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Stephenson big data utrecht 2017

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Building an analytics team - The six skill sets you’ll need
David Stephenson

Published in: Data & Analytics
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Stephenson big data utrecht 2017

  1. 1. 6 skill sets David Stephenson, Ph.D. david@dsiAnalytics.com Hilversum Staffing your analytics team
  2. 2. Strategic Planning for Analytics Business Goals Analytic Projects Data Technology Staffing 3
  3. 3. Stage 1: Data Beats Opinion 4 Is my marketing spend effective? Why is revenue 20% below budget? How is my website traffic?
  4. 4. Business Goals Analytic Projects Data Technology Staffing Maximize marketing ROI Understand revenue streams 5 Stage 1: Basic Data Analysis
  5. 5. Sales Strategy Finance Marketing OperationsIT Stage 1: Business Analysts 6
  6. 6. Stage 1: Data Beats Opinion 7 Is my marketing spend effective? Why is revenue 20% below forecast? How is my website traffic? How can I improve my website?
  7. 7. 8 Stage 1: Basic Data Driven Approach Track use of website and apps Tagging and analysis of web site and mobile apps Web analytics data Web analytics tool (Google Analytics, Omniture, etc.) (Web) analyst
  8. 8. Sales Strategy Finance Marketing OperationsIT Web Analytics Stage 1: Business Analysts 6
  9. 9. 10 How are KPIs such as traffic and sales changing over time ? Can I understand and steer customers across all touchpoints? Can I make real-time reports and self-service data tools available across my organization? Stage 2: Bigger Questions Long-term view Breakdown of data silos Enterprise use of data
  10. 10. Dashboard Visualizations
  11. 11. Visualization Slide Here 8 Pareto Chart
  12. 12. Visualization Slide Here Geographic Overlays
  13. 13. 14 Stage 2: Approach for Bigger Questions Business Goals Analytic Projects Data Technology Staffing Ability to access and analyze detailed historic data Centralize records of all customer interactions Real time, scalable reporting and business analytics
  14. 14. Web Analytics Stage 2: Data Warehousing and Reporting (BI) 10 Sales Strategy Finance Marketing OperationsIT Business Intelligence (BI) Storage Visuals
  15. 15. 16 How can I customize product recommendations for each visitor? How can I prevent valuable customers from leaving? Can I forecast future demand for my products? Stage 3: Data Science and Big Data
  16. 16. Business Goals Analytic Projects Data Technology Staffing Customers quickly find products that appeal to them Recommender Engine Product features Click Stream Sales records Retain valuable customers Churn analysis Customer profiles Multi-touchpoint data Historic churn data Forecast product demand Statistical model or deep learning Web analytics data Social media data Sales data 17 Stage 3: Data Science and Big Data
  17. 17. Data Science Big Data Platform Sales Strategy Finance Marketing OperationsIT Web Analytics Business Intelligence Storage 2 1 3 Visuals 4 5 Stage 3: BI, Big Data and Data Science 13
  18. 18. 3-6 months 1year3year ContinuedA/Btests Analytics Road Map First Focus Area Second Focus Area Third Focus Area xxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxx xxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxx xx xxxxxxxxxxxxxxx xxxxxxxx xxxxxxx xxxxxxxxx xxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx xxxxxxxxxxxxxxx 6 Analytic Leadership 14
  19. 19. 2 Suggested Hiring Order Leadership for data and analytics program 1 Business Analysts 6 Web Analyst (Dedicated) 3 Date Warehousing Experts 4 Visualization Experts (Reports and Dashboards) 5 Data Scientists (Machine Learning, Statistics, etc.) 15
  20. 20. 21 Contact david@dsiAnalytics.com @Stephenson_Data

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