Analyzing the Impact of Digital Analytics on Marketing Decisions

This essay provides a comprehensive overview of the role of digital analytics in business, focusing on its application in marketing and decision-making processes. It defines digital analytics and outlines its key steps, including data collection, scrutiny, and strategic decision-making. The essay discusses various tools used in digital analytics, such as measuring website effectiveness, content marketing impact, and predictive lead scoring. It highlights how digital analytics aids in identifying market risks, understanding customer demands, and improving business strategies. The author shares personal experiences of implementing data analysis in marketing roles, emphasizing its impact on sales and overall business growth. The conclusion underscores the importance of data integrity and careful implementation to leverage the full potential of digital analytics for sustained business success. Desklib offers a wealth of resources, including past papers and solved assignments, to further explore this topic.

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Author Note

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Introduction:
Definition-
The term data analysis means to inspect, process, scrutinize, and transform the valid
information regarding the business that helps the business to build a better scope in the
market. The data that is identifies are key sources to identify the drawback and strength of the
business. It have various approaches under variety of name(Agresti 2013). The steps involved
in data analysis are as follow:
1. Receiving the data from external sources
2. Scrutinizing the data with valid technology and sources
3. Identifying the factors that are revealed from the data
4. Separating them among asset and risk to the organization
5. Taking decision to maintain the asset
6. Taking necessary steps to reduce the risk
7. Reducing the scope for future risk
8. Protecting the company from any threats
A person who does the data analysis is termed as data analytics. The term digital analytics
means the analysis of qualitative and quantitative information from the organization and to
compete to drive a continuous improvement in the process that will attract the customers
towards the organization thus helping the business to meet its target or goal. The evolution of
cloud computing has enhanced the chances of the business to identify their risk in the market
and analyse the data in a judicious manner(Silverman, 2018). It includes the right processes
and skills to identify the risk and make necessary changes in the digital world to attract
consumers and improve the business condition. The study will discuss about the digital
analysis in the field of marketing in a company.

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How the data are applied in business for decision making:
There are various tools used in digital analytics such as:
 Measuring the effectiveness of the website- Marketing analysis begins with the
foundation of the business. A real marketing operation contains few key elements like
marketing automation software, CRM system, web presence tracking tools and a
marketing production space. It gives the company a well -defined look into the users
are doing, the time they are spending on that application and this information can be
implemented into the business for improving its condition for a better outcome. It
helps the organization to identify which area is getting the maximum push and which
area is remaining untouched by the consumers(Miles Huberman and Saldana 2013).
This gives an approximate idea to the company to meet the consumer need and make
better production.
 Measuring the impact of content marketing: the primary purpose of marketing is to
bring revenue. The business aims to fulfil their target with proper marketing skills and
strategies. Content scoring defines the effect of singular marketing deliverables to
revenue. It states the amount of revenue the digital marketing brings at each and every
step. It uses CRM to track the information about the customers.
 Marketing ROI planning: the marketing evolution helps to create the ROI plan. The
big data forms a smog of numbers that identifies the difference between the business
hike and failure. This includes three type of data real time data, big data, automation.
 Predictive lead scoring and conversion rates: this is the most powerful tool and takes
the conventional data stored by the marketers. This helps the analytics to understand
the business situation and the scope for business structure. This helps them to assess
and create the required message and content in order to optimize the financial
potential. This is a strong tool that determines many aspects in a faster way

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How it helps in decision making:
A business transformation is working out everywhere as the big data power and data
analytics are introducing themselves to the market and creating a better scope for the
business organization in the market. The data analytics are helping the organization to
identify their risk and threat in the market and take necessary steps for the
business(Nishisato 2014). The big data analysts can improve the decision making
condition by making the decision making process more responsive and agile to
understand the value of the information or data. The critical analysis helps to understand
the related risk and make necessary changes to the business. It views the business
problems and informs the business about the strategic decision referring them to rely on
objective data. The tools used are good data, valuable insights and sound analysis for
facing the risk and abolishing them from the business. Data analytics have become the
core centre of decision making for an organization. The business decisions are related to
them as they completes the analysis and gives critical review about the related risk and
strength of the business. They identify the emerging demands and establishing the
resources to perform the operations. The y provide real-time insight that has to be
operated immediately to get better outcome. It is said that the real time change is
transforming the decision of the organization. The business organizations that has smooth
decision making system are able to understand better the value of real-time data and build
a better competitive advantage. The companies that deal with data analytics should also
implement the data in their decision making process. The decisions will be dependent on
the information that will be harvested from the analysis and make required changes. The
companies have got a clear idea about the technological advantages used to analyse data
and make judicious us of the information that helps the business to extend further.

