Getting Started with Q Part 1: Understand the Q Workflow
Q makes it easy for market researchers to discover the stories in their data. At Q, we understand market research and the structure of survey data, so Q makes it quick and easy to generate tables, crosstabs, and other analyses without syntax writing, and allows you to export your results directly in Microsoft PowerPoint, Excel, Word or PDF. In this post, I take you through a simple workflow in Q, from importing a data file to exporting the final report to Microsoft PowerPoint.
The basic Q workflow
Q helps you turn survey data into tables with the desired statistics (e.g. count, %, average, etc.), find the story quickly, and publish your results effortlessly. The basic components of the Q workflow are as simple as 1, 2, 3:
- Import your data.
- Build your report: create your tables, crosstabs, visualizations, and more advanced analyses.
- Publish your results to Microsoft PowerPoint or Excel as tables and charts.
In this post, I’ll tell you how to do these things in Q.
When you import your data set, Q does a lot of the decision making about the structure of your data and how it should be presented and analyzed. This is all done on top of your data file, which means you can make changes to it at any point in time and your data file stays intact. This is great from a risk management point of view.
Most people get survey data in the SPSS (.sav) format, but you can also use Dimensions (.mdd), Excel-style files (.xlsx or .csv), and more. For tips on getting a good .sav data file for Q, see our recommended specs.
You don’t need to have a data file to follow the steps in this post. Q comes with some handy example data files for you to play around with. I’ll use one of Q’s example files in this tutorial and explain where to find them.
Build your report
Tables are the workhorse of most reports in Q. There are advanced analyses and visualizations too, which will be covered in separate articles.
Q’s tables are dynamic, interactive objects that live in your project in the Outputs tab. At any time, you can change the contents of a table or take a copy and start making a new table. Data selection is done in the blue and brown dropdown menus, whereas filters and weights are applied at the bottom of the screen as per the screenshot below.
Your tables are organized as a report on the left side of the screen. The tables live here and are remembered for later, so you can come back and modify them as needed.
Q’s tables are interactive. You can do things like merging by dragging and dropping rows or column headers, or you can do tasks like renaming, and hiding rows and columns by right-clicking. No syntax writing is required to do these things. Changes you make on the table will be remembered, so you can get your outputs looking the way you need once and then reuse them for the remainder of your work.
Publish your results
Once you have found the story in the data and built a report around it, you can share it by exporting results directly to Microsoft Excel, PowerPoint, Word or PDF as both tables and charts.
For Microsoft PowerPoint publishing, you can create tables and charts following your company’s template, save it and tell Q to use that template in future exports, saving you a lot of time doing formatting.
If you need to generate tabular reports, Q’s automated table creation and Microsoft Excel exports make it a breeze. I go into more detail on generating tabular reports in this post.
Updating reports when new data comes in is easy! Once the data set is uploaded into Q, all tables are automatically updated and all you need to do is to click a couple of buttons to update your exports in Microsoft PowerPoint, Excel, Word or PDF. Say goodbye to producing individual charts manually, formatting and resizing. Q does the heavy lifting for you.
Try it yourself
I’m a great believer that the best way to learn is by doing it, so I’ve outlined the steps below for you to follow using one of our example projects that come with Q: the Cola study.
Step 1: Open Q.
You start with a blank workspace called a Q Project. This will store your data and all your analyses.
Step 2: Select File > Data Sets > Add to Project > From File...
There are many sources you can use, but most people would have the data file on their computer or network drive.
Step 3: Find C:\Program Files\Q\Examples on your computer, select Colas.sav, and click Open.
The examples folder contains a variety of different example data files for you to explore, as well as premade projects. These are used in the interactive tutorials in Help > Online Training. I highly suggest you taking some lessons from this source if you are a visual person and learn best by seeing how it is done, then doing it yourself.
Step 4: Choose how the data should be imported by selecting the automatic detection and click OK.
This option scans your data file and groups together all the variables of multiple response and grid questions so that it matches your survey structure as closely as it can.
Step 5: Click into the Blue drop-down menu in the Outputs tab and select the Preferred cola question.
The blue menu allows you to select the questions to show in the rows of the table. You can click and choose from the list of questions in your project, or you can click and type the question label into that menu to quick-search.
Step 6: Click on the Coca-Cola row label, hold SHIFT, and click on the Coke Zero row label.
Like many things in Q, holding CTRL or SHIFT on your keyboard allows you to multi-select.
Step 7: Right-click and select Create NET. Type in “NET Coke”, and click OK.
This context menu also includes options for renaming and removing rows, changing table statistics, and other data manipulations.
Step 8: Click the + Duplicate button.
When you are exploring your data, duplicating tables basically saves your table in the report tree for later use. There are automated options for churning lots of tables at once, and I cover this in this post.
Step 9: Click into the Brown drop-down menu in the Outputs tab and select the Gender question.
Crosstabs are formed by selecting a question in the Blue drop-down menu to show as rows and a question in the Brown drop-down menu to show as columns.
Step 10: Hold CTRL and select both tables listed under Report.
Multi-selecting is your friend for saving time on repetitive tasks.
Step 11: Click the PowerPoint Icon in the top toolbar, and click OK.
On this screen you get to choose the formatting and chart type from Microsoft in the Exporting tab. Select To PowerPoint as Excel Chart in the