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Managing Self-evolving Portfolios of Customer Profiles

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  1. Managing Self-evolving Portfolios of Customer Profiles Petros KAVASSALIS Themis ZAMANI ITS Berlin September 4-7, 2004

  2. Paper authors • Petros KAVASSALIS • Themis ZAMANI • Michael MPATIKAS • Zoi POLITOPOULOU • Haralambos SABALIS • Ntina SPYROPOULOU

  3. Agenda • Marketing goes digital • Technology-based Marketing • Internet & Mobile channels emerge • Challenges ahead • The ATL Messaging Management Engine project (Univ. of Crete) • Concluding thoughts

  4. ME under pressure • Marketing executives (ME) learn to live with multiple marketing technologies • Marketing Campaign Management • Enterprise Marketing Management • Digital Direct Marketing • Marketing and Sales Effectiveness Technologies • New issues arise • Prove marketing operations performance • Customer-by-customer profitability

  5. What exactly happens? • Most new marketing technologies are enabled because of the proliferation of the marketing channels • But also enable companies to store data customers INTERNET MOBILE data

  6. Implications • Increased data storage together with new capabilities for measurement and reporting • Lead to a more “granular” marketing (down to customer detail) • Tighten customer relationships by encouraging dialogue • Allow for personalized marketing content (personal messages, special discounts) • Help companies to develop an enterprise-wide view of the customer

  7. Marketing Management T • M E • A C • R N • K O • E L • T O • I G • N I • G E S • Needs for : • Efficient management of collected data • Systematic collection of customer feedback • Provision of analytical information • Effective privacy protection • Enterprise-wide privacy policies • Privacy regulation including self regulation (technology embedded)

  8. Agenda • Marketing goes digital • Technology-based Marketing • Internet & Mobile channels emerge • Challenges ahead • The ATL Messaging Management Engine project (Univ. of Crete) • Concluding thoughts

  9. Do data have value? • Can Data be • Collected • Stored • Detailed • Individualized • Linked Users • Visit sites • Send messages • Purchase goods Data

  10. Yes! If you can build knowledge Customer data Knowledge Information [See: Boisot & Canals, Dosi & Egidi, Kogut]

  11. Efficient data management • Data  Information: Information filters on data (structure data, recognize regularities) • Customer profiles = Information filters • What is a customer profile? • Information repository • A historical record of the behavior of a customer or prospect while interacting, via an electronic channel, with a particular company or product(s) • Comprises pairs of <objects (or events) – attitudes> • Builds a historical summary of each prospect/customer’s behavior, which may be updated not only through the accumulation of new marketing information but also with transaction data (sales)

  12. duration of visit to each site number of page views during each visit items viewed Frequency of visits other attitudes during site’s navigation Customer profiles in practice • Internet User • Site 1, 2, 3…. n • Mobile User • Service 1, 2, 3…. n SMS campaign response date and time conducted actions (participation in a SMS poll or expression of an opinion through a SMS message) content of customer message (s) Frequency of participation other attitudes

  13. Effective privacy management • Information  Knowledge: Enterprise-wide privacy management (impose access controls and multiple restrictions on collected PII use, to act in and upon its environment consistently with rules and standards) • IBM e-P3P (IBM Platform for Enterprise Privacy Practices = Privacy Enabled Technology, PET) • What is IBM e-P3P? (http://www.zurich.ibm.com/security/enterprise-privacy/) • A framework enabling business to publish clear privavy promises and enforce these promises throughout the enterprise • A privacy architecture defining • What data are collected • For what purpose they will be used • How long they will be retained • How and when these data may be delivered to third parties (beyond the enterprise)…

  14. IBM e-P3P extends W3C P3P IBM e-P3P PII Applies To: Datacollection + storage + processing + strategic use eP3P: Implements an enterprise privacy enforcement system to effectively manage privacy P3P Applies To: Data collection P3P:Is a standard, computer readable format for privacy policies Mission: Enforces E-P3P privacy policies, allows for a transparent auditing, while promising a “provable” P3P statement to customers Mission: Defines privacy policy processes and supports transparency in data collection

  15. New regulation paradigm Regulation Self-Regulation Legislation Use of Privacy-Enhancing Technologies Industry Standards or Third Party Verification 2002/58/EU P3P IBM eP3P Privacy Policies MMA TRUSTe OECD • Adoption of privacy policies • Notification of privacy policies to users • Availability of enforcement and redress mechanisms • Promoting user education and awareness • Use of privacy-enhancing technologies • Use and development of contractual solutions for onlinetransborder dataflows Enforcement Mechanisms Codes Actions

