Marketing Analytics versus Data Analytics – Know the Difference!

Marketing Analytics versus Data Analytics - Know the Difference!

Before we dive into Analytics, let us first get an estimate of data generated in every digital minute of 2020:

• Instagram users posted 347K stories

• Youtube users upload 500 hours of video

• Netflix users stream 404K hours of video

• Facebook users upload 147K photos

• WhatsApp users share 41.7M messages

• 1.4M individuals make video or voice calls

• LinkedIn users apply for 69K jobs

Surprising... Isn't it? If this is the information being generated in a matter of 60 seconds, can you imagine the vast amount of data that is created and stored daily in addition to these platforms?

Well, we are surely surrounded by a lot of data, be it generated from these social media channels or large scale enterprises. However, it is of no use unless interpreted. So how can one analyze data? This brings us to the topic of discussion - Analytics!

Analytics is the need of the hour. With the advent of easily accessible analytical tools, companies are investing more in the analytics segment to make sense of the available information and utilizing it for their benefit.

Analytics offers the following advantages that lead to the overall growth of an organisation:

• Increase in revenues

• Marketing campaign optimization

• Improved operational efficiency

• Streamlined customer service efforts

• Faster response to new market trends

• Staying ahead of the competition

Want to know more about Analytics and its types? Keep on reading to understand the key differences between Marketing Analytics and Data Analytics. This blog highlights their significance, commonly used tools and also the career aspect.

Marketing Analytics

What is Marketing Analytics?

Marketing Analytics is used to evaluate the performance of various marketing activities to maximize their effectiveness. It involves using specific analytical techniques to measure, manage and study metrics data to optimize the Return on Investment (ROI) of marketing efforts. This practice improves the efficiency of the marketing team by minimizing money wasted on unworthy campaigns.

Marketing Analytics also provides real market feedback to the sales, customer service and senior business management departments. This feedback helps them decide on where to invest and how to prioritize.

Marketing analytics serves as a holistic approach to measuring the efficiency of marketing strategies by connecting all areas of marketing with sales and lead generation results. This strategy helps determine the actual impact of a marketing campaign.

Why perform Marketing Analytics?

• Aids Campaign Designing - Marketing Analytics make it easy to understand customer trends and purchase behaviour. This data can be used to plan effective campaigns.

• Facilitates Campaign Analysis - Marketing Analytics performs a thorough analysis of the marketing campaign, determining if it is likely to work in terms of ROI.

• Predicts Future Results - Marketing Analytics can easily predict future results with the help of marketing trends.

• Helps Campaign Optimization - Marketing Analytics helps marketers understand what people want from a product through keyword research. According to this, they can select the right target keywords to optimize their marketing campaigns.

What are the tools used for Marketing Analytics?

There are different types of marketing analytics tools available in the market. These include event-based, testing, visual behaviour, digital marketing analytics and marketing dashboard tools. Some examples of such tools are:

• MixPanel

MixPanel is a type of event-based marketing analytical tool which provides an advanced mobile and website analytics platform to track different events. It helps businesses build better products and craft a delightful customer experience.

• Heap Analytics

Heap Analytics is a marketing analytics platform designed to track actions on websites and mobile apps. It helps create a digital experience that attracts, converts and retains users. The user can then review the analytics report to evaluate and optimize their campaigns accordingly.

• Oribi

Oribi is a marketing analytics tool that helps users use actionable insights to drive results. It has an easy interface which makes it stand out among its competitors. It automatically tracks website traffic and events that allows users to determine what is working and what is not.

• Optimizely

Optimizely is a testing marketing analytical tool used for testing multiple variants of any page and element related to the website. The analytics report generated helps a user determine the alternative providing the best result according to their marketing goals.

• Hotjar

Hotjar is a type of visual behaviour tool that has many marketing analytics features. Key features of this tool include feedback from polls, lead conversion funnel analysis, surveys and registration form analysis. It provides a data visualization platform used to track the visits and behaviour of a user on a particular website.

• SEMrush

SEMrush is a digital marketing analytics software that helps increase the online visibility of businesses. It allows online marketers to design, manage and measure the results of their online marketing campaigns.

• Google Analytics

Google Analytics is a free digital marketing analytics model that provides web analytics and tag management solutions. This toolkit is used widely by mid-tier marketers. It offers a suite of search, website and advertising campaign management tools.

• Cyfe

Cyfe is a marketing dashboard tool which is ideal for marketers who need to experiment with multiple data influences on a single dashboard. It can also track data from social media platforms effortlessly.

Career Opportunities in Marketing Analytics

Individuals can gain sufficient knowledge and skills in various Marketing Analytics tools to become Marketing Analysts. A Marketing Analyst is a professional involved in tasks including collecting, analyzing and presenting data on customers or competitors and understanding business objectives to design effective marketing strategies.

Data Analytics

What is Data Analytics?

Data Analytics is the practice of extracting raw data and analyzing it to gather relevant insights. It utilizes various analytical techniques to facilitate a company or organization to solve business problems or make better decisions. It is also used in the sciences to verify or disprove a hypothesis or theory.

Data Analytics entails the collection of information from various sources and the creation of reports stating the overall importance of the collected data.

Why perform Data Analytics?

• Provides Hidden Insights - Data Analytics produces hidden insights like behavioural patterns relevant to the business requirements by analyzing the extracted data.

• Facilitates Competitor Analysis - Market Analysis, a part of Data Analytics helps a business or company understand the strengths and weaknesses of their competitors.

• Promotes Business Growth - Data Analytics generates reports from the analyzed data. These reports guide the respective teams or individuals to take further actions to boost their business.

• Improves Customer Experience - Data Analytics helps understand customer requirements and enables improved Business to customer experience.

What are the tools used for Data Analytics?

Many Data Analytics tools are available in the market with various functionalities. The selection of a particular technique or tool depends on an individual's preferences. Following is a list of some of the best tools available in the data analytics market:

• R programming

R programming is widely used software for statistical computing and data modelling purposes. It renders for the automatic installation of all packages required by the user.

• Python

Python is the most preferred general-purpose, object-oriented coding language to streamline complex data sets. Being fast, easy to learn and simple to use, it goes well with data analysis. Also, it makes data more accessible by providing a range of graphical and visualization tools.

• Tableau

Tableau is a freely available, leading Business Intelligence tool. It uses an easy format for data analysis and visualization with real-time updates on the web.

• QlikView

QlikView offers a user-friendly self-service BI interface that facilitates data visualization and analytics. It provides features like Data Integration and Data Literacy which helps accelerate business value.

• Microsoft Excel

Microsoft Excel is one of the most simple yet effective tools for statistical data analysis. It offers clear data interpretation and visualization by utilizing charts and graphs. It is used mostly for storing clients' internal data.

• Apache Spark

Apache Spark is an open-source big data analytic tool utilized to handle huge datasets by many companies. It is easy to use and is used often for data pipelines and machine learning model development.

• Power BI

Power BI is a powerful tool utilized for business analytics. It furnishes interactive visualizations with self-service business intelligence capabilities, allowing a user to create live dashboards and reports. It also helps connect their data to other data sources and secure it across different Office platforms.

Career Opportunities in Data Analytics

After gaining considerable knowledge in this field, one can become a renowned Data Analyst. A Data Analyst is a professional responsible for data extraction and analysis by applying various data analytics tools and techniques and delivering meaningful insights that add value to a company. Their prime duties include collecting information about specific topics, interpreting it and presenting their findings through comprehensive reports.