Big Data Blog

Analysis of Blog posts traffic using GA. Audience Analysis Overview :  The above analysis is based on a course of 6 weeks blog post traffic showing the number of new users, the number of times a user visited the page, the total number of page views by users, how many times the user exited the site as soon as they came on the website i.e Bounce Rate. Acquisition Analysis Overview :  The above analysis is based on how the users came to the website. In the course of six weeks, 40 Users came directly to the website through the shared link, 25 came through social media platforms like Instagram, Facebook, LinkedIn etc, 14 of them came through referral links. Also as there was no On-page Optimization so the organic search is almost negligible. Behaviour   Analysis Overview :  The following behaviour analysis shows the following:  Total Pageviews Unique Pageviews Avg Time on Page Bounce Rate Exit Percentage Most visi...

Subject Name: Data and Digital Marketing Analytics Subject Code: B9DM105 Lecturer Name: Naomi Kendal Student Name: Tarun Gahlot Student Number: 10521043 Assignment Title: Publishing 6 Blog Posts and analyzing it using Google Analytics Blog URL:  https://dbsserialblogger.blogspot.com/

According to, Alan Mathison Turing " If a machine can think, it might think more intelligently than we do, and then where should we be? Even if we could keep the machines in a subservient position, for instance by turning off the power at strategic moments, we should, as a species, feel greatly humbled". (September 2004)  With the use of AI in Marketing like chatbots, Voice-based searches etc has made lives easy for many organisations. To understand better the trends of Artificial Intelligence in Marketing which is likely to explode by the end of 2020.  Customer Segmentation:  With the help of AI in marketing organisations can now profile customer based on their browsing behaviour, content creation is made easy with AI, Re-targeting, click-tracking, tracking the digital prints. Also, various products are suggested to customers by companies based on their purchase history using AI. Hence, improving customer service and providing better service. Using Artificial Int...

Using customer data is no new thing. Database Marketing is being used for several decades. Nowadays, marketers are more involved with data as the customer data is growing at an enormous amount and using data analytics, the insights extracted from the collected data is also growing exponentially. Using Database Marketing organisations can benefit in several ways :  A couple of decades ago, marketers used mass media marketing strategies (like TV's, Radio, etc) to create any sort of brand or product awareness. But now with the proper Customer Data Platform and analyzing the data efficiently marketers can maintain a clean and centralized record of the collected data also known as  Single Customer View  Marketing Database. Single Customer View refers to the process of collecting data from both online and offline sources and merging it to form a single customer profile. This Single Customer View profiling can be done based on website visit, purchase history, demographics a...

The term Value in Big data refers to the worth of data being collected or the process by which collected data can be turned into something valuable. If the data being collected can't be turned into value then it is useless for any organisation, although the potential value of big data is quite high. Storing terabytes of data is of no use unless it can be evaluated, rather extracting value from the bulk of data and using it for the improvement of a business. Big data can be used to deliver value in almost every aspect of a business. Big Data helps companies to understand their customers and serve them better. Big Data is used by many Government and Law agencies to fight terrorism and stop any cybercrime, thus improving security. Big giants like Amazon and NetFlix also use Big Data by extracting value from it and recommending customers things tailored to their interests using Predictive Analytics. Value in big data allows companies to optimize their processes just like uber can...

With the huge amount and variety of data available, understanding big data analytics can be difficult. To understand better it is categorized into three segments commonly known as 3 Vs of Big Data. Volume, Velocity and Variety (  as discussed in the previous blog  ). Volume  Data is being generated continuously from phones, cars, sensors, IoT Devices, healthcare equipment, videos, etc. Moreover, data is also being collected the way human behave, act and engage by the means of machine learning. Having more data means getting a better approach over competitors.  This high volume of data requires equivalent storage and distributed approach to be accessible whenever required. However, many organisations fail to manage and decipher the collected data efficiently. As the volume of data has increased, so have the options for storing data. Data lakes , a central repository for all the data and analytics that allows organisations to store structured, unst...