  16. Agenda • Marketing goes digital • Technology-based Marketing • Internet & Mobile channels emerge • Challenges ahead • The ATL Messaging Management Engine project (Univ. of Crete) • Concluding thoughts

  17. Mobile M A R K E T I N G • Business Mobile Messaging • mobile CRM • enterprise m-channel ATL MMM: an open to the community project • Collect and process data from mobile operations SMS Interactive TV / Radio Mobile Coupons

  18. TRACKING & REPORTING DESIGN 1 4 DEVELOPMENT EXECUTION 2 3 Example: a m-m campaign invite response reveal identity motivate INFORM SEND SMS SMS REPLY SEND AGAIN • Track real time data • Provide response rates • Set business objectives • Define success rates • Decide service modules • (text-to-win, quiz, poll, coupons etc.) • Implement the services modules • Send messages & verify delivery • Collect responses Build or acquire opt-in lists

  19. Opinion Alerts Project Design & Development Vote Quiz Multicast Project Mngt Chat Tracking & Reporting Message routing Connection to operators & mobile gateways ATL MME ATL mm gateway ATL mm platform ATL studio Mobile operators (SMS-C) & MOBILE GATEWAYS HTTP / SMPP Users entry Mngt of 4/5digits numbers ATL mm permission database

  20. How it works? ATL mm platform • Mobile Marketing • Mobile Coupons • business mobile messaging • mobile CRM • enterprise m-channel • SMS Interactive TV / Radio • SMS / MMS TV • SMS Radio ATL studio ATL mm permission database Participate in

  21. SMS streams like clickstreams

  22. ATL mm platform Opinion Alerts Vote Quiz Multicast Chat Architecture ATL studio Profile SUBSET USERS UPDATE PRIVACY POLICIES Third sources PROFILES DATA COLLECTION & ORGANIZATION

  23. Element “Project Sheet” • Project owner (data user) • Run (or done) • Type of Module (Opinion, Vote, Other… “taylored” module) • Type of project (mobile marketing, Interactive TV/Radio, etc.) • Content (Information, Interaction, Advertising) • Περιγραφικά στοιχεία • Project name • Starting date • Ending date • Keyword(s) [Euro2004, Athens2004] • Short number [4160] • Response message

  24. Element “Customer Profile” Local profile Project 1 Project 1 12 Local profile Project 2 12 12 Project 2 12 Project 3 Local profile Project 3 (Dynamic) Customer profile

  25. An example of Customer Profile self-evolving

  26. ATL MME = “open source” m-P3P • We implement IBM e-P3P in the context of the mobile business and in an “open source” framework (ATL MME m-P3P) • ATL MME contains • A “customer profile” information filter on collected data • A privacy policy architecture that • Defines types of PII data collected from customers • Describes what operations should be performed on PII data, for which purposes, by which data user • States actions that have to be performed (obligations) • Explicitly models opt-in & opt-out choices for the customer

  27. Types of PII data (from “data subjects” / customers) Third Party (through ATL studio) P4 ATL mm permission database Entry P1 soft opt-in ATL mm platform register P2 Structured Data P3 Call Center / Web Site (through ATL studio)

  28. ATL MME m-P3P implementation ATL studio Who? (data-user) Operations Project Sheet {data-user, project} PII DATA ENTRY Admin Purposes Obligations Obligations Dynamic Profiles Local Profiles

  29. In detail… Who? ATL studio Project Sheet Operations - only read data - write on data - disclose data {data-user, project} Purposes - send response message - send marketing message PII DATA ENTRY Admin Obligations Obligations • - do not operate for “under 14” • erase local profile when receiving “opt-out” SMS - erase profile if no participation for more than 12 months Dynamic Profiles Local Profiles

  30. Agenda • Marketing goes digital • Technology-based Marketing • Internet & Mobile channels emerge • Challenges ahead • The ATL Messaging Management Engine project (Univ. of Crete) • Concluding thoughts

  31. Open issues • Is the “customer profile” a viable “data information filter” or business will act “per project”? (“how much” history will matter?). Is the storage of customer profiles for business use a socially acceptable practice? • Are efficiency / privacy issues at the center of attention of mobile service business – who are “small players”? (how mature is this industry to operate consistently with rules and standards?) • Do the customers easier accept to provide data when there is a strong (auditable) promise for privacy protection?