This document discusses analytics and data-driven strategies through various case studies. It describes how Harrah's casinos analyzed customer data to find that their most valuable customers were frequent, middle-aged slot players, not high rollers. It also discusses how the Oakland A's used analytics to find undervalued metrics like on-base percentage. The document advocates applying a data-driven approach across industries to improve customer experience, sales, and operations.

1. Analytics - A way of life
Ankit Chaudhary
UpGrad Xchange, IIIT Bangalore
21st May, 2017

2. What gets measured, gets analysed
What gets analysed, gets acted upon...

3. What is analytics?
The art of thinking through data…
What is impact analysis?
What are success metrics?
What are KPI’s, how to define them?

4. The beauty of data...
Harrah’s game changing strategy
Problem landscape:
● Lot of cross visits were happening
● Unable to replicate Vegas like themed properties
● Lower retention rates and increasing competition
● Multiple properties with different marketing strategies

5. Some key data insights:
On average Harrah’s customer spent 36% of gaming dollars with them
26% of the customers produced 82% of the revenue
‘Best’ customers were not the high rollers
They were slot-playing middle aged players -- doctors, lawyers, bankers and
retired teachers
They often did not stay at the hotel but visited in the evening for a game or two
(So Harrah’s gave them free meals as compared to a free night stay at the

6. Learning from Harrah’s case
● 3 key metrics for casino’s
○ Acquisition: NPS/Loyalty: Retention
● 80:20 rule - Keep an eye on who your customer is, user pattern and habits
● Tailor your marketing plans, retention plans as per the customer needs
● Focus on CLTV (Customer Lifetime Value)
● Strategize to increase customer share (of the pie)

8. Oakland A’s:
Out of the box
approach!

9. Oakland A’s:
The magic of
Data!

10. Key learning from Oakland Athletics...
Key data insights:
● Getting on base is highly correlated with winning games
● Pitching is important but not a game changer
● Fielding is over-rated
Lessons:
● Asking the right questions?
● Biases cloud judgement and prevents success
● Don’t be a dinosaur - be agile and flexible, open to experiment and testing

11. Obama’s 2012 Election victory
“There’s always been two campaigns since the
Internet was invented, the campaign online and the
campaign on the doors. What I wanted was, I
didn’t care where you organized, what time you
organized, how you organized, as long as I could
track it, I can measure it, and I can encourage you
to do more of it.”
- Jim Messina, President Obama’s 2012 campaign manager

12. Use of data in real world
● Enhancing customer experience (NPS, CSAT)
● Improving sales conversion
● Resource planning and forecasting
● Pricing decisions
● Support and Operations management
● Product funnel optimization
● Marketing ROI and dashboards
● Balanced scorecards and business metrics

13. Practical case study - ClearTax
Sales optimization, increasing sales conversion from 12% to 20%
Problem statement?
Importance of logging correct data points and product/channel/source wise
attribution
Rep wise resourcing and clustering
Category level approach and engagement strategy
Reporting and creation of required dashboards

14. Careers in analytics & required skillsets
● Business/marketing Analyst
● Data Analyst
● Business Analysis Manager
● Data Scientist: tech oriented role (data modelling and stats)
● Data Engineer: coding oriented (Python, Scala, Java etc.), creating data
pipelines, optimizing data structures etc.
● Program Manager roles - Growth & analytics
● Operations Manager

15. Data thinking approach...
Have you read this article?
https://www.linkedin.com/pulse/linkedin-top-companies-2017-where-india-wants-
work-now-adith-charlie
Results?
Flipkart listed as the top company with Swiggy, Ola, CTS, McKinsey, HCL,
Vodafone, Oracle, Reliance, Tech Mahindra and others in the list.

16. Research criteria (as published by LinkedIn)
Job applications: At what rate are people viewing and applying to job postings
featured on LinkedIn?
Engagement: How many non-employees are viewing and asking to connect with
a company’s employees? How many professionals are viewing a company’s
career page? What's the reach and engagement of a company's content? How
are a company's follows performing? Etc.
Retention: Are employees sticking around for at least a year?
**500+ employees; included only actions taken in the 12 months ending in February

17. Uber customer experience
Problem statement and case description -
Design experience metrics from an end user point of view
Single person booking and no sharing of rides
Total working time: 15 mins
Take the required assumptions
Define a set of customer experience metrics
Be quantitative in your approach

18. Uber - key metrics (approach)
● Booking related metrics
● ETA metrics
● Maps related metrics
● Pricing and surge metrics
● Customer drop-off related metrics
● Cancellation and experience driven metrics
● NPS ratings
● Retention and engagement metrics

19. Uber - Take home case assignment
# 1 (KPI’s for UberPool)
→ What would be the user experience metrics for shared rides?
# 2 (Driver experience metrics)
→ Define experience metrics from a driver point of view
# 3 (Problem of delayed responses)
→ Users giving late responses, identify if a late response is genuine?

20. Connect with me on LinkedIn: https://www.linkedin.com/in/ankitchaudhary1/
Follow me on Twitter: @chaudharyankit1
Connect via email: ankitc.bits@gmail.com
Passionate about philosophy and data; also writing my first novel :)