big data for retail
DESCRIPTION
The retail industry is at the forefront of the Big Data revolution, with every point-of-sale transaction, website click, or social media post potentially revealing an insight into the customer’s preferences and buying behaviour. The capability to harness this information effectively to provide optimal pricing and enhanced customer experience can be a game-changer for retailers.TRANSCRIPT
Organizations are increasingly grappling with the “Big Data” problem. What is Big Data? How did “Data” evolve into “Big Data”?Smart devices, improved Internet connectivity, Social Media, and cheaper storage have contributed to a significant increase in the volume, velocity and variety of data generated every single day. Almost 80% of this data is unstructured – photos, videos, sound, media, e-mail, social feeds, blogs, locations, appliance sensors, text messages, and more. This “Big Data” is an incredible source of intelligence for organizations and a potential source of competitive advantage.
The retail industry is at the forefront of the Big Data revolution, with every point-of-sale transaction, website click, or social media post potentially revealing an insight into the customer’s preferences and buying behavior. The capability to harness this information effec-tively to provide optimal pricing and enhanced customer experi-ence can be a game-changer for retailers. The best way to unlock the power of this data is to collaborate with an innovative, established IT partner that will extract maximum benefits from Big Data solutions, and deliver value-added business insights. Syntel’s Big Data Innovation Lab has built solutions around the pioneering open source platform—Hadoop—to empower its retail clients with valuable insights.
enable you to acquire, organize, and analyze Big Data in conjunction with traditional enterprise data to drive business value.
Our services have enabled clients to:
Transform key business processes in market-ing, merchandizing, and supply chain
Gain customer insights to enable personali-zation and influence purchase decisions
Improve profitability through dynamic real time pricing
Speed up reporting, analysis, and modeling
SYNTEL
BIG DATA SERVICES
Capitalize on changing market dynamics—predict trends and prepare for future
Identify business use cases with measurable outcomes
Start with existing data for quick successes
Build on small successes and integrate with transactional applications and web portals
OVERVIEW OF THE
BIG DATA INNOVATION LAB’S APPROACH
Develop organization-wide Big data strategy
Select the right tools and architecture for implementation
Run Project in sprints, with tangible and measurable outcomes
BIG BENEFITSFOR THE RETAILINDUSTRY
BIG DATA
CLIENT SITUATION
SYNTEL SOLUTION
Improved Customer Insight for Online Retail Store
BIGDATALeverage
Syntelits Retail ClientsHow does help
BUSINESS VALUE
CLIENT SITUATION
SYNTEL SOLUTION
Personalized End-user Experience for Retail Store
BUSINESS VALUE
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SYNTEL̀ S
BIG DATA INNOVATION LAB
• Offering end-to-end Big Data services from data management, information delivery, to information lifecycle management• A dedicated team of technical and business domain experts with hands-on experience in developing and deploying Big Data solutions• Cost-effective solutions to manage and integrate data to derive insights for decision support• Product capabilities, tools, accelerators, and frameworks to create tangible business value for clients
For more information, visit us at http://www.syntelinc.com/Bigdata.aspx or call us at US: +1(248)-619-3503, UK: +44(207)-636-3587
• One of the largest online home improvement specialty retailers in the US
• Teradata-based business warehouse could capture and store web-click history for 6 months only
• Limited ability to leverage historical data to improve product offerings and increase profitability
• One of the largest online home improvement specialty retailers in the US
• Inability to identify unique customers and preferences due to duplicate customer records and limitations of their legacy system
• Needed a technology solution to store millions of customer records, interface with third-party services, and identify duplicate and unique customers
• Re-architected the data model to store raw data and perform aggregation in Hadoop with aggregated results moved to Teradata
• Developed scalable and cost-effective Big Data solution to track and analyze the click stream using:
• HDFS, a Hadoop distributed file system• Hive, an SQL-like interface that abstracts complexities of Map-Reduce• Cassandra, a distributed columnar NoSQL datastore
• Single source of truth for customer definition
• Enhanced ability to provide a personalized end-user experience
• Peer-to-peer architecture eliminated single point of failure and reduced application downtime
• Client saved $1 million by migrating from legacy database (mainframe processing cycles) to Hadoop
• Reduced batch job processing time due to lower processing requirement
• Focused targeted marketing for better customer satisfaction
• Ability to derive timely insights from large historical dataset
• Client saved $500,000 by migrating from commercial data warehouse to HDFS
• Faster response from BI team to business user’s requests
• Enhanced customer conversions with cross selling ability
• Migrated data feed to HDFS and processed it on Hadoop
• Implemented Hive for data cleansing • Leveraged data science techniques to develop business logic for identifying unique customers using Map-Reduce framework