What is Big Data?

1.Google Analytics Home In the last 28 Days, 105 Users have read this blog, creating 184 sessions with a bounce rate of 38.04% and session duration of 2m 17s. FIG.1 1.1. Active Users The below image gives an analysis of page views per minute. For instance, six active users are viewing four different blogs for the given minute. FIG.2 1.2.  How do you acquire users?     There are three different ways to acquire users, namely: 1.2.1. Traffic Channel The below histogram indicates maximum traffic is caused by direct and social channels. FIG.3 1.2.2. Source/Medium Views have been escalated through the use of Direct and Instagra m. FIG.4 1.2.3. Referral  FIG.5 1.3.  How are your active users trending over time? The line graph displays the number of active users over 90 days.  FIG.6 1.4.  How well do you retain users? The below statistic gives the percentage of returning users for 6 different w

Artificial Marketing Marketing is a strategy to leverage data and machine learning to deliver campaigns that help to more effectively achieve a brand's goals. Most marketers use AI in market research, data science, and real-time analysis of campaigns. (adverity.com, 2019) Advantages of Artificial Intelligence in Marketing  1. Faster data analysis The marketers can analyse complex data sets faster than a human with artificial intelligence. But this increased speed doesn't just mean more efficiency. Or the ability to rally and act more quickly on insights. It also suggests organisations could manually reduce the time associated with data processing. Because of Faster data analysis, they could launch more effective campaigns quicker and at a lower cost, deliver higher ROI.  (adverity.com, 2019) 2. More accurate insights Using AI, more detailed analyses of the data can be performed. Multiple data sets can be broken down with various machine learning alg

All personal, behavioural, and population data that the marketing companies and departments collect from their customised databases refer to customer data or consumer data. (Wikipedia Contributors, 2020) Types of Customer Data 1. Identity Data The first type of customer data analysis looks at the heart of database marketing, the most essential information to identify a person. It gathers the name, gender, age, telephone number, email address, occupation, social media handles, and account information of a customer. (Connext Digital, 2019) 2. Descriptive Data Your understanding is beyond the names, age, and email addresses of your customers. To get the right feeling of your customers, you must dig deeper. Here descriptive data comes into play. The goal is to collect quantifiable data on your customers so that their actions, seasonal increases, and buying practices can be accurately predicted. For maximum effect, your predictive analysis can be aligned with y

Big data gives us eyes and ears on our marketing activities. It captures insights into our prospects and customers at a level of detail that has never been possible before. At the moment, we can respond to audience actions in real-time and drive customer behaviour. Big data is changing marketing and sales in areas that only a few years ago seemed unachievable. Types of Big Data for Marketers 1. Customer Data Data from consumers allow advertisers to consider their target audience. This type of apparent data is facts such as names, email addresses, purchase history, and web searches. Just as important are indications of the attitudes of your audience, which can be gathered from social media activity, surveys, and online communities. (Pearlman, 2019) 2. Financial Data Financial information allows us to assess and improve performance. The numbers, expenditures, and earnings of your company on sales and marketing fall into this category. Pricing can