Orange County Convention Center Orlando, Florida June 3-5, 2014 Innovative Personalized Customer Experience on Banking Digital Channels Shuki Idan, SAP Labs Israel
THE SPEAKER Dr. Shuki (Yizhak) Idan Head of Technology and Solutions Management shuki.idan@sap.com SAP Labs, Israel
SAP REAL TIME OFFER MANAGEMENT (RTOM) Omni-channel contextual recommendation engine* available standalone, hosted and on demand Automatically learns from response and recommends optimal next best offers (NBO) and next best actions (NBA) Offer designer End-to-end offer management solution including offer designer, simulation tools, analytics and management tools, as well as integration and configuration tools Recommendations on the end-user & agent screens *standalone or powered by HANA Offer management analytics
THE RIGHT OFFER AT THE RIGHT TIME 2. Real-time contextual information (trigger) Channel Info, Customer ID, Location, Agent ID, Type of activity, Volume, 1. Offers Definition What - Offer / Action Who - Target Audience Where - Channels When - Context SAP RTOM 4. Optimal Recommendations Cross/up sell offers Next Best Actions Loyalty offers Marketing Messages 5. Response capture and online learning 3. Real-time information fetch Real time customer profile and historical transactions Previous customer s responses
FSI NBO/NBA GUIDELINES Appropriate for automation Repeatable so automation worthwhile Non-trivial i.e. requires a certain degree of expertise or analysis With measureable impact to justify and enable optimization Rule-Centric i.e. policy, eligibility, online calculations and/or Analytic Centric i.e. marketing, retention, optimization, risk, fraud
MARKET TRENDS DRIVING INNOVATION Contact Center Omni-Channel Across all touch-points: website, mobile apps, social, kiosks, Predictive Event Based Our digital life requires fast reactive response to location, time, desire, action and other presence parameters Customer Data Big Data Melding fast changing data streams and customer information, from internal/external sources, provide innovation and differentiation opportunity for fast movers
TRENDS AND INNOVATION OPPORTUNITIES Reactive Omni-channel Needs sensitive Cross channel sensitive Channel discriminative Social sensitive Up/cross selling / bundling Personalized Contextual Surprise ready (e.g. retention) Location/browsing based Automating escalations Guiding (e.g. dynamic selling) Ubiquitous and aware Predictive Big Data Behavior Change Sensitive Opportunity identification Risk handling (e.g. fraud, compliance, income,..) Event based Discriminative
CONTEXTUAL OFFER IMPLEMENTATION Why: branding, credit card differentiation, loyalty club boost When: mobile device location, ATM/Kiosk location, credit card swipe location, branch location, etc. How: Offer locations are loaded as attachment RTOM serves eligible offers that are within a required range set by the calling application (e.g. short range in downtown and long range in suburbs)
TYPICAL CHALENGES Data is everywhere - data is spread across multiple systems handling credit cards, wealth, stocks, cash accounts, loans, insurance products, etc. Legacy is still the king - requires integration with many legacy and 3 rd party solutions Complex data models - data models include accounts, transactions and products in a mix of system and structures Compliance - data privacy, location tracking, communication, consumer privacy protection, other regulations
OVERCOMING CHALENGES Data is everywhere - data is spread across multiple systems handling Offer oriented design and phased rollout credit cards, wealth, stocks, cash accounts, loans, insurance products, etc. Legacy is still the king - require integration with many le and cy and 3 rd party solutions Identify what is really real time Complex data models - data models includes accounts, transactions Prefer data push to data pull and products in a mix of system and structures Compliance- data privacy, location Connectivity tracking, communication, to policy management consumer privacy protection, etc.
ROLLOUT METHODOLOY - EXAMPLE Rollout oriented design ensuring seamless future extension Start at the call center to evaluate the benefits, collect feedback and put in place best practice processes Use of the framework that was set up in the call center to extend deployment to online channels Rollout extension to other countries
RETURN ON INVESTMENT 114% with incentives Business challenges Complex offering the bank manages a comprehensive offering environment: banking, brokerage, insurance, investment, mortgage, trust and payment services Wish to create and manage a multitude of cross line of business offers (e.g. mortgage + insurance) All product should be available over all channels Booked Accounts vs. control group 62% 60% 60% CRM strategy & objectives We are always here for you Service available 24 hours a day, 7 days a week; 24-Hour Bankers are available 24 hours a day, 7 days a week; etc. We have the product you need and if not we will create it Immediate and accurate execution guaranteed 58% 56% 54% 52% 50% 48% 52% 57% Jan Feb Mar Results RTOM agents were doing 50-60% better and improving month to month 18% positive response to offers; additional 12% requested follow up 3 hours to train new agents Up and running in call center within 3 months ROI within 6 months
KEY LEARNINGS CRM FSI innovation opportunities can be found at the crossroads of big data, event based and Omni-channel The key benefits of implementing NBO/NBA scenarios are in providing a personalized and relevant customer experience to maximize conversions while governing risks Legacy landscapes, data dispersal, data complexity and compliance are the main challenges for implementing NBO/NBA scenarios To overcome these challenges and create business processes that embrace innovation, projects need to be offer focused and phased Centralized real time decisioning infrastructure can serve many other SFI scenarios in the front and back office
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