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BI Consultancy - Data, Analytics and Strategy

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The presentation describes my views around the data we encounter in digital businesses like:
- Looking at common Data collection methodologies,
-What are the common issues within the decision support system and optimiztion lifecycle,
- Where are most of failing?
and most importantly, "How to connect the dots and move from Data to Strategy?"

I work with all facets of Web Analytics and Business Strategy and see the structures and governance models of various domains to establish and analyze the key performance indicators that allow you to have a 360º overview of online and offline multi-channel environment.
Apart from my experience with the leading analytic tools in the market like Google Analytics, Omniture and BI tools for Big Data, I am developing new solutions to solve complex digital / business problems.

As a resourceful consultant, I can connect with your team in any modality or in any form that meets your needs and solves any data/strategy problem.

Publié dans : Données & analyses
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BI Consultancy - Data, Analytics and Strategy

  1. 1. DATA STRATEGY
  2. 2. OUR Business OBJECTIVES
  3. 3. “We Build Experiences
  4. 4. “We Manage User Behaviour
  5. 5. “We Optimize Outcomes
  6. 6. WORKING AROUND DATA
  7. 7. DATA Planning Media Planning Social Listening Search Queries USER INTENT Research Web Analytics A/B testing UX & Usability USER VOICE Returns User Satisfaction Goal & Conversion ROI & Revenues RESULTS
  8. 8. Behavior DATA Planning Media Planning Social Listening Search Queries USER INTENT Research Web Analytics A/B testing UX & Usability USER VOICE Returns User Satisfaction Goal & Conversion ROI & Revenues RESULTS
  9. 9. Behavior DATA Planning Media Planning Social Listening Search Queries USER INTENT Research Web Analytics A/B testing UX & Usability USER VOICE Returns User Satisfaction Goal & Conversion ROI & Revenues RESULTS
  10. 10. Behavior DATA Planning Media Planning Social Listening Search Queries USER INTENT Research Web Analytics A/B testing UX & Usability USER VOICE Returns User Satisfaction Goal & Conversion ROI & Revenues RESULTS
  11. 11. Behavior DATA Planning Media Planning Social Listening Search Queries USER INTENT Research Web Analytics A/B testing UX & Usability USER VOICE Returns User Satisfaction Goal & Conversion ROI & Revenues RESULTS
  12. 12. DATA IS MYSTERIOUS
  13. 13. DATA: Light blue White Black Sleeveless Neck bow
  14. 14. DATA: Light blue White Black Sleeveless Neck bow
  15. 15. DATA on its own is NOTHING
  16. 16. It’s not just about DATA
  17. 17. but what it MEANS
  18. 18. &howitRELATES
  19. 19. totheOUTCOME
  20. 20. DATA DRIVES DECISIONS
  21. 21. DATA DRIVES DECISIONS
  22. 22. DATA DRIVES DECISIONS
  23. 23. The DATA that drives our DECISIONS
  24. 24. The DATA that drives our DECISIONS
  25. 25. High Volume High Quality The DATA that drives our DECISIONS
  26. 26. High Volume High Quality Behavioral Attitudinal The DATA that drives our DECISIONS
  27. 27. High Volume High Quality Behavioral Attitudinal Actual Artificial The DATA that drives our DECISIONS
  28. 28. High Volume High Quality Behavioral Attitudinal Actual Artificial systematic observations semi-structured collection The DATA that drives our DECISIONS
  29. 29. High Volume High Quality Behavioral Attitudinal Actual Artificial systematic observations semi-structured collection The DATA that drives our DECISIONS
  30. 30. THAT’S A LOT OF DATA
  31. 31. Quantitative WHAT happens and WHEN HOW it happens and WHY Qualitative
  32. 32. Quantitative WHAT happens and WHEN HOW it happens and WHY Qualitative
  33. 33. It is not much use to know WHAT is happening if you don’t know WHY
  34. 34. It is not much use to know WHAT is happening if you don’t know WHY You can’t know WHY things are happening if you don’t know WHAT is happening
  35. 35. Quantitative Top Down Analysis
  36. 36. What we want to measure KPIs / Key Metrics Collection of Data Analyze Metrics Benchmark Improve Quantitative Top Down Analysis
  37. 37. What we want to measure KPIs / Key Metrics Collection of Data Analyze Metrics Benchmark Improve Quantitative Top Down Analysis Bottom Up Analysis Qualitative
  38. 38. Quantitative Top Down Analysis Bottom Up Analysis Qualitative What we want to measure KPIs / Key Metrics Collection of Data Analyze Metrics Benchmark Improve Prove Hypothesis Collect Data Devise Experiment How can we improve? Why is this happening? Analyze existing trends
  39. 39. What we want to measure KPIs / Key Metrics Collection of Data Analyze Metrics Benchmark Improve Prove Hypothesis Collect Data Devise Experiment How can we improve? Why is this happening? Analyze existing trends Quantitative Top Down Analysis Bottom Up Analysis Qualitative
  40. 40. What’s in the Middle? What we want to measure KPIs / Key Metrics Collection of Data Analyze Metrics Benchmark Improve Prove Hypothesis Collect Data Devise Experiment How can we improve? Why is this happening? Analyze existing trends
  41. 41. What we want to measure KPIs / Key Metrics Collection of Data Analyze Metrics Benchmark Improve Prove Hypothesis Collect Data Devise Experiment How can we improve? Why is this happening? Analyze existing trends What’s in the Middle?
  42. 42. DECISIONS What we want to measure KPIs / Key Metrics Collection of Data Analyze Metrics Benchmark Improve Prove Hypothesis Collect Data Devise Experiment How can we improve? Why is this happening? Analyze existing trends What’s in the Middle?
  43. 43. Till now, > How Business Intelligence works > BI approach and methodologies towards DATA > What informs our decisions
  44. 44. IT WAS SIMPLE
  45. 45. IT WAS SIMPLE
  46. 46. What we want to measure KPIs / Key Metrics Collection of Data Analyze Metrics Benchmark Improve Prove Hypothesis Collect Data Devise Experiment How can we improve? Why is this happening? Analyze existing trends What’s in the Middle?
  47. 47. REPORTS What we want to measure KPIs / Key Metrics Collection of Data Analyze Metrics Benchmark Improve Prove Hypothesis Collect Data Devise Experiment How can we improve? Why is this happening? Analyze existing trends What’s in the Middle?
  48. 48. APPROACH DATASOURCE Adapted from work of Christian Rohrer 2008 X Multivariate (live A/B) testing X Eye Tracking X Usability Lab Studies X Customer email Feedback X Intercept Surveys X Data Analysis / Mining X Live UX assessments X Participatory Design X Focus Groups X Card sorting X Desirability studies X social Listening solutions X Message board mining X Email Surveys
  49. 49. ?
  50. 50.
  51. 51. BI Solutions Directing Metrics to Strategy
  52. 52. SHIVAM
  53. 53. Parting Notes Connect with me asking ‘How do we… Bridge cultural gaps Design and Manage integrated web teams Develop DATA reliance with reliable data Generate analytical awareness Improve on tools, methodologies and standards
  54. 54. THANKS Follow me @ShvmDhwn More Here… Connect -

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