Transcript ManagingCustomerProfiles

Managing Self-evolving
Portfolios of Customer
Profiles
Petros KAVASSALIS
Themis ZAMANI
ITS Berlin
September 4-7, 2004
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Paper authors
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Petros KAVASSALIS
Themis ZAMANI
Michael MPATIKAS
Zoi POLITOPOULOU
Haralambos SABALIS
Ntina SPYROPOULOU
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Agenda
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Marketing goes digital
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24/7/2004
Technology-based Marketing
Internet & Mobile channels emerge
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Challenges ahead
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The ATL Messaging Management
Engine project (Univ. of Crete)
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Concluding thoughts
ME under pressure
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Marketing executives (ME) learn to live with
multiple marketing technologies
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Marketing Campaign Management
Enterprise Marketing Management
Digital Direct Marketing
Marketing and Sales Effectiveness Technologies
New issues arise
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Prove marketing operations performance
Customer-by-customer profitability
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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What exactly happens?
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Most new marketing technologies are enabled
because of the proliferation of the marketing channels
customers
INTERNET
MOBILE
data
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But also enable companies to store data
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Implications
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Increased data storage together with new
capabilities for measurement and reporting
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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
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Marketing Management
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M
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Needs for :
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Efficient management of collected
data
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Systematic collection of customer
feedback
Provision of analytical
information
Effective privacy protection
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Enterprise-wide privacy policies
Privacy regulation including self
regulation (technology
embedded)
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Agenda
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Marketing goes digital
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
Technology-based Marketing
Internet & Mobile channels emerge

Challenges ahead

The ATL Messaging Management
Engine project (Univ. of Crete)

Concluding thoughts
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Do data have value?
Users
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Can Data be
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1. Visit sites
2. Send messages
3. Purchase goods
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Collected
Stored
Detailed
Individualized
Linked
Data
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Yes! If you can build knowledge
[See: Boisot & Canals, Dosi & Egidi, Kogut]
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Efficient data management
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Data  Information: Information filters on data
(structure data, recognize regularities)
Customer profiles = Information filters
What is a customer profile?
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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)
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Comprises pairs of <objects (or events) – attitudes>
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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)
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Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Customer profiles in practice
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Internet User
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Site 1, 2, 3…. n
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Mobile User
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Service 1, 2, 3…. n
SMS
campaign
duration of visit to each site
response date and time
number of page views during each visit
conducted actions (participation in a SMS
poll or expression of an opinion through a
SMS message)
items viewed
content of customer message (s)
Frequency of visits
Frequency of participation
other attitudes during site’s navigation
other attitudes
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Effective privacy management
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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/)
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A framework enabling business to publish clear privavy promises
and enforce these promises throughout the enterprise
A privacy architecture defining
o What data are collected
o For what purpose they will be used
o How long they will be retained
o How and when these data may be delivered to third parties
(beyond the enterprise)…
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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IBM e-P3P extends W3C P3P
PII
Applies To : Data collection
+ storage + processing +
strategic use
Applies To: Data
collection
eP3P: Implements an
enterprise privacy
enforcement system to
effectively manage privacy
P3P: Is a standard,
computer readable format
for privacy policies
Mission: Defines privacy
policy processes and
supports transparency in
data collection
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
Mission: Enforces E-P3P
privacy policies, allows for a
transparent auditing, while
promising a “provable” P3P
statement to customers
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New regulation paradigm
Regulation
Self-Regulation
Use of Privacy-Enhancing
Technologies
Legislation
2002/58/EU
Industry Standards or
Third Party Verification
MMA
TRUSTe
P3P
IBM eP3P
Privacy Policies
1.
2.
Enforcement
Mechanisms
3.
4.
Codes
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
5.
Actions
6.
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 online
transborder data flows
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Agenda
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Marketing goes digital
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Technology-based Marketing
Internet & Mobile channels emerge

Challenges ahead

The ATL Messaging Management
Engine project (Univ. of Crete)
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Concluding thoughts
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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ATL MMM: an open to the
community project
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Collect and process data from mobile
operations
Mobile
M
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SMS Interactive
TV / Radio
Business Mobile Messaging
1. mobile CRM
2. enterprise
m-channel
Petros KAVASSALIS <[email protected]>,
ITS Berlin
2004
Mobile Coupons
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Example: a m-m campaign
INFORM
SEND SMS
SMS REPLY
SEND AGAIN
•Track real time data
•Provide response rates
•Implement the
services modules
•Send messages &
verify delivery
•Collect responses
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
•Set business objectives
•Define success rates
•Decide service modules
(text-to-win, quiz, poll,
coupons etc.)
Build or acquire opt-in
lists
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ATL MME
Connection
to operators
& mobile
gateways
Mngt of
4/5digits
numbers
ATL
mm platform
Opinion
Alerts
ATL studio
Project
Design
&
Development
Vote
Quiz
Project
Mngt
Users entry
HTTP / SMPP
Mobile operators
(SMS-C) & MOBILE GATEWAYS
ATL
mm gateway
Multicast
Message
routing
Chat
Tracking
&
Reporting
ATL mm permission database
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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How it works?
ATL
mm platform
ATL studio
1.
2.
3.
4.
ATL mm permission database
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
Mobile Marketing
Mobile Coupons
business mobile messaging
1. mobile CRM
2. enterprise m-channel
SMS Interactive TV / Radio
1. SMS / MMS TV
2. SMS Radio
Participate in
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SMS streams like clickstreams
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Architecture
ATL studio
ATL
mm platform
Opinion
Alerts
Vote
Profile
SUBSET
USERS
Quiz
Multicast
Chat
U
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Third sources
DATA COLLECTION &
ORGANIZATION
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
PRIVACY
POLICIES
PROFILES
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Element “Project Sheet”
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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
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Project name
Starting date
Ending date
Keyword(s) [Euro2004, Athens2004]
Short number [4160]
Response message
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Element “Customer Profile”
Local profile
Project 1
Local profile
Project 2
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Project 1
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Project 2
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Project 3
Local profile
Project 3
(Dynamic)
Customer profile
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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An example of Customer Profile
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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ATL MME = “open source” m-P3P
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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
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A “customer profile” information filter on collected
data
A privacy policy architecture that
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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
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Types of PII data
(from “data subjects” / customers)
Third Party
(through ATL studio)
P4
ATL mm
permission
database
Entry
P1
ATL
mm platform
P2
P3
Structured
Data
Call Center /
Web Site
(through ATL studio)
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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ATL MME m-P3P
implementation
Project
Sheet
ATL studio
Who? (data-user)
Operations
{data-user, project}
PII DATA
ENTRY
Admin
Purposes
Obligations
Obligations
Dynamic Profiles
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
Local Profiles
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Who?
In detail…
Project
Sheet
{data-user, project}
ATL studio
Operations
- only read data
- write on data
- disclose data
Purposes
PII DATA
ENTRY
Admin
- send response
message
- send marketing
message
Obligations
Obligations
- erase profile if no
participation for more
than 12 months
- do not operate for
“under 14”
-erase local profile when
receiving “opt-out” SMS
Dynamic Profiles
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
Local Profiles
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Agenda
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Marketing goes digital

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Technology-based Marketing
Internet & Mobile channels emerge

Challenges ahead

The ATL Messaging Management
Engine project (Univ. of Crete)

Concluding thoughts
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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Open issues
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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?
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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?)
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Do the customers easier accept to provide data when
there is a strong (auditable) promise for privacy
protection?
Petros KAVASSALIS <[email protected]>, ITS Berlin 2004
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