Marketing Analytics with R

Text is a valuable data type in various applications, including marketing analytics. It is often used for product reviews and social media analysis. Due to its affordability and simplicity, text is frequently used as a replacement for unstructured data. To fully leverage the potential of text, it is crucial to organize, clean, summarize, and model it effectively. This course aims to teach individuals how to utilize the latest tidy tools to start working with text efficiently. Participants will learn how to organize and visualize text, conduct sentiment analysis, and create and interpret topic maps. The course covers various aspects of data analysis using R, including text mining, textual analytics, and sentiment analysis using R. By the end of the course, participants will have gained the necessary skills to perform comprehensive text analysis and sentiment analysis in R. This course is ideal for individuals looking to enhance their understanding of text analysis and sentiment analysis and those interested in utilizing these techniques for marketing analytics purposes.

Analyzing data from social media can provide valuable insights. This can be used to plan campaigns, increase sales and marketing, analyze competitor data and discover untapped networks. This course will show you how to use R in order to extract and visualize Twitter data, perform network analysis, and view tweet geolocations. You will be able use various datasets to put your knowledge into practice, including tweets about celebrities, technology companies, trends and sports.

How did you go grocery shopping last time? Do you see any connection between the products you purchased, such as tomatoes and spaghetti or ham and pineapple? Online and offline retailers can access millions of customer baskets information to determine associations between products and extract insight through association rules.

Market basket analysis can be used to determine the degree of relation between items. You can also use it to visualise relevant rules and discover connections. You will then be able put into practice all the knowledge that you have gained from analysing a movie library. It is possible to predict the most popular movies together and make personalized recommendations for your users.

This is your chance to dive into the world of marketing and business analytics with R. Everyday companies face many decisions. With statistical models, you can help businesses make better business decisions based on data. We'll show you how statistical modeling can help improve the performance of your business. We will show you how communication can make a difference and what to do with your results.

People make choices every day. Every day, people make choices. People make choices every day about what products they want (such as orange juice and cars), who they vote for, how they get there. This information is crucial for retailers, product designers, and other professionals. Choice models are used to predict what options people will choose, and can be used to aid in product design decisions. This course will teach you how to organize and estimate choice models in R. It includes both real-world and survey-based choice analysis.

This course on data modeling in marketing will teach you how to analyze and utilize digital data to improve marketing strategies effectively. By creating simple models, you will be able to identify patterns in customer reactions and market actions. These models will allow you to quantify marketing variables such as price, promotion tactics, and other factors by utilizing aggregate sales and individual-level data. With the help of data scientists, you will gain the skills to build statistical models that show the impact of your marketing efforts. This course is essential for marketing professionals who want to measure the success of their campaigns and make data-driven decisions.