Crunch fundamentally changes the way you interact with your DP (data processing team).

You no longer need to go back and forth to ask for a stack of tables. Because Crunch enables you to quickly make a deck of tables yourself, it eliminates the need for you to give intricate and lengthy table specs.

Instead, you’ll be asking your DP for well-organized data. The data that comes into Crunch is called a dataset. It’s the dataset that you will be “crunching” yourself.

You’ll then be able to quickly build tables and graphs, create and apply filters and weights, and export your findings to Excel, PowerPoint, a shareable dashboard and more (such as Crunchbox, which we’ll explain later).

Crunch also gives you the ability to collaborate easily with other researchers (and your DP). Datasets can be shared amongst other researchers (and even your clients). But furthermore, you can do things in your dataset that others can see too (or not, if you choose to keep it private). We’ll talk about how to collaborate with Crunch later.

We’re going to give you an overview to build and filter some crosstabs, make some graphs, and then publish them.

On each topic, there is of course more detail, and we provide relevant links to our documentation (including short videos) if you want to dig a little deeper.

Before we get into the fun stuff (making tables and charts) there’s just a few key housekeeping issues to take care of. If you know these are taken care of, you can jump into making tables and charts.

• Getting a clean and tidy dataset
• Organizing your questions (and other variables)
• Checking and tidying your variables