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Introduction of digital analysis:
The term digital analysis is used to define a set of technical activities that create,
collect, transform digital data into research analysis, recommendation, prediction and
automation. The data analysed is used in the organization to make required changes and
improve the condition of the entire organization. Digital analysis is required in every field
of industry and role in the industry(Wickham 2016). Mobile or web is used to analyse the
data and scrutinize the possible risk or issues that the company might have faced. The
information received from the analysis helps the business to understand the customer
demand in the market and makes them understand what the customer is demanding in the
market.
Establishment of the data in personal life:
Data analysis in marketing is a key factor. As it is known that data analysis helps to grow
and build a better platform for any business and sector. The marketing sector that has the
maximum usage of analysis is the marketing sector. In marketing the company must
know which section of customers are targeted by the company. The marketing sector
must have proper knowledge and does proper investigation about the threats related to the
business and its customers.
In work life:
In my experience of work life I have been benefitted by the data analysis in many
areas. The core marketing sector is highly dependent on the analysis of the market with
appropriate use of data analysis and testing. In my work life we have done a core testing
and analysis on data to identify the risks for the company and find the scopes that are
beneficial to reach the customers. The data analysis gives an extra hope to the company to
improve their skills and strategies to create a demand for the product of the company.
Being an assistance marketing manager I have felt the need for growing the sales and

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satisfying the consumers in the market. The introduction of internet has increased the
competition in the market(Aaker et al. 2013). The companies are using various new
strategies to improve their market condition and make a better place to succeed. The
global market has created a demand for proper analysis and competing strategies in the
market. Everyday new companies are rising with new strategies that is helping the
companies to reach a new height. The online marketing has once again helped to improve
the standard of the company and now customer from any end can reach the brand easily.
This was reducing the future scope of the company where I was working. My company
was relatively small if compared to the other brands present in the market. We decided to
create a better scope for the company by critical analysing the company and identifying
the areas that needs to be changed. This really worked out for the company. In a time gap
of 6 months the company saw a drastic change in the company sale and profit(McDaniel
and Gates 2013). The first few weeks were bleak and dull. It took two months to identify
the exact reason for the downfall of the company. Among these few were common and
were already predicted by us. The other factors like the comparison with other companies,
issues in personal development skills were unknown to us. We got a clear idea about the
drawback that were caused due to our careless analysis. The digital analytics performed
their task and started to recommend us measurable step to improve out work condition.
From the third month we started to improve our strategies and made necessary changes
that were required. The sixth month showed a drastic change in the sale and soon the
company was flourishing with its benchmark(Pradeep, Knight and Gurumoorthy, Nielsen
Co (US) LLC 2013).
I have been planning to change my job role from marketing to PR relation. This role too
has a huge influence by digital analysis. In PR relation the customers are the prior objects
to be focused on. The analysis of consumer type, their demand, likes, dislikes and

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affordability is very important. The business must be keep a note about the product type
the consumers are wanting and should use their strategies to get the best product for the
customers. The job role will require a lot of data analysis that will help to understand the
market scope, risk and strength related to the business(Neuendorf 2016). The business
will also get benefitted from such information’s that is helping it to expand and explore to
a wider world.
Conclusion:
However, few things should be considered that the business should not be too much
dependent on such sources and should analyse itself at least for once. The business should
hire proper and trust worthy employees who will not misuse the data. The business make
sure that they are using the right source and not fake sources. Thus, if the business is
using such preventive measures to protect itself from false situation and threats then there
are hi chances that the business will face success and will have high scope to expand in
future.

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References:
Aaker, D.A., Kumar, V., Leone, R.P. and Day, G.S., 2013. Marketing research:
International student version. John Wiley & Sons.
Agresti, A., 2013. Categorical data analysis. John Wiley & Sons.
Chambers, J.M., 2017. Graphical Methods for Data Analysis: 0. Chapman and Hall/CRC.
McDaniel, C. and Gates, R., 2013. Marketing research. Singapore.
Miles, M.B., Huberman, A.M. and Saldana, J., 2013. Qualitative data analysis. Sage.
Neuendorf, K.A., 2016. The content analysis guidebook. Sage.
Nishisato, S., 2014. Elements of dual scaling: An introduction to practical data analysis.
Psychology Press.
Pradeep, A., Knight, R.T. and Gurumoorthy, R., Nielsen Co (US) LLC, 2013. Analysis of
marketing and entertainment effectiveness using central nervous system, autonomic nervous
system, and effector data. U.S. Patent 8,484,081.
Silverman, B.W., 2018. Density estimation for statistics and data analysis. Routledge.
Wickham, H., 2016. ggplot2: elegant graphics for data analysis. Springer.