STUDENT DETAILS

Subject Name: Data and Digital Marketing Analytics 

Subject Code: B9DM105 

Lecturer Name: Naomi Kendal 

Student Name: Amrit Raj Pawar 

Student Number: 10539085 

Assignment Title: Analysis of Blog Posts on Data Analytics using GA. 

Blog URL: https://bigdatasizematters.blogspot.com/  

Google Analytics Analysis for Big Data, Size Matters Blog

This is the analysis of data generated in the last 6 weeks on my Blog page Big Data, Size Matters using Google Analytics. 


Audience Overview

The above report gives us information on the audience, like:

• Users: The number of users that visited the site in 6 weeks.
• Sessions: The number of times they visited the site.
• Pageviews: Number of time pages are viewed.
• Average Session Duration: The average length of a session per user.
• Bounce Rate: Percentage where there was no interaction with the page.

Audience Location & Hardware

The charts below show the countries in which our audience that visited the blog page resides and also the medium used by them to get on to our site.

Acquisition Overview

The report above shows the channels via which the users got on to our website. The post links were shared on personal social media platforms like Facebook and also on direct links that were shared on WhatsApp groups with friends and family. 

Behavior Overview

This part of the report focuses on particular pages and the insights related to these pages like how the content is, how much time was spent on a page by the user and such.

Google Analytics provides a lot of useful insights and helps keep track of the activities by us and our users on the site. With the help of these reports generated by Google Analytics, we can make changes and use them to our own benefits.

With this, we end our 6 Blogs of this module and probably soon again start with a new journey of blogs with different topics. A big thank you to all who helped in generating this data.

Artificial Intelligence in Marketing

Hearing AI takes us to a world of imagination with driverless cars and robots taking over the world and stealing all possible human jobs. Our perception and imagination of AI are very different from what it is used for in marketing. 


What is AI?

As defined by the English Oxford Dictionary Artificial Intelligence stands for "The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision making, and translation between languages." AI uses computers to complete tasks that otherwise humans would have to do thus saving time and effort.



AI in Marketing

When it comes to marketing, any kind of data collected can be easily analyzed with the help of AI. You can also achieve deeper insights related to patterns observed and digital footprints left by a consumer on one's website by generating a report. You can choose from either purchasing an AI-inbuilt software or program your computer to implement the algorithms and techniques of artificial intelligence.  Some of the examples of its use are:

• Setting up ad campaigns
• Alexa and Siri, voice recognition
• A personalized experience, better customer service
• Amazon uses Machine learning for recommending products, or the explore feed on Instagram
• Segmentation of the target market
• Content generation

With the ever-changing industry and technological intervention, we can't deny that AI is useful for not just marketers but consumers as well. 

Share your views, suggestions, and questions in the comment box below and tell us what you imagine when you hear Artificial Intelligence!

Sources

'AI Marketing: What, Why and How to use Artificial Intelligence Marketing' (2019). available at: https://www.mageplaza.com/blog/ai-marketing-what-why-how.html (accessed: 20/02/2020)Mullan, E. (2019) 'The uses of Artificial Intelligence to Marketers' available at: https://blog.hurree.co/blog/what-is-artificial-intelligence-marketing (accessed: 22/02/2020)
Rouse, M. (2019) 'artificial intelligence in marketing' available at: https://searchcustomerexperience.techtarget.com/definition/artificial-intelligence-in-marketing (accessed: 21/02/2020)

Benefits and challenges of using customer data for marketing

In the previous blog, we discussed the value of Big data in marketing. Today's topic of discussion is the benefits and challenges of using customer data for marketing.

We have discussed the importance, the various types of Data and what makes up the Big data and today we will discuss the benefits that an organization reaps from Big data and the challenges that it usually faces in order to gather or use this data.

Benefits

Gathering this data gives helpful insights relating to customer preferences, customer buying behavior, and patterns. This helps the business and companies to align themselves with their target audience and provide them with a better user experience. 

A more personalized experience is put forward to the individuals initiating customer engagement and improving customer relationships resulting in higher sales and satisfied customers. 

Challenges

Cost is a major challenge for enterprises. The collection, storage, and analysis of this data require tools and infrastructure to be built. Some companies keep these on site while some outsource it. It requires buying hardware, software, and licenses.

Another major challenge is the security aspect of this data that is collected. Realizing that data is of the utmost importance in today's era to the businesses, data leaks and misuse of the data can be a big turn off to the customers and keep them at bay from your company. Complying with the data collection laws and keeping them safe from hackers is a challenge that a lot of corporations face and fear.

Last year we saw data breach in many giant corporations like Facebook, Quora, Underarmour. A data breach on Facebook resulted in a loss of $13 billion market cap in just one day.

Such breaches in big corps suggest how big of a challenge Data security is.

We will meet again next week with a new topic till then keep sharing your views, suggestions, and questions in the comment box below. 


References:
Kokemuller, N. (2019) 'The Advantages & Disadvantages of Database Marketing'. Available at: https://smallbusiness.chron.com/advantages-disadvantages-database-marketing-22810.html (Accessed: 04 February 2020).
Minkara, O. (2014) 'The Good, the Bad, and the Ugly in Using Customer Data for Marketing'. Available at: https://www.aberdeen.com/cmo-essentials/good-bad-ugly-using-customer-data-for-marketing/ (Accessed@ 04 February 2020).
Rongala, A. (2016) 'The 5 Challenges in Customer Database Management'. Available at: http://customerthink.com/top-5-challenges-in-customer-data-management/ (Accessed: 05 February 2020).

