4 June 2007

The client is an established bank providing a complete range of accounts and services including liabilities, assets, cards and direct banking. It has more than 499 Branches spread across 219 cities in India and possesses more than 1054 ATMs with 1.2 million credit card and 3.9 million debit card customers. The current banking industry, particularly at regional level, is witnessing a heightened demand from customers for more personalised services. With plenty of choices in hand, customers can easily move to the best service provider within no time. This changing trend has enforced the regional banks to ably understand the changing customer needs and behaviour from time to time.

The client was in need of technical support that would streamline its existing analytical marketing processes by addressing various legitimate concerns like significant data preparation, insufficient latency and retention periods, management of customer details and other external data.

The client engaged Satyam to provide an analytical marketing data architecture based on assessed recommendations, data elements required for analytical marketing along with data source mapping and high level transformation, technical components that enables to use analytical marketing data elements effectively and a customer activity record to with the help of the customer intelligence module of iDecisions.

This solution helps the client to improve its bottom lines by working with 'what if' corrective scenarios, facilitating the client to benchmark itself against competitors.

The Customer Activity Record (CAR) is treated as a sandbox of data elements. It stores all analytical marketing data elements inclusive of role up and transformed data that is usable for analytical marketing activities like customer segmentation, customer value and customer behaviour. It also collects the required data elements that are owned by other user groups.

IDecisions' customer intelligence, on the whole would operate on 80:20 rule ensuring the minimal manual intervention. The solution has all the challenging capabilities to handle various analytical issues like predictive modelling, behavioural segmentation, lifetime values, customer metrics, product roll-ups, revenue summaries, cross/up sell opportunities etc.

The architecture with its unique technical components facilitates a trouble- free migration and transformation of data at various levels. As a part of data acquisition process, data is pulled from various operational data sources in to ODS and Enterprise data warehouse The staging area acts as an intermediary layer at which all the source data is collated for loading into the data warehouse. iDecisions contains the detailed specifications for the staging area, including data element definitions and formats.

The transformation and roll-up of data is implemented with the help of ETL tool on daily basis according to appropriate subject areas. It is treated as a single source of data and manages the issues pertaining to data versioning. The weekly refresh of data is implemented as an intermediate step avoiding insufficient latency of data.

The Analytical Marketing Data elements in CAR are provided with a Relational LAP (ROLAP), an end user access layer tool. iDecisions contains pre-delivered analytical templates that can be delivered on this layer. This layer facilitates to transfer the processed data into CAR and group them into required analytical templates. It also supports the end users with unrestricted slice and dice capability, so that the end user can extract the needed information directly from the specific template without delay or any additional effort.

The client has seen considerable benefits from the implementation including significant reduction in data preparation time and unrestrained slice & dice capability to end-users by providing required analytical marketing data elements with a Relational OLAP (ROLAP).

Issues pertaining to insufficient latency for analytical marketing campaigns are dressed with high priority and the subject-wise grouping of data facilitating fastest retrieval.

The period for analytical marketing data elements has increased to a minimum of 36 months and external data is now available for analysis.