This presentation is created during Data Analytics Internship under Prof. Sameer Mathur, IIM Lucknow.

1. Analysis of
Big Data
Hype and
Reality By
Gregory
Piatetsky-
Shapiro

2. INSIGHTS
AND
RELEVANCE
TO
MANAGERS

3. Decision-makers want to understand the patterns in
the past and the present in order to anticipate what is
most likely to happen in the future

4. As big data offers unprecedented awareness of
phenomena — particularly of consumers’ actions and
attitudes — will we see much improvement on the
predictions of previous-generation methods?

5. Let’s look at the
evidence so far,
in three areas
where better
prediction of
consumer
behavior would
clearly be
valuable

6. As a company that thrives when people consume more
content, Netflix routinely serves up personalized
recommendations to customers based on their
feedback on films they’ve already viewed
This is a prediction challenge; Netflix must venture an
informed guess that, if someone gave a certain rating
to movie a, they will rate movie b similarly
The company
launched a
competition to
improve on the
Cinematch
algorithm it had
developed over
many years
Film Ratings

7. The winning algorithm was a very complex ensemble of
many different approaches — so complex that it was
never implemented by Netflix
With three years of effort by some of the world’s best data
mining scientists, the average prediction of how a viewer
would rate a film improved by less than 0.1 star

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.

9. With the benefit of
big data, will
marketers get
much better
prediction
accuracy?
NO
There is always a
limiting factor to
prediction accuracy
for consumer
behavior such as
churn
What Managers need to realize?

10. The challenge of predicting the click-thru rate (CTR%) of
an online ad — clearly a valuable thing to get right, given
the sums changing hands in that business

11. The average CTR%:
Display ads :
As low as 0.1-0.2%
Behavioral and
targeted advertising :
1.4% - meaning that
today’s best targeted
advertising is ignored
98.6% of the time

12. Marginal gains can
perhaps be made
through big data, but
breakthroughs will be
elusive as long as
human behavior
remains inconsistent,
impulsive, dynamic,
and subtle
What
should
Managers
understand?
The randomness inherent
in human behavior is the
limiting factor to consumer
modeling success

13. Similarly, when an activity is driven by consumers’ whims,
no amount of ingenuity can produce the ability to know
what will happen
Predictive analytics can
figure out how to land
on Mars, but not who
will buy a Mars bar

14. Proven success of Big Data
Google can be considered
one of the first successes of
big data; the fact of its
growth suggests how much
value can be produced
While analytics may be a
small part of its overall code,
Google’s ability to target ads
based on queries is
responsible for over 95% of
its revenue

15. Proven success of Big Data
Social networks, too, will rely
on big data to grow and
prosper
The success of Facebook,
Twitter, LinkedIn and
YouTube also depends on
their scale, and big data tools
and analytics will be required
for them to keep growing

16. We can expect big data to have transformative effects in
other areas, too. Location analytics and location-based
services such as foursquare come to mind. So does
healthcare, where big data will drive progress in
personalized medicine.

17. Big data will see its biggest and most important
applications in the realm of Artificial Intelligence
IBM Watson
Apple Siri
Google Now
By 2020, all of these will be vastly more capable thanks to
the growing ability to make sense of big data and learn

18. Conclusion:
We should expect big data to have
big impact. And we can bet that it will
help machines interact more usefully
with our unstructured, changing, and
sometimes downright confused
human ways.
But if we’re counting on it to make
people much more predictable, we’re
expecting too much

19. By Dheepika C
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