Study Blog

Student Name - Colin Almeida. Student Number - 10530977. Subject  - Data and Digital Marketing Analytics. Lecturer - Naomi Kendal.

Recently I started my Study Blog for an assignment and I have been writing blogs about big data and now I am going to write about the analytics report about the blogs here. We are going to see how people interacted with my blog. Audience Overview: As you can see above in our audience overview we have different metrics which we have mentioned below in details. Users: The total number of users that visited the blog is 54 and our new users are 54 as well because being a new blog. Sessions: The number of sessions the 54 users had on the blog were 250 and on the average per-user it was 4.63 sessions. Page Views: The number of page views by the users was 1,116 where the per page had on average 4.46 sessions. Bounce Rate: The average session on the page is 3:28 minutes where we got a bounce rate of 34.80%. User active time: The users have mostly been active between 12PM-2PM and between 6PM-10PM where we received most visitors on Tuesdays and Fridays. Users: The ...

Introduction. AI in marketing uses customer data, machine learning to predict the actions of a person to help marketers segment their customers to create a customized audience. Using AI, businesses can create a smart marketing campaign to target the right customers and show them the content they are interested in through the right channels. AI is having a huge impact on digital marketing currently has it allows marketers to analyze enormous data that they collect through social media, emails, websites in a shorter time which helps marketers to boost the performances of their ad campaigns to get maximum return. Parts of AI Marketing. Big Data:  Big data is a concept where marketers can understand and segment large sets of data in less time and using big data with AI, the message can be delivered to the faster and more effectively. Machine Learning:  Machine Learning can help to understand a large amount of data effectively by predicting insights, reaction...

Introduction Customer data in marketing is a form of direct marketing which involves the collection of different types of customer data such as name, address, mobile number, email, payment history, interaction and interest. when this data is analyzed it helps to create a personalized experience for different customers as per their interest and to attract new customers. Database marketing is on the rise again because marketers have access to a huge amount of customer data like never before. Customer data has it's own benefits and challenges which marketers have to consider as mentioned below. Benefits of using Customer Data. Customer Segmentation:  The goal of marketing is to give personalized and relevant content to different customers as per their interest and by segmenting them it gives the opportunity to reach the right customer. Customer Feedback: It is important for marketers to collect customer feedback to get insights about their company services. This he...

Introduction to Big Data in Marketing. Big data can be used to gather, analyze and use a huge amount of digital data in marketing to improve business growth and operations. Big data has been proven to be a major tool for marketers who are constantly trying to optimize performance, to build customer relationship, making precise decisions and improving engagement and loyalty of existing customers. Big data plays an important role in marketing as it leads to better insights about the potential target audience and helps to make better decisions. When marketing strategy and big data is combined businesses can have a major impact in the below-mentioned areas: Customer Engagement:  Big data helps marketers to understand who their customers are, where they are from, what they want and how to reach the customer so that Personalize Customer Experience can be delivered to them. Retention and Loyalty:  Big data can be used to understand the existing customer and t...

Introduction to the 3Vs in Big Data The properties of big data have been defined by the 3Vs which are volume, velocity, and variety. The 3Vs refer to the different data types such as, the volume is the amount of data, velocity is the speed at which the data is processed and variety is the different types of data. The 3Vs of Big Data Volume:  The volume in big data is the amount of data which is generated through different sources. For example, social media has a lot of text, images, videos and different multimedia shared through it where Facebook, YouTube, Twitter and Instagram have combined over 4 billion-plus accounts from which data is shared in huge volume. Velocity: The speed at which data gets generated to be processed using big data can be termed as Velocity. The amounts of data that is being uploaded on different social media platforms every day are in millions of photos, videos and tweets. This is like a sand storm and big data helps companies to stand th...

Introduction Big data is a huge amount of data which has complex data sets and new data sources which traditional data software cannot process. Big data can be used by business to tackle problems which they couldn't before with the massive amount of data. Big data can help business address multiple factors in their system such as product development, predictive maintenance, customer experience, fraud and compliance, operational efficiency and drive innovation.  Types of Big Data Big Data has three types of sets such as structured, unstructured and semistructured data which is collected by organizations by mining the information to use in their projects.  1. Structured Data -  The data that can be stored, accessed and process in a fixed format can be called as structured data.   2. Unstructured Data -  The data that does not have a format or a proper structure can be identified as unstructured data.  3. Semistructured Data...