How Big Data Impacts Strategy and Marketing
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This document discusses big data and its impact on strategy and marketing. It begins with definitions of big data and introduces some key principles. Some differences between big data and small data are outlined. The document then discusses the big data value chain and workflow. It provides examples of how Target and EGI have used big data successfully. Finally, it discusses how small and medium businesses can leverage big data and provides some key takeaways.
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How Big Data Impacts Strategy and Marketing
- 1. C.K.Kumar What it means for Strategy & Marketing @SupraMBA #PCATX11 The Big Deal with Big Data
- 2. Big Data : Big Deal C.K. Kumar What is Big Data ? Big Data vs. Small Data Big Data – Impact on Strategy / Marketing Case Studies Big Data and SMB Agenda
- 3. Big Data : Big Deal C.K. Kumar Big Data – a definition "Big data refers to things one can do at a large scale that cannot be done at a smaller one.” :Victor Mayer – Schonberger & Kenneth Cukier Authors
- 4. Big Data : Big Deal C.K. Kumar Big Data – a small Introduction Doug Laney, Gartner, 2001 Martin Hilbert, USC
- 5. Big Data : Big Deal C.K. Kumar Big Data – Guiding Principles All the data, all the time Trade accuracy for insight What, not Why Based on Victor Mayer – Schonberger & Kenneth Cukier
- 6. Big Data : Big Deal C.K. Kumar Big Data vs. “Small” Data Big Data should NOT defined by size. Size is incidental ! Criteria Small Data Big Data # of Data Points Limited ~All # of Data Sources Few Many Sampling Expensive, Accurate No Sampling Data Type Structured All Types
- 7. Big Data : Big Deal C.K. Kumar Bruce Reading, VoltDB Big Data Value Chain
- 8. Big Data : Big Deal C.K. Kumar Big Data Work Flow Data Sources Structured Semi-structured Unstructured Physical Virtual Contextual Data Collection Performance Deduction Inference Prediction Analyses Options Prevention Recommendation No Action Decisions Technology Oriented Business Oriented Based on R. Wang & Insider Associates
- 9. Big Data : Big Deal C.K. Kumar Big Data to grow from $3.2B in 2010 to $16.9B in 2015 - IDC 68% of Marketers expected to increase spending on data - Forrester Research
- 10. Big Data : Big Deal C.K. Kumar Big Data’s Impact on Strategy Based on McKinsey Articles on Big Data
- 11. Big Data : Big Deal C.K. Kumar Big Data’s Impact on Marketing
- 12. Big Data : Big Deal C.K. Kumar Big Data in Action - Target Inflexion in Buying Correlation Track and Engage Test Feedback loop Success!
- 13. Big Data : Big Deal C.K. Kumar Big Data in Action - EGI Pre-eminent in E&P Research Archival and Real-Time big data iCORDS™ Data Platform Potential impact to E&P Industry
- 14. Big Data : Big Deal C.K. Kumar Big Data & SMB Source: The METISfiles 2012 Data - Driven Goals Strategic Marketing Scale without Mass Byte Inventory Datafy
- 15. Big Data : Big Deal C.K. Kumar Big Data – Key Takeaways Big Data is creating new opportunities Fragmented ecosystem will mature Perpetual Value : Data Insights Actions Data Pre-emptive, Ultra-customized Product / Service Big Data strains societal morals / ethics
- 16. Big Data : Big Deal C.K. Kumar Thank You
Editor's Notes
- http://www.apcon.com/big-data-in-action-/https://www.youtube.com/watch?v=EsVy28pDsYo – BBC Age of Big Data
- André Gide, ‘Everything has been said before, but since nobody listens we have to keep going back and beginning all over again.’ –
- Here’s a taste of what Netflix is collecting, and how much:More than 25 million usersAbout 30 million plays per day (and it tracks every time you rewind, fast forward and pause a movie)More than 2 billion hours of streaming video watched during the last three months of 2011 aloneAbout 4 million ratings per dayAbout 3 million searches per dayGeo-location dataDevice informationTime of day and week (it now can verify that users watch more TV shows during the week and more movies during the weekend)Metadata from third parties such as NielsenSocial media data from Facebook and Twitter
- Small, Simple and Slow Large, Complex and Fast
- Statisticians take over baseball scouts – Sophisticated analysis beats gut instincts. Certainty was based on sentiment rather than science.Mastercard aggregates / Analyzes 65B transactions from 1.5B cardholders in 210 countries. Filling up at 4:00 p.m. , spend $35 - $50 bucks at a grocery store or restaurantObama For America – The most response on e-mail title was “Hey”Amazon on an item –to-item collaborative filteringInform, not explain
- Any key strategic imperative would consist of 3 key things – Improvement – product quality, product velocity, service, customer satisfaction Optimization – Processes, products, customers, peopleReduction – in costsA Road Map for Analytics in the Big Data WorldWe all know that the market for Big Data software continues to grow. The big players are getting bigger through internal development and selected acquisitions. And, start-ups are popping up faster than popcorn pops. Here is an overview of the market segments:1) Capture and Storage: The volume of unstructured, semi-structured, and structured data continues to explode. All this data needs to be stored in the Cloud or on local servers in a way that is recoverable. This level of analysis is about what do I have and where is it. This segment will be dominated by big vendors such as IBM, Oracle, SAS, and, perhaps, semi-open sourced software like Hadoop.2) Add value though data analytics: Once you have the flood of data captured, it needs to be analyzed. This is a matter of indexing, counting instances, correlating, answering the very basic question of "what is here?" This segment today is a combination of small start-ups and the big vendors. IBM, Oracle, and SAS will increasingly penetrate this segment through acquisition and internal development.3) Add more value through forward-looking analytics: Once you have summarized what is in the database, there are specific market-driven questions that need to be answered: What will they buy next? When will the engine wear out? How much power will be consumed in the next four hours? Where will I get the faster return on my oil well placement? What are the antecedent conditions for arthritis? The list of potential predictive questions to be answered will grow daily. To be a vendor in this segment will require deep domain experience/knowledge. The large vendors may select a segment to penetrate (e.g., IBM in the medical space), but small vendors from the specific industry will dominate.