Learn about conjoint analysis.
- I love a good story about a startup company. When Airbnb started out, it was called AirBed and Breakfast, for example. You could rent an airbed on someone's floor and the owner of the home would provide breakfast in the morning. The idea didn't take off in its original incarnation and the founders had to actually sell breakfast cereal, of all things, to keep the company afloat. Today, obviously, they are a roaring success. The number one reason startups fail is due to lack of interest from the market. Remember that market may have intended to be, or could've accidentally become.
They create a product or provide a service that the world simply doesn't want. So, how do you know if a startup is creating a desired product? A great way to know is to ask the market itself, to conduct a survey, or to observe consumer behavior. In our example, let's assume we are working for a startup organization, one that is interested in becoming the leader in the next wave of social media applications. Their premise is simple. They know certain features are critical, but certain features have yet to be invented. Now, these new features will take the social media world by storm.
So, we have created a consumer survey. The survey categorizes the certain types of functionality into buckets like photos, user experience, and the ability to share content. We then identify the features that can comprise each category and have asked survey respondents to rank, or weight those features that they find most exciting, or most important to them. For example, in the user experience bucket, we wanted to assess the most important platform for the product's first release. So, we asked users to weight the importance of three different environments, mobile, desktop, or virtual reality, which could revolutionize social media.
Life is full of options. So are new ventures. Conjoint analysis, with the sort of data that our survey provides, can help us to know where to focus our resources to ensure traction. One category you'll see in the data is one called differentiation. Now, this is our client's social media special sauce, if you will. It's a bucket of innovative ideas that no other player on the social media space has brought to life yet. They could all be amazing, but unless the world is excited about it, it'll be a flop. So, what we'll see as a result, once our analysis is complete, are the functions this new social media platform should include to have the best chance at making it big.
In this course, discover how to gain valuable insights from large data sets using specific languages and tools. Follow Chris DallaVilla as he walks through how to use R, Python, and Tableau to perform data modeling and assess performance. As Chris dives into these concepts, he shares specific case studies that come directly from his own work with clients. Plus, he shares three essential—and practical—best practices for data-driven marketing that you can use to bolster your organization's marketing performance.
- Installing R, Python, and Tableau
- Navigating the UI for R, Python, and Tableau
- Using R, Python, and Tableau
- Exploratory analysis
- Performing regression analysis
- Performing a cluster analysis
- Performing a conjoint assessment
- Stakeholder alignment