big Data NGDATA Webinar – October 22nd 2014 Steven Noels CTO, NGDATA
- 2. Key Takeaways ▪Steps to successfully gain actionable insights from your Big Data ▪ How to apply Customer DNA to better engage your customers and increase their value ▪ Case studies of top banks that are increasing their customer satisfaction by using actionable, real-time insights Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 2
- 3. With so muchdata available, analysis is often time-consuming— making it hard to be agile, let alone proactive. Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 3
- 4. Customer Experience Customerspamming is doing more damage than good Social Data Company & Customer Activity Customer Web & Mobile Website & online apps Mobile App Server Customer Channel Campaigns Mail SMS Print Broadcast Customer Service Desk Customer CRM Systems Offers direct mail ATM web Agent, IVR email mobile chat Relevance? Awareness? Value? Timing? Clarity? Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 4
- 5. Main Challenges toCustomer Centricity Marketing Pressure Multiple Customer Definitions Large organizations are marketing to the same database in different ways and times Inconsistent cadence and messaging damages trust and credibility Over-marketing to customers can lead to decreased engagement and increased churn No central view of the customer Lack of relevant messaging to customers which can lead to low engagement Too many dashboards – little insights Batched analysis can lead to missed opportunities to present offers and messaging in a timely manner. Missed opportunity to impact loyalty and lowers ROI. Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 5
- 6. Not Just BigData Graphs… Enterprises are NOT looking for new presentations of their data anymore, but for RESULTS and for solutions and people to achieve them Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 6
- 7. Answering the ToughQuestions… Which of my most valuable customers is most likely to churn away? And provide me with enough advance notice to go & fix this! Which additional offers can I recommend to a customer based on their recent behavior and spending or savings habits? What is the best channel to connect with my customer, and when? What products can I cross- or up-sell to gain a more solid, long lasting customer relationship, for greater engagement and value? Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 7
- 8. Google Now TheLeading Example connect the dots real-time context-aware hyper-personal Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 8
- 9. Get to KnowYour Customers Preferences Context Affinities Behavior CUSTOMER DNA Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 9
- 10. What is CustomerDNA? ▪ an organized collection of 1000s of predefined descriptive metrics ▪ calculated in real time ▪ by a configuration-based calculation engine ▪ organized per identified customer ▪ based on a variety of data sources, both interaction-and fact-based ▪ using a variety of predefined calculation, prediction or retrieval methods ▪ providing actionable data for marketing & customer-centric applications Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 10
- 11. Customer DNA isBased on Interaction Data and factual data (customer facts, contract info …) Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 11
- 12. Customer DNA Towardsa New Architecture App Phone Mobile www STB Network Shop Call Centre CDR POS Personalization Acquisition Journey ARPU / CLTV Marketing Advertising Churn Fraud App Phone Mobile www STB Network Shop Call Centre POS CDR Personalization Acquisition Journey ARPU / CLTV Marketing Advertising Churn Fraud Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 12
- 13. Customer DNA EnablesYou To… Overcome “Analysis Paralysis” Proactively Engage with Customers Cope with plethora of data Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 13
- 14. Customer DNA EnablesYou To… Analysis Action ability 3 V’s Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 14
- 15. Apply Data-Driven Applications Data-driven applications act on any volume of real-time data to actively guide and optimize business processes based on continuously growing insights on customer behavior, intent and preferences. Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 15
- 16. Applied to Subscription-basedBusinesses Customer Lifetime Value (Inbound, Outbound, Risk) Banking •Value-add Services such as Merchant-funded Coupons • Customer Experience − Personalized service & products − Financial Advise • Risk Assessment • Marketing Targeting Efficiency Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 16
- 17. Use Cases forFinance
- 18. Listen: 1-2-1 Marketingand Micro Campaigns Product-Centric Customer-Centric web branch social media social Retrofit Cus Branch Result Product Teams ATM telesales Product & Individual Product and Content Preferences – Marketing campaigns with higher Frequency (> x10), higher Response rate (x4) and reduced Budget (< ½) Objectives • Improve ROI (conversion ratio) of Marketing Campaigns by targeting individual customers, or Sets of customers based on preferences Solution • Real-time ingest of multiple data feeds • DNA with focus on current accounts, activities, context based interactions and product preferences • Learned preferences to feed event-based marketing actions & connect customers to preferred products • Moving from product centric to customer centric marketing tom er journeys contact center self- Service mobile web Channel Wrapper Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 18
- 19. Learn: Improve CustomerService for Increased CLTV Large US Wealth Management Bank Result Real Time Actionable Customer DNA – Allows agents to provide better and more efficient advice. Building increased customer loyalty Objectives • Improve financial advice suggesting the right investment at the right time to the right customer Solution • Real time ingest of the investment history, behavioral metrics, etc., of the customer • Monitor all interactions (payments, CC, calls, IVR, mobile and online…) to develop a Customer DNA • Continuously learn and enhance the Customer DNA, with a focus on offering potential new investments in line with the individual profile Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 19
- 20. Execute: Merchant-funded MobileOffers Fortune 50 US Retail Bank Mobile Information Mobile Wallet Mobile Redemption Objectives • Leverage multiple sources of data to improve coupon redemption rate through real-time, location-based personalized offers Solution • Real-time ingest of payment transactions • Behavior-based MCC preference learning • Location- and preferences-based coupon selection & delivery in mobile wallet • Evaluate performance between collaborative filtering & KB-based preference learning Result Individual Coupon delivery – Average targeting precision increased by 5-7x, results in increased redemptions and loyalty Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 20
- 21. Experience the Differencewith Lily Listen Bigger. VOLUME Learn Faster. Volumes of Data Availability Questions Answered SPEED Execute Smarter. ANSWERS Unknown Unknowns Known Unknowns Known Knowns DW/BI DW/BI DW/BI Start working with Lily to discover results from Day 1 Zettabytes Exabytes Petabytes Terabytes Gigabytes Seconds Minutes Hours Days Weeks Copyright 2014 NGDATA®, Inc. Confidential – Distribution prohibited without permission 21
- 22. Copyright 2014 NGDATA®,Inc. Confidential – Distribution prohibited without permission 22
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