This document discusses the importance and applications of data analytics in marketing. It explains that marketing covers all business activities from conception to sales. Data analytics provides valuable insights by turning vast amounts of customer data into meaningful information. This allows marketers to personalize their efforts, assess different marketing channels, conduct full funnel marketing, understand customers more comprehensively, and forecast customer behavior through predictive analysis. The key applications of data analytics highlighted are personalization, channel assessment, full funnel marketing, customer understanding, and forecasting.

1. Application of Analytics in
Marketing
Sohini Podder

2. Introduction
 Marketing is a domain where business analytics
finds great applicability.
 Marketing covers almost all leading business
activities. From conception to sales, everything
comes under the purview of marketing.
 Therefore, it can be said that data analytics is
indispensable to marketing.

3. Importance Of Data Analytics In
Marketing
 In this day and age, data is generated continually
in all aspects of our daily lives.
 Analytics turns such data into insights- creating
meaning out of disorganised, dispersed
information.
 These insights are invaluable to marketers, who
can apply the new knowledge gained from such
insights to serve their customers better and reap a
grater return on their investments.

4. Applications
 Personalization of marketing efforts
◦ Using customer information to tailor marketing methods for
the best fit.
 Assessment of channel functionality
◦ Data analytics make it easier to track marketing efforts from
initial interest to final purchase. With the help of cookies
and click-through-rate, marketers can prioritize channel
expenditure efficiently.

5. Applications
 Full funnel marketing
◦ With increasing customer awareness in the digital age,
marketers have a growing need to target prospective
consumers through multiple sources since there happens
to be a website for every unique need.
 Understanding customers
◦ To garner a comprehensive understanding of its customers
and their needs, marketers need to augment their first hand
data with data from reliable third party sources.

6. Applications
 Forecasting
◦ Using predictive analysis, marketers can effectively
forecast customer behaviour. This is made possible
through customer profiling. It can be used to develop finer
and better products which address customer needs while
tackling competition efficiently. Prediction will soon become
an indispensable part of marketing, the shift in the market
trends bearing evidence to this.

7. THANK YOU