Big data provides an unprecedented opportunity to predict consumer behavior through the longitudinal and cross-sectional analysis of vast time series data. However, the inherent randomness of human behavior poses a limiting factor, and while marginal gains can be made through big data, breakthroughs may remain elusive as long as human behavior stays inconsistent, impulsive, and dynamic. The biggest impact of big data will be creating new areas like personalized medicine, improved customer service, and powering artificial intelligence through vast data analysis to understand and anticipate human behavior.

1. Big Data Hype (and Reality)
by Gregory Piatetsky-Shapiro
Insights from HBR article

2. Let’s talk..
Most applications of data mining
and analysis have been, at their
hearts, attempts to get better at
prediction.

3. Big data is fastest growing job trend
Is it a bubble?

5. When Netflix relied on data.
Cinematch algorithm:
To analyse if someone
gave a certain rating
to movie a, they will
rate movie b similarly.
When Netflix started
this competition, their
RMSE was 0.95, and
challenge was to reduce
it by 10%.

6. They achieved target after 3 years!

7. Click-through rate
Click-thru rate (CTR%) of an online ad — clearly a valuable thing to get right,
given the sums changing hands in that business.
The average CTR% for display ads has been reported as low as 0.1-0.2%.
Behavioural and targeted advertising have been able to improve on that
significantly, with researchers reporting up to seven-fold improvements.
But note that a seven-fold improvement from 0.2% amounts to 1.4% — meaning
that today’s best targeted advertising is ignored 98.6% of the time.

8. Customer attrition
If predictive analytics drawing on big data could accurately point to who in particular was
about to jump ship, direct marketing dollars could be efficiently deployed to intervene,
perhaps by offering those wavering customers new benefits or discounts.
Analysts measure how accurate the list of potential churners is by using a measure called
“lift.”
A wireless provider has a churn rate of 2% per month. If an algorithm can learn indicators of
customer defection, and generate a list of the subscribers most likely to leave, and 8% of
those subsequently do leave, then this list has a lift of 4.

9. Story so far..
Predictive analytics where decision maker wants to
understand the relationship between time series
data and predict what will happen in future.
BIG data is an abandoned source of time series data
collected longitudinally and cross sectional to offer
unparalleled advantage for predicting consumer
behaviour.

10. What are we to conclude from this?
The randomness inherent in human behaviour is the
limiting factor to consumer modelling success.
Marginal gains can perhaps be made thanks to big data,
but breakthroughs will be elusive as long as human
behaviour remains inconsistent, impulsive, dynamic, and
subtle.

11. Big data intelligence #1
Big data analytics can
improve predictions but
the biggest effect of big
data will be in creating
wholly new areas.
For e.g. Google, Facebook
all explored the dynamics
of data analytics and now
the major revenue is
coming from that tools.

12. Big data intelligence #2
In healthcare, big data will drive progress in
personalised medicines and improved service
satisfaction among patients.

13. Big data intelligence #3
Big data will be biggest and the most important
application in the realm of the AI.
AI uses large data in order to understand and
predict behaviour of human beings.
Apple, Google using Siri and Google Now to
demonstrate the future

14. Big data intelligence #4
Bigdata can have transformative effects in
other areas too, like location based services
such as foursquare

15. Thank you!
Prepared by: Abhishek Rana