Applied Marketing Analytics

Program Simulation Case Throughout this program, you will be applying advanced analytics techniques to solve marketing challenges using a real-world data set. The simulation is based on the scenario of a marketing team that is 10 months into the release of a new mobile game. Which users are most likely to convert? Which product feature is driving the most conversions? Did our promotion work? Each module introduces methods for deriving business value from the data repository, which is the linchpin for this experiential learning journey.  Module 1: Understanding Your Data and Basic Predictions To be an effective marketer today, you need to be able to extract value from the reams of data you have. Build an understanding of the types of data the simulation organization has collected and how it can use this data to increase paying customers. Learn about variations in data, correlations between features, and how to predict how many users will convert in a campaign by using historical data. Module 2: Predictive Models and Desired Outcomes Going beyond the historical data to grow your business, gain an introduction to how predictive models work. Learn different basic predictive models, when to use them, and how to interpret results. Experience the power of predictive models at finding customers who will buy. Module 3: Machine Learning Tools for Segmenting and Targeting Dive into more sophisticated models that will maximize the value of your data. Learn about several popular machine learning methods that are most relevant for marketing applications and how to assess which model is right for your business challenge. Module 4: Machine Learning Models To Sharpen Your Strategy Delve deeper into an advanced machine learning method: neural networks. Understanding multiple ways of predicting consumer outcomes will equip you to test models on your data and find the best fit for your business goals.  Module 5: Testing Models in the Real World: Link Analytics to Business Outcomes Activate an advertising pilot and use the data dashboard to compare the results of the ad campaign with predictions made in earlier modules. After discovering how well your models and predictions performed, you will aim to improve them further by retraining the model through the pilot. Module 6: Incrementality: Identify Your Highest-Value Customers By identifying your highest-value customers, you can optimize your ROI. Calculate both regular profits and incremental profits by employing two different (but equally cutting-edge) models: propensity modeling and uplift modeling. You will experience the final twist in the simulation: comparing the profitability derived from each model and exploring opportunities to improve marketing ROI.