advertising analytics and bjp 2014
TRANSCRIPT
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That historical 2014 Indian
Election BJP’s win..
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What was the real secret behind this
achievement?
BJP = 282/543
282
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What it just the effective
speeches that made BJP win?
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Or the rallies and “MODI LEHER”…..??
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It was a lot more….
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Effective target
Advertising played
a key role in this
win…
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But how did BJP targeted people so effectively in a country like India with huge diversity?
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How did they analysed how much resources
they need to allocate to different areas and
segments of advertising?
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The insight in HBR article
could provide the answers to our questions.. By Wes Nichols
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What is meant by
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It is the art of evaluating advertising effectiveness and performance.
ADVERTISING ANALYTICS
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It quantifies impressions, clicks, conversions and buying behaviour that different ads generate.
ADVERTISING ANALYTICS
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What are the of this article?
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OBJECTIVES
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What are the
of allocating resources in different areas of advertising ?
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Traditional ways
It helped marketers link scanner data
with advertising and decide how to allocate
marketing resources.
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Traditional ways
Marketers started tracking consumers most recent online action- say
a click on a banner ad and attributed a purchases
behaviour to it
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Traditional ways
Different teams and marketers measure the performance of each of
their marketing activities as if they work independently
of one another
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What are the
of using such traditional methods ?
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The traditional ad techniques ignores the assisted effects of marketing.
Disadvantages
The change in an advertisement viewing behaviour due to influence of another ad of the same company.
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Suppose, a user might see a T.V. ad & newspaper ad inspired and search Google , sees it banner later, click and make purchase.
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Disadvantages Here, T.V. , newspaper, google search all have assisted in buying behaviour which these traditional methods could ignore and measure their effects independently.
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Disadvantages
This could result in
over attribution or
under attribution of
advertising
revenues
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What is the other big problem marketers could
face?
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Virtually infinite record of data
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LACK OF CAPABILITY OF STORAGE
LACK OF CAPABILITY
OF ANALYSIS
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How should the company know that how ads assist
each other and which combination is the best?
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What should be the right amount to be invested at
right points in the customer-decision journey?
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The companies need to prepare segment of people by proper
analysis and then targeting them by al locating appropriate
resources.
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are involved
3. ALLOCATION
1. ATTRIBUTION 2. OPTIMISATION
Analytics 2.0
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It is the process of quantifying the
contribution of each element of advertising using analytics engine
storing huge data.
Analytics 2.0 - ATTRIBUTION
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market
conditions
consumer
response
competitive
activities, marketing
actions
business
outcomes.
Data is collected across categories.. Analytics 2.0 - ATTRIBUTION
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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.
Analytics 2.0 - ATTRIBUTION
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It runs various testing analytic tools to run scenarios for
business planning on a small scale.
Switching the shade of blue used on advertising links
in Gmail and Google search earned the company an
extra $200m a year in revenue.
Analytics 2.0 - OPTIMISATION
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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.
Analytics 2.0 - OPTIMISATION
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Uses such test to place its ads to see, which has the maximum response.
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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
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It redistributes the resources across
marketing activities according to
optimisation scenarios.
Analytics 2.0 – ALLOCATION
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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.
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are involved
3. ALLOCATION
1. ATTRIBUTION 2. OPTIMISATION
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One-of the world’s largest software gaming companies Successfully Attributed, Optimized, and Allocated to increase its selling and profit by increasing its revenue by 23% in a very popular game “BATTLE FIELD”
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Analytics 2.0 allowed Samsung Mobile to
cost-effectively determine which markets
would shift the overall brand preference
score in their favor and the right
advertising techniques to target people.
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What are the
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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.
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- Traditional methods of advertising - Disadvantages - Move to analytics 2.0 - Attribution, optimisation, allocation - Ways of implementation
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- 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.
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Coming back to the BJP case…
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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
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Many companies like SAP, Oracle, InMobi, Modak Analytics were tasked with analysing data for electoral
campaign and developing customised tools for the elections.
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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.
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The companies developed their own
customised digital tools based on
commisioned and open source data
including a 64 node Hadoop, PostgreSQL,
a d ser ers that process a aster 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.
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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.
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They even planted cookies in computers of people who visited their website to track their activities online and target them at the appropriate time.
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Such twitter analysis
were also made to see
what are people
response.
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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 did ’t spe d o ey i those areas ore here the people ere sure of not voting BJP for any reason.
The party effectively targeted people at various places of their interest
The party was able to interact with people ith ariety of its progra s like Chai pe Charcha .
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- HBR Article : Advertising Analytics 2.0
- http://dataconomy.com/narendra-modi-first-prime-minister-use-big-
data-analytics/
- http://articles.economictimes.indiatimes.com/2013-11-
26/news/44487290_1_data-analytics-bjp-and-congress-delhi-
bungalow
- http://www.cnbc.com/id/101571567
- http://www.firstpost.com/india/big-data-analysis-how-it-firms-like-
sap-oracle-helped-modi-win-1576355.html
- https://en.wikipedia.org/wiki/Big_data
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Created by-
Deepali jain
HBTI, KANPUR
during an internship by Prof.
Sameer Mathur, IIM
Lucknow www.iiminternship.com