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.

1. Big Data and Analytics
Do I need it ??

2. The Top guys use it…

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. 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. Almost a fifth of
these are closely
related to analytics
and data
management
And is equally
critical for
large
Organizations

6. But Do ”I”need it ??
(I am still a startup …)

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. 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. 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. 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. 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. Analytics 2.0
• Fraud prevention
– Revenue leakage
– Fraud detection and prevention
• Fraud detection
techniques
• Machine learning

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. Case study

15. ENOUGH GYAN …
LETS DO SOME REAL STUFF

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. THANKS
May Data be with you …

18. Speaker Details
Cultivate data skills
1. Bring in experts
2. Business first
3. Don’t follow the crowd

19. Concluding …
Ajay Piwhal
CEO & FOUNDER, Prizmatics
https://www.facebook.com/ajay.piwhal
https://twitter.com/ajayPrizmatics
https://in.linkedin.com/in/ajaypiwhal