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SAS marketing analytics
Project background
The Client is a leading global technology company which also manages sales and marketing of its products through various channels like retail, online, direct sales, wholesalers and resellers.
The Client organization uses different datasets to help its business managers to take strategic & predictive decisions. The datasets help them to encapsulate growth, sustain business and understand effectiveness of demand generation and direct marketing activities / opportunities.
Key drivers
The enormous volume of historical data required for statistical analysis & simulation of the business system resulted in huge warehouse (more than 100 Terabyte and still growing) in the client environment. This in turn demands growing customization and re-engineering needs across the various portfolios to unify the heterogeneous systems processing EBCDIC, ASCII, and even direct from other databases. There was a need to develop and maintain analytic data mart which will allow the team to build variety of customer and marketing analytics.
Project scope
The scope included implementing, enhancing, migrating, system tuning and supporting SAS based analytic platform for marketing group. Several functions / enhancements were implemented using this framework for bringing the analytics closer to apple marketing strategy. .
Technology platform
Operating Systems : Unix, Aix, Windows-NT Server
Languages : Shell Scripting, SAS 9.1, SAS Macro, PL/SQL
Databases : SPDS 4.4, ORACLE 9i, TERADATA
Tools & Utilities : SAS Enterprise Guide, SAS Management Console
Domain Expertise : Retail, CRM (Data Warehousing), Marketing Analytics
Leverage your data for business advantage
Accessibility to high quality data improves decision making process radically. We have built the right combination of people and process to help our clients to successfully implement their BI strategies.
Project details
This analytic data-mart defined over SAS includes over hundreds of batch interfaces processing more than 35 million transactions per day and more than 50 scheduled extracts and with hundreds of analytic datasets, segments & reports. The analytic datamart components are as described below:
Real Time ETL Implementation
- Extract data from warehouse & loading into the anlytic Data mart on a daily basis to ensure real-time data available for business users to track today’s fast paced business.
Market Analysis & Data Mining
- Profiling and segmentation of retail outlets based on transaction history and trade area demographics.
- Transaction profiling based on transaction value and purchase time.
- Customized reports of customer data based on a variety of data, including transaction size, transaction value, recency and frequency of visits, items-returned history and overall profitability.
Track the metrics of retail operations
This case study is centered on how EXILANT helped the retail client to establish and improve reporting solution for their retail stores operation. The solution enabled the client to track the KPI’s of stores and also analyze the shopping trends.
Modeling & Scoring
- The process of using a model to make predictions about behavior that has yet to happen is called "scoring". It includes the algorithm (based on user behavior over certain period of time) to build models from historical data.
- Score the transactional data with the models to identify best email-able customers.
- Calculate the recency time (Time between which customer may back again for some kind of transaction) for each product segments and individual.
Benchmarking commercial website
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Migration from SAS/Oracle to SAS/Teradata
- Migrating SAS Data mart to support Teradata as Enterprise Data Warehouse (EDW), in response to EDW migration from Oracle to Teradata.
- Installing Teradata library in SAS & modify the production environment to be Teradata compliant.
- Modifying existing script according to Teradata architecture.
BASE SAS to SPD Server migration
- The scope of this change is to migrating SAS System from BASE SAS environment to SPDS Environment.
- The capabilities of SAS Scalable Performance data Server ensure that business intelligence and analytic applications maintain consistent performance and that extraction, transformation and loading processes do not exceed the time windows available as enterprise data continues to grow.
- Modifying existing script according to Teradata architecture.
Automating information management
EXILANT helped one of the state government intelligence agency to collate information from various sources, analyze and otify information to various subscribers. The solution enabled the agency to disseminate crucial information faster to the subscribing authorities.
Project results
As a result of the project, the users got an analytic environment with faster processing. This also saved time and data replication. The marketers were able to focus just on the data analytics in a fully controlled environment. As data is presented in business terms, non-technical users were able to perform search and choose the information they need without the confusion of data complexities.
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