Digital Advertising & Marketing 101: Take The Complete Guide
How do consumers see your brand relative to your competitors? …
What you'll learn
From one-off customer satisfaction surveys to brand tracking surveys that are administering on a continuous basis, they provide the information that marketers need to understand how their products, services and brands are seen by consumers.
In Analytic Methods for Survey Data, statistical learners will become familiar with established methods for converting survey responses to insights that can support marketing decisions.
Techniques discussed include factor analytics, cluster analysis, discriminant analysis and multi-dimensional scaling.
Cook Real Food: How to Make Simple Plant-Based Meals
If you’re struggling to lose weight or stick to a …
What you'll learn
Be able to use simple tricks and techniques to make self-control easier.
Actually apply these strategies and make a deliberate effort to understand their effects
Have a huge advantage when it comes to sticking to your diet
Meeting your fitness goals, and leading a healthier lifestyle.
Vegan Nutrition Health Coach Certification
Being healthy and living a happy and fulfilled life, respecting …
What you'll learn
Give you the tools to design a vegan custom health coaching package that is focused
Develop a thorough understanding of nutrition, nutrient density, macronutrients, micronutrients, and dieting
Learn health coaching skills and the key elements of behavioral change
Survey analysis to Gain Marketing Insights
How do consumers see your brand relative to your competitors? …
What you'll learn
From one-off customer satisfaction surveys to brand tracking surveys that are administering on a continuous basis, they provide the information that marketers need to understand how their products, services and brands are seen by consumers.
In Analytic Methods for Survey Data, statistical learners will become familiar with established methods for converting survey responses to insights that can support marketing decisions.
Techniques discussed include factor analytics, cluster analysis, discriminant analysis and multi-dimensional scaling.
