- Analytics can be used to effectively target advertising campaigns through attribution, optimization and allocation of resources. - BJP's 2014 election win can be attributed to its use of advanced data analytics to segment voters based on demographics and interests. Custom tools analyzed terabytes of data to identify swing areas to focus resources. - Cookies and tracking online activities allowed highly targeted ads. Funds were spent contacting undecided voters through diverse programs. Advanced analytics allowed optimal resource allocation leading to BJP's victory.

2. That historical
2014 Indian
Election
BJP’s
win..

3. What was the
real secret
behind this
achievement?
BJP = 282/543
282

4. What it just the
effective
speeches that
made BJP win?

5. Or the “MODI LEHER”…..??

6. It was a lot more….

7. Effective target
Advertising played
a key role in this
win…

8. But how did BJP
targeted people so
effectively in a country
like India with huge
diversity?

9. How did they analysed
how much resources
they need to allocate to
different areas and
segments of advertising?

10. The insight in HBR article
could provide the answers to our questions..

11. What is meant by

12. It is the art of
evaluating advertising
effectiveness and
performance.
ADVERTISING ANALYTICS

13. It quantifies impressions,
clicks, conversions and
buying behaviour that
different ads generate.
ADVERTISING ANALYTICS

14. What are the of this
article?

15. OBJECTIVES

16. What are the
of allocating resources in
different areas of advertising ?

17. Traditional ways
It helped marketers
link scanner data
with advertising and
decide how to allocate
marketing resources.

18. Traditional ways
Marketers started
tracking consumers most
recent online action- say
a click on a banner ad
and attributed a
purchases behaviour to it

19. Traditional ways
Different teams and
marketers measure the
performance of each of
their marketing activities as
if they work independently
of one another

20. What are the
of using such traditional
methods ?

21. These techniques ignores the assisted effects of marketing.
Disadvantages

22. Suppose, a user might see a T.V.
ad & newspaper ad inspired and
search Google , sees it banner
later, click and make purchase.

23. Disadvantages
Here, T.V. , newspaper,
google search all have
assisted in buying behaviour
which these traditional
methods could ignore and
measure their effects
independently.

24. Disadvantages
This could result in
over attribution or
under attribution of
advertising
revenues

25. What is the other big
problem marketers could
face?

26. Virtually infinite record of data

27. LACK OF
CAPABILITY
OF STORAGE
LACK OF
CAPABILITY
OF ANALYSIS

28. How should the company
know that how ads assist
each other and which
combination is the best?

29. What should be the right
amount to be invested at
right points in the customer-
decision journey?

31. are involved
3. ALLOCATION
1. ATTRIBUTION 2. OPTIMISATION

32. It is the process of
quantifying the
contribution of each
element of advertising
using analytics engine
storing huge data.

33. market
conditions
consumer
response
competitive
activities, marketing
actions
business
outcomes.
Data is collected across categories..

34. The huge data is stored using
and
where, record of every
activities and their inter-related
effects could be analysed to
allocate the marketing resources.

35. It runs various
testing analytic tools
to run scenarios for
business planning on
a small scale.

36. In a war-gaming process , team
members define marketing
goals and software generates a
set market scenarios and
recommendation to achieve
them.
Elasticity points are given in respect that by how
much percentage sales in changes by changing
any factor.

37. Uses such test to place its ads to see,
which has the maximum response.

38. uses an A/B framework (used to test the success of web
marketing campaigns), allows multiple versions of the site to be
live simultaneously. This helps the company conduct live
experiments by siphoning off a small portion of traffic and
studying the results

39. It redistributes the
resources across
marketing activities
according to
optimisation scenarios.

40. The Obama team in 2008 U.S.
elections looked at 24 different
variations of the splash page using a
mix of images and CTA buttons to
determine which combination
produced the greatest results. Each
variation was seen by more than
13,000 people
The winning combination saw a
40% increase in sign-up rates and
an additional 2.8 million email
addresses which ultimately led to
$60 million in donations.

41. are involved
3. ALLOCATION
1. ATTRIBUTION 2. OPTIMISATION

43. What are the

44. 1.Embrace analytics as an organization
2. Appoint an analytical minded person to tasks.
3.Conduct an inventory of data through
organization
4.Build limited scope models that aim to achieve
early wins
5.Aggressive testing and feeding of results.

45. - Traditional methods of advertising
- Disadvantages
- Move to analytics 2.0
- Attribution, optimisation, allocation
- Ways of implementation

46. - Analytics can be used to find out the appropriate
resources needed to allocate.
- The revenue of the company could take a high growth by
applying analytics.
- Marketing is rapidly becoming a war of knowledge,
insight, and asymmetric advantage gained through
analytics 2.0 .
- Companies that don’t adopt next-generation analytics will
be overtaken by those that do.

47. Coming back to the
BJP case…

48. India consisted of :
-543 parliamentary and 4120 assembly
constitution
-930,000 polling booths
-Voter rolls in PDF’s in 12 languages
-900,000 PFD’s
- Diverse range of voter names and
information

49. Many companies like SAP, Oracle, InMobi, Modak
Analytics were tasked with analysing data for
electoral campaign and developing customised tools
for the elections.

50. A large professional data analytics team was
appointed to process and filter data from various
sources like debates on mygov.in, social network,
economic conditions of people etc.

51. The companies developed their own
customised digital tools based on
commisioned and open source data
including a 64 node Hadoop, PostgreSQL,
and “servers that process a master file
containing over 8 Terabytes of data.”
Machine learning algorithms were
also developed to help categorize
people based on name, geography,
religion, caste and ethnicity.

52. They analysed historic voter pattern and newly
available voter rolls to identify the pocket
boroughs of their party, the booths unlikely to
elect them and the ones that could go either way,
or the swing booths.
It helped them know were to
allocate resources and how
much.

53. They even planted cookies in computers
of people who visited their website to track
their activities online and target them at the
appropriate time.

54.  BJP was able to categorise people on the basis of gender, age, race, religion and
interests through the digital tools.
 Also, by proper analysis, the party segmented people on the basis of who are
likely to vote.
 The party spent money in those areas more where the people were still not sure
of the party they are going to vote for.
 The party effectively targeted people at various places of their interest
 The party was able to interact with people with variety of its programs like “Chai
pe Charcha”.