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InData Labs. How we leverage Big Data - 5 use cases

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Wondering what InData Labs is all about? Check out the presentation explaining how our team combines technology and data science to make sense of big data and help businesses implement data-driven decisions.

Contents:

2 slide: About InData Labs:
Leveraging the latest big data technologies with a highly professional & talented team of data engineers, statisticians & mathematicians, we help our clients solve high impact business problems

3: Our solutions:
• Big Data strategy consulting.
• Big Data platform engineering and technical support.
• Data Science: High-end predictive analytics solutions.

4: Leverage advantages of MoneyGraph product to strive your business forward:
• Process social data
• Precise segmentation
• Trending topics monitoring
• Finding opinion leaders

5-11 slides: We master the following cases:
• A/B testing
• Customer churn
• Personalized product offerings
• Real-time fraud detection
• Risk management

indatalabs.com

Published in: Business
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InData Labs. How we leverage Big Data - 5 use cases

  1. 1. Ascertain & implement data-driven business decisions
  2. 2. About InData Labs Big Data consulting - engineering & predictive analytics services company. Our team is a top-notch mix of business experts/smart guys (data science + distributed engineering). On-premise R&D Data Science Laboratory - Master`s & PhD graduates in applied mathematics. Solving high impact business problems for our clients in Finance & Banking, FMCG & Retail, Media & Entertainment, Telecom.
  3. 3. Our solutions Big Data Strategy Consulting 1. Capability requirements & data identification 2. Use cases definition & prioritization 3. Architecture design 4. Road Map elaboration 5. Strategy report delivery Engineering 1. End-to-end deployment and management of Big Data platform 2. Big Data integration services 3. System engineering & technical support services Data Science • High-end predictive analytics solutions, customized for each particular case • Statistics, mathematical models & algorithms developed and deployed by our data scientists
  4. 4. Accelerating with internal products: MoneyGraph MoneyGraph: • process social data and custom database information • improve communication through precise segmentation • track trending topics • detect and engage opinion leaders among your customers
  5. 5. A/B testing#1 Customer churn analysis Personalized product offerings We are proficient at: #2 #3 Real-time fraud detection#4 Risk management#5
  6. 6. Use Case #1 A/B testing (e-commerce) • Use A/B testing to improve specific business problems – increasing amount of impression in ad network, test a new look and feel of mail list in order to receive more conversion • Implement A/B testing with minimum amount of potential loss; choose user base for A/B carefully in order to get full insights Example The e-commerce shop performs hundreds of concurrent A/B tests analyzing billions of records in each test of new feature implemented by UX or development team. It verifies that a new feature improves customer experience. The A/B testing system also checks marketing hypothesis against real customer user experience. When marketing is not sure about look and feel of video player, A/B testing verifies hundreds of small changes to receive customer recognition of changes based on actions. It will help management to take a concrete decision on how the video player should look like. A/B
  7. 7. Use Case #2 Customer churn analysis (e-commerce) • Conduct behavior analysis • Prevent customer dissatisfaction & keep your customers • Learn the right steps to implement in order to meet customer needs and save your most profitable customers Example Being close to finalize purchases via an online-shop, a client suddenly changes his behavior. The client has selected certain products and filled the product basket… but then - no action on the page happens. The system identifies that the client has loaded pages of other online shops for prices comparison. Using factor analysis the system identifies potential churn automatically, and the customer gets a phone call (e-mail message) informing of a special discount and asking – how the shop could be improved.
  8. 8. Use Case #3 Personalized product offerings (telecom) • Customer segmentation - understand client buying patterns, their most preferred channels and influencers • Identify the next best offer for segmented customers • Create targeted marketing campaigns to segmented customers Example Based on social networks activity analysis we get insight that the client has just married and offer him a special offer for calls with members of his family at very attractive rates.
  9. 9. Use Case #4 Real-time fraud detection (banking) • Analyzing points of sale, transactions & other data points • Distinguish fraudulent activity from normal activity • Detect, prevent & eliminate internal & external fraud Example Potential fraud transaction appears using credit card of the client abroad. We combine details of this transaction with the client`s historic data, as well as authorized third-party data, e.g. client`s social networks activity, and mobile phone location. This enriched analysis increases fraud risk identification in real-time. In case of a high risk, we inform the client about it.
  10. 10. Use Case #5 Risk management (banking) • Determine risk & exposure based on simulated market behavior, scoring customers and potential clients • Comply with regulatory requirements & evaluate credit exposure Example Client would like to raise his credit limit at internet banking private account. We propose optimum credit limit increase real-time, based on matching other clients with the similar profile raising limits history. If the client wants to get a loan, we help banks reach higher credit scoring accuracy. For that we combine data from traditional loan applications and local credit bureaus with other information from online sources (social media, blogs, Google search, etc.)
  11. 11. info@indatalabs.com www.indatalabs.com

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