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Big data analytics primer for w2 e startups

Big data analytics primer for w2 e startups

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When It Comes to Data Analytics, Ignorance Is Not Bliss. As an entrepreneur you can not afford to not have a basic understanding of this technology. Using good analytics enable you to make decisions using facts, without which, you’re operating off of gut instinct. And there is not a single aspect in your entrepreneurial journey from ideation to exit where you can not use this beautiful technology.

When It Comes to Data Analytics, Ignorance Is Not Bliss. As an entrepreneur you can not afford to not have a basic understanding of this technology. Using good analytics enable you to make decisions using facts, without which, you’re operating off of gut instinct. And there is not a single aspect in your entrepreneurial journey from ideation to exit where you can not use this beautiful technology.

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Big data analytics primer for w2 e startups

  1. 1. Big Data and Analytics Do I need it ??
  2. 2. The Top guys use it…
  3. 3. It is Favourite closer home too .. • Flipkart/Snapdeal /Amazon – – predict market trends based on user behaviour, click data and information from social media, algorithm to rank sellers. – uses high-end analytics and algorithms in a number of areas such as recommending relevant products to users, showing users relevant search results, displaying ads to users that they are very likely to click on, predicting future demand for products, detecting spam reviews and detecting fraudulent orders • Make my trip/ Ceartrip – – Targeted mailers, personalization in search results
  4. 4. One of the hottest start-up skills.. 1. Software engineer 2. Account Manager 3. Data and Analytics professional 4. HR and Talent acq professional 5. Product mgr
  5. 5. Almost a fifth of these are closely related to analytics and data management And is equally critical for large Organizations
  6. 6. But Do ”I”need it ?? (I am still a startup …)
  7. 7. What is analytics – 1.0 • Market research – Who will buy my product – At what price – Who are my competitors – How much funding does my venture need – When will I breakeven • Data collection • Data cleaning • Tabulation • Correlation and regression • Advanced data analysis – Factor analysis, PCA, Conjoint, etc • Forecasting
  8. 8. What is analytics – 1.0 • Customer insight – Who is my customer / which are the customer segments – What is she/they using my product for – How is consumption of my product growing – When will I reach a targeted consumption level • Data collection • Data cleaning • Tabulation • Correlation and regression • Advanced data analysis – Factor analysis, PCA, Conjoint, etc • Forecasting
  9. 9. What is analytics – 1.0 • Product insights – Product comparison – Geographical trends • Data Visualization – Understand data better – Use data to aid decision making • Data visualization • Charts and plots • Data interpretation
  10. 10. Analytics 2.0 • Advanced customer segmentation – Create previously unknown customer segments – Create better customer understanding • Advanced forecasting – Time series forecasting, seasonality impacts • Clustering (supervised, unsupervised) • Time series modelling • Forecasting techniques
  11. 11. Analytics 2.0 • Recommendations and personalization – What will a particular customer buy next – Offer targeting – When is she likely to move to my competitor – What offer is likely to prevent churn • Predictive modelling • Churn modelling • Machine learning • Big Data analysis
  12. 12. Analytics 2.0 • Fraud prevention – Revenue leakage – Fraud detection and prevention • Fraud detection techniques • Machine learning
  13. 13. Common tools for Analytics Tool Application 1 MS Excel Data manipulation, visualization, Data Tabulations, Correlation and regression, What if analysis 2 MS Access Large data manipulation 3 SQL Even larger data manipulation 4 R / SAS/ SPSS Advanced data analysis, Predictive modelling, Clustering 5 Python / Java/ C Real time data analysis, Big data manipulation 6 Qlik sense / Qlik view / Power BI Visualization and reporting
  14. 14. Case study
  15. 15. ENOUGH GYAN … LETS DO SOME REAL STUFF
  16. 16. Concluding … 1. Start small , scale as needed 2. Cultivate data skills 3. Bring in experts 4. Business first 5. Don’t follow the crowd
  17. 17. THANKS May Data be with you …
  18. 18. Speaker Details Cultivate data skills 1. Bring in experts 2. Business first 3. Don’t follow the crowd
  19. 19. Concluding … Ajay Piwhal CEO & FOUNDER, Prizmatics https://www.facebook.com/ajay.piwhal https://twitter.com/ajayPrizmatics https://in.linkedin.com/in/ajaypiwhal

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