Value in Big Data for Marketing

Welcome to our third blog in the third week of our college semester, the topic of discussion today is the value a business can derive from Big Data in marketing. In the previous 2 blogs, we discussed:

•  What is Big Data
• 3 V's of Big Data

The collection and storage of customer information by businesses have existed ever since the inception of the internet. Companies have collected and stored huge amounts of data in hopes that they might require it sometime in the future. Earlier the data collected was random and had not much specific value to it whereas, now the data collected has some kind of specificities attached to it and has specific values to be derived out and used to perform a specific purpose or task.

In this technologically advanced and Big Data era the data collected can be analyzed and put to use to make better and more profitable decisions for the business. It also helps in various other benefits which are mentioned below:

1. Better customer insights
   Analysis of the big data can tell you a lot about the current needs of your customers. If a lot of people are talking about a certain product over the internet or a social media platform you can make use of it and pop up your ad for better target marketing.
2. Personalization
   You can analyze the purchase behavior of your customers and suggest to them the products they would like to buy. This builds one to one rapport with the customer and increases the chances of making a sale.
3. Understanding market trends
   The past, present and future market trends can be analyzed and strategies can be developed on their basis.
4. Minimizing risk
   With a large amount of Big Data a full in-depth study of your competitor and the customers can be done which further can tell you about the risks associated with your business and product. This risk identification can help you make changes and avoid any or minimize the losses.

It is not just the collection of immense data but the collection of valuable and high-quality data that matters and is of use to the companies. This data is further analyzed and value is derived using various tools and methodologies depending upon the requirement of the business.

We will meet again next week with a new topic till then keep sharing your views, suggestions, and questions in the comment box below. 


References:
Bhattacharjee, S. (2017) 'Big Data, Data Mining, and Machine learning: Deriving Value for Business'. Available at: https://www.smartdatacollective.com/big-data-data-mining-machine-learning-deriving-value-business/ (Accessed : 25 January 2020).

Volume Velocity & Variety of Big Data| 3 V's of Big Data|

In the last blog, we learned about what Big data is and now we have laid down the 3 V's that form this Big data.

• Volume: Data collected is immense and gathered through various platforms like IoT devices, social media platforms, surveys, etc. The data collected is both structured & unstructured and is of different value in different areas of business and cross terabytes or even petabytes of space for some organizations.

• Velocity: It is the speed at which data is collected and processed, with growth in technologies and data collection instruments like IoT devices & RFID, information is gathered in real-time & requires to be dealt with in real-time speed as well.

• Variety: Data is available in a lot of variety. Along with structured data, the new data is unstructured or semi-structured and in different forms like mails, reactions, numerical, texts, audio, video, images, etc.

Keep sharing your views, suggestions, and questions in the comment box below.

References:
'Big Data: The 3V's explained' (no date). available at: https://bigdataldn.com/intelligence/big-data-the-3-vs-explained/
Dave, P. 'Big Data: What is Big Data - 3V's of Big Data'. available at: https://blog.sqlauthority.com/2013/10/02/big-data-what-is-big-data-3-vs-of-big-data-volume-velocity-and-variety-day-2-of-21/

What is Big Data ?

Big Data is to industries what oxygen is to humans. In simple words, it is the large and complex set of data gathered by business entities using new mediums of data collection. Collection of data and using it has existed for a long time but this new data known as Big Data is so huge, fast & complex that it is not easy to access, store and process this data via traditional methods, platforms like Hadoop & Data lakes have made it easier to carry out these activities. Big Data also helps industries identify the hidden patterns and thus enhance their operations by making more informed and smart decisions.

In 2001 Gartner stated: Big data is a variety of data that comes in at an ever-increasing rate and the volume of which is constantly growing (Gartner, 2001) 

Types of Big Data:

• Structured Data: Over the years computer technology has developed to store access and process some data in a particular format and also derive value out of it, this is referred to as Structured Data.
  For eg.: A Student table in college Database with information consisting of ID, Name, Subjects, D.O.B, and marks.

• Unstructured Data: Any data without a form or structure and from which deriving value is a challenging process is called Unstructured data. This is completely raw data and the perfect example of it is texts, videos, images on social media sites.

• Semi-structured Data: This consists of both types, structured and unstructured data, it can be structured but without a form.
  For eg.: An XML file. 

Whereas, now the availability of data is in abundance but the optimum & efficient use of that data still poses as a challenge to many organizations.

In the next blog, we'll talk about the 3 V's of Big Data and some organizations that use Big Data.

You can share your views, suggestions, and questions in the comment box below.

References:
'What is Big Data'(no date). Available at: https://www.oracle.com/ie/big-data/guide/what-is-big-data.html (Accessed: 20 January 2020).
'Big Data What it is and why it matters' (no date). Available at: https://www.sas.com/en_ie/insights/big-data/what-is-big-data.html (Accessed: 21 January 2020).