HOW TO FIND YOUR WAY AROUND A CUSTOMER DATABASE

Transcription

1 HOW TO FIND YOUR WAY AROUND A CUSTOMER DATABASE Fabio Marchetti - BIPOP-CARIRE Alberto Saccardi - NUNATAC SEUGI 19 Florence May 29 June

2 MULTI-CHANNEL CUSTOMER-CENTRIC APPROACH VIRTUAL CHANNEL A customer-oriented Group, should enable customers to choose the channel which better fits their needs, preferences and skills PHYSICAL CHANNEL BRANCH WEB FINANCIAL PLANNERS MOBILE CALL CENTER KIOSKS ATM/POS

3 OUR INTERNATIONAL EXPANSION

4 CUSTOMER DATABASE: HOW TO BUILD A CRM DATA ENVIRONMENT The project goals are: implementation of an environment which meets marketing/sales information requirements unique identification of customers of the various Group companies: who they are, how they interact with the company, how they respond, their profitability generation of customer analyses supporting operational and strategic marketing decisions interaction with customers offering the most appropriate services through the right channel in each individual case

5 MARKETING DATAWAREHOUSE the solution adopted Management Data ERP Data Web Data External Data Integration Unique customer identification Data audit Applications Data warehouse Data Mart Mining Data mart sales reporting Behavioral Segmentation Data Delivery Reports and ad hoc queries SAS Enterprise Miner Customer tables Churn Analysis Scoring system

6 SOME PRELIMINARY INDICATIONS The questions we need to answer: how many are our customers? Which are the market segments where they position themselves? Who are the best prospects for product and/or channel cross-selling? Who are the customers with greatest churn? The goal of the Customer Database Project is creating an environment for marketing analyses on BIPOP Group customers This environment requires data structures, data mining tools, qualified personnel capable of handling the entire process

7 THE STARTING POINT Management Details Staging Area Data Warehouse Current Accounts, Third-party Securities Asset under Management Data Mart Branch Targets

8 THE END RESULT Management Details Marketing Client Staging Area Data Warehouse Current Accounts, Third-party Securities Asset under Management Data Warehouse Plastic Cards, Financing, Services Data Mart Branch Targets Data Mart Mining

9 DATA MART MINING: WHAT IS IT FOR? How How II respond respond to to marketing marketing actions actions Which Which contracts contracts II made made and and for for how how long long Prod./Serv. Prod./Serv. which which BIPOP BIPOP offers offers to to me me How and and how how often often II use use How products and and services services products Who Who II purchased purchased from from Who Who II proved proved II am am All-round views views of of All-round customer behavior behavior customer Who Who II am am i.

10 DATA MART MINING: THE CUSTOMER MODULE How How II respond respond to to marketing marketing actions actions Which Which contracts contracts II made made and and for for how how long long Prod./Serv. Prod./Serv. which which BIPOP BIPOP offers offers to to me me How and and how how often often II use use How products and and services services products Who Who II purchased purchased from from Who Who II proved proved II am am All-round views views of of All-round customer behavior behavior customer Who Who II am am i.

11 DATA MART MINING: THE DATA MODEL E-money Customer deposits Customers Third-party securities Financing Accounts Insurance Debit Cards Credit Cards

12 DATA MART MINING: THE DATA MODEL E-money Customesr COD_GR COD_CLI Accounts COD_GR COD_CLI COD_CC MONTH BALANCE COD_GR COD_CLI COD_CC

13 DATA MART MINING: THE DATA MODEL Promoted products Target Customers Contacts Current Accounts Savings accounts Campaign Time Deposits Finance Customer Tables Insurance Customers Loans & Financing. Accounts Sales Organization Debit Cards Credit Cards Products Salaries Pensions

14 A PRODUCTION ENVIRONMENT FOR ANALYSES Data Mining Environment Standard analysis Ad-hoc analysis Sample Customer tables Assess Explore Model Modify Data Mart Mining Detail Tables Rules Lists of Customers Data Warehouse Campaign Planning & Treatment

15 THE FIRST CONCRETE RESULTS Behavioral Segmentation of retail customers Identification of Sleeping customers Analysis of lost customers

16 BEHAVIORAL SEGMENTATION OF RETAIL CUSTOMERS Goals of the analysis: summary classification of retail customers on the basis of their behavior to assess their individual potentials and carry out more targeted marketing actions on the basis of gathered intelligence. analysis of migration flows: a. to monitor migration patterns of sets customers from one segment to the other, b. to analyze the segments of customers who terminated their relationship with the bank c. to determine in which segments new customers position themselves.

17 4 VIPOP 3 Cadets 2 USE 1 To the Top 0-1 On the Edge Small Loyal Customers Traditional Piggy Bank WEALTH

18 IDENTIFICATION OF SLEEPING CUSTOMERS Goals of the analysis: Creation of a criterion for the assessment of sleeping customers Delivery of sleeping customer lists to branches for waking up actions

19 IDENTIFICATION OF SLEEPING CUSTOMERS Sleeping Customers by branch 0089 BRESCIA - BR.16 BIPOP-CARIRE Branches Cliente GESTIONALE CDG ANALISI Anagrafica Codice Apertura Età Anagrafica Codice Apertura Tipo CDG Matricola Fascia FACCHI FRANCESCO /09/00 29 FACCHI FRANCESCO /09/00 S 692 CC - Fascia 5 PASOTTI LUIGINA /09/00 45 PASOTTI LUIGINA /09/00 S 603 CC - Fascia 5 Updated as of 31/03/2001 page 3

20 THE NEXT STEPS DMM extension to include FINECO and online trading data Addition of external lists (prospects) Churn Model Scoring Models for Cross-selling Geo-marketing

