Answering Why, How and What question about predictive analytics.

1. Rudradeb Mitra
https://www.linkedin.com/in/mitrar/

2. Overview: Why, How and What
•Why is prediction important?
•How can you do predictions?
•What predictions to do?

3. Why?

4. What is Predictive Analytics?
“What is likely to happen”

5. Why is that important?
Current Analytics Approaches:
Past data and trying to optimize
Predictive Analytics:
What can happen in future

6. Two use cases

7. Most important metric of any firm?
“total of lifetime values of all your current and future
customers – the sum total of all the value you'll ever
realize from customers”
Customer equity

8. The biggest question startups face?
How much is someone willing to pay for my service or
product?

9. If you know…
•How much person X will buy tomorrow, next week, next
month and next year?
•Compare X vs Y
•Where to spend our marketing and sales budget?
•Where to get more customers than person X and less like
person Y?

10. In short…
Mother of all Business Intelligence

11. But it is complex
•Esp. for transactional behaviors like ecommerece
•Depends on various factors like weather, political
situation, time….

12. How?

13. How can you use data to derive
insights?
•Regressions or mathematical models
•Deep Neural Networks

14. Deep Neural Networks

15. A use cases

16. vdts
product_id
user
_id
eval_se
t
order_num
ber
order_do
w
order_hour_of_d
ay
days_since_prior_ord
er
2539329 1 prior 1 2 8
2398795 1 prior 2 5 7 15
473747 1 prior 3 7 12 20
22544786 1 prior 4 1 7 21
4215438 1 prior 5 3 15 28
2295261 1 prior 6 2 7 19
2295261 1 prior 7 6 20 20
2550362 1 prior 8 5 14 14
1187899 1 prior 9 2 16 0
2168274 1 prior 10 2 8 30
1501582 1 train 11 1 11 10
Instacart Data - 2M order data

17. 2539329
2398785
473747
2550368
1187899
(Product ID)
Predicted product ID
Existing approach

18. What is missing?

19. Recurrent Neural Networks

20. Zalando - use case
https://tech.zalando.com/blog/deep-learning-for-understanding-consumer-histories/

21. What?

22. What kind of predictions to do?
1. How to use data to better target customers?
2. How to use big data that creates value for
customers?

23. Three questions every business must ask
What types of future information will help my customers
reduce their costs or risks?
- Discount information

24. What type of future information would yield new insight
if aggregated?
- Credit score
Three questions every business must ask

25. Will benefit from aggregating others’ data with theirs?
- Bank loan
Three questions every business must ask

26. Conclusion
•Predictive Analytics is the future of Business
Intelligence
•Focus on adding value to your customer

27. Questions?