Secondpoteaupavard

        As part of Module B9DM105 Data and Digital Marketing Analytics , we were tasked with creating and managing a blog. The latter has been linked of articles on Big data in order to generate traffic. In this article, we will look at the website statistics using Google analytics. It's quite hard to estimate the efficiency of this blog because of the lack of baseline data and the short term duration. Audience overview : The report above highlights the audience metrics for my blog, such as : How many users How many sessions How many views How many time is spent by session The bounce rate These metrics shows some interesting elements. First, the number of session is almost 3 time higher than the number of users, it means that a single user has come many times on my blog. Moreover, the average session duration is 07:39 min, so every user spend enough time to deeply read my articles on each session. Finally, the bounce rate is 38.60%, so 61.40% of...

               In a marketing context, artificial intelligence can be defined as entrusting a machine, software or set of algorithms, a task that cannot be handled by a human or that could only be performed by an individual under conditions of cost, quality or time that are less attractive than those provided by the artificial intelligence device. The boundary between a "simple basic algorithm" or the "simple automated use of a response library" and real artificial intelligence is tenuous and sometimes debatable, especially in a context where the term artificial intelligence is often used as a marketing argument or image factor by marketing solution providers. Other observers may have a higher requirement to qualify a technology as artificial intelligence, and some, often from the humanities, even go so far as to say that artificial intelligence does not yet exist. In the field of marketing and e-commerce, for example, artificial intelligenc...

          Today, the stakes of customer knowledge are particularly heavy for all customer relationship management professionals.   The customization of every aspect of the relationship, and an ever more fluid and efficient follow-up are part of the requirements of a new generation of customers appreciating efficiency and immediacy in all things. Customer data can be divided in 4 categories :  Descriptive data : This includes demographic data like gender, age, geography and income. It also includes self-described attitudes and preferences toward products categories and technology Behavioral data :  These are the general patterns customers exhibit when using your products and services. It includes making purchases, registering, browsing, and using difference devices. interactive data  This includes the clicks, navigation paths and browsing activities found on websites and software.  The classic usability test typically focus...

              Marketing data is changing.   It moves faster than most marketing professionals can even predict, so it is essential to understand that the processes around it are changing, too.   Data integration is the result of data generated by various platforms and sources, collected, cleaned, sorted and ultimately brought to companies in a form and shape that they can use directly to make decisions.Today, organizations are active on so many platforms – Facebook and Linkedin, Microsoft Advertising, Google Analytics and email marketing solutions like Mailchimp, that the amount of data they generate is simply overwhelming. Getting the right data         Companies can have a lot of data, but they are often disorganized, unstructured, and displaced.   Data brings information with them, and when integrated in the right way, it can bring a lot of benefits to the business. Then, i t must be treated in a manner...

.        Each company, large or small, manages a considerable amount of data generated by its various data points and business processes.   Sometimes companies can process this data using Excel sheets, databases or other similar tools.   However, when data cannot be integrated into such tools and human error cases exceed acceptable limits due to intensive manual processing, it is time to think about big data and analysis. In this article, we will be discussing how big data can be analysed using the famous 3Vs - Volume, Velocity and Variety. Volume : Considerable amount of data to process The amount of astronomical data generated by businesses and individuals is constantly increasing.   Only Big Data is capable of handling such a large amount of data and information.  Within the Social Media space for example, Volume refers to the amount of data generated through websites, portals and online applications. Velocity : Speed...

       Big Data has long been on everyone’s lips and is the subject of a lively debate. While its supporters point out the great usefulness of this big data that has emerged with digitisation, criticism is directed at the confidentiality of information. However, the concept is much more complex than it seems and that is why a definition of Big Data is necessary.        Big Data, or literally “big data”, is also called mega data or even massive data. This data is so complex that conventional software or hard drive is unable to process it. In addition, the notion of Big Data is vague since it can also refer to rather innocuous amounts of data from research. Given that the data collected relate to the consumption or communication behaviour of Internet users, the notion is poorly perceived. Critics view this data collection as an infringement of their private law.        The volume of digital data has increased signific...