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22 2001 a CRM odyssey How to find your way around a Customer Database Fabio Marchetti, Filippo Avigo - BIPOP CARIRE Alberto Saccardi - NUNATAC Abstract Two brands; three networks of financial consultants; a traditional branch network; virtual channels which saw an increase of over 700% in terms of both clients and total assets in the year 2000: these are the reasons behind the decision taken by the Marketing Service of the Bipop-Carire Group to develop a dedicated customer-centric data infrastructure. To build the Customer Database (CD) the enterprise data warehouse has been integrated with a marketing module for an all-round view of Group clients and a functional data model for Data Mining has been developed. However, not to get lost in a myriad of data and to undertake a proper CRM strategy require appropriate skills and tools to generate relevant market and customer intelligence from the CD. In this paper we will show how we approached and resolved the essential issues in the development of the CD and how we are using it: to instill trust in new clients attracted via virtual channels; to drive and measure BIPOP CARIRE CRM Campaigns; to produce a Profit and Loss statement for marketing activities.. Introduction. Bipop-Carire ranks within the top five Italian financial groups in terms of market capitalization and is considered one of the most innovative for its multi-channel approach and its strategy of expansion abroad. The Group is already present in Spain, Portugal, France, Ireland, Luxemburg, Switzerland, Germany and Austria and is expanding its operating strategy both directly and through joint ventures. Customer satisfaction is the mission of the Group. It is pursued through the offer of a wide range of products (mutual funds, investment trusts, life insurance, personal loans, leasing services and mortgages, but also conventional bank products and online trading) which are customized, with the support of advanced technological tools, to meet the needs of individual customer in every important moment of his/her life at best. Three networks of financial consultants (namely Bipop City, Fineco and Azimut which employ over 3,000 professionals), a network of 300 traditional branches and the virtual bank Fineco, the Italian leader in online trading, work together every day to achieve this ambitious goal. Nunatac is a consulting firm specialised in database marketing, comprising data warehousing and data mining for business purposes. Nunatac is focused on the provision of tailormade business solutions to its clients, using the SAS SYSTEM and is certified SAS Quality Partner. In the first part of this paper we will discuss the main issues dealt with in the development of the Customer Database project, in the second part we will introduce the business objectives that the Marketing Management of the BIPOP- CARIRE Group intends to pursue using the Customer Database. 1. The Customer Database Project: how to build a data environment for CRM. The purpose of the Customer Database project is to provide a CRM supporting System to be progressively implemented which enables BIPOP-CARIRE and its marketing organization to use a System and have the required skills to conduct analysis and profiling of Group customers/prospects. This System consists of: a data environment for data analysis called Data Mart Mining (DMM); 1

23 SAS Enterprise Miner templates for segmentation analysis, scoring and churning models. The Customer Database Project was based on an existing Data Warehouse (DWH) designed for monitoring net assets acquired through Group branches and financial planners. This facilitated many issues such as data integrity and certification. However, to use these data at customer marketing level required DWH integration with a module enabling customer identification and development of customer unique identification code (ID). In fact, building a data environment for marketing purposes requires proper identification of customers as logic business entities. Identification of individual customers by a unique ID is of paramount importance to avoid duplications and lost information. However this is not always easily manageable, especially when multiple customer master files exist and customer data are collected without any normalization and non-duplication validation. In the case of BIPOP, we have used tax numbers or VAT numbers to identify the marketing customer. This is an easy and at the same time efficacious criterion supported by data stored in the information management system. However it should be noted that use of the tax number avoids duplications only for existing customers (internal list) and not for prospects (external list). For the purpose of providing a complete picture of customer behavior the DHW has been expanded to include new types of products/services which had not been considered initially for measurement of net assets. Said products/services are: Debit/credit cards ; Revolving facilities; Services Mortgages; Personal loans. The DMM is BIPOP data environment for marketing analysis of Group clients. Therefore the DMM data model has been designed and developed to meet the following requirements: organized by area to deliver a clear and complete profile of characteristics which distinguish customers in a target marketing view, consistency with bank marketing logics: data organization by service/product area compliance with the marketing customercentric model and customer tracking, efficient data organization: data extraction, summarizing, joining. Compliance with said requirements in turns implies: building partly de-normalized detail data structures and de-normalized structures at customer number level, called Customer Tables; generation of a table containing descriptive information on bank accounts, e.g. opening date, closing date; statistical tables with behavioral data summarized on a monthly basis, e.g. transactions, amounts, balances; a de-normalized data model organized according to a hierarchical logic where each table contains its own key and the keys of tables which are at a higher level in the hierarchical organization ; duplication of data related to bank accounts and transactions at marketing customer level in case of multiple owners. 2. The Business Problem. A properly structured data environment, like the DMM, is the core in the implementation of a customer Relationship Management system. The next step in the implementation of CRM strategies is the creation of customer behavioral profiles and measurement of their propensity to buy a new product/service or terminate the relationship. At BIPOP the decision was made to give priority to behavioral segmentation of retail customers. In fact identification and quantification of clearly differentiated targets and historical analysis of performance in these segments provide the groundwork for the achievement of critical business objectives such as: assessment of potentials for offer customization; cross-selling; identification of targets ensuring profitability of certain specific marketing actions; provision of crucial information to those responsible for preparing the marketing plan; planning of and feed-back on customer loyalty strategies. 2

24 Segmentation is in progress and its results will be presented at the SEUGI 2001 conference in Florence. Fabio Marchetti BIPOP-CARIRE Via Leonardo da Vinci, , Brescia Italy Tel Fax Filippo Avigo BIPOP-CARIRE Via Leonardo da Vinci, , Brescia Italy Tel Fax Alberto Saccardi NUNATAC Via Crocefisso 5, 20122, Milano Italy Tel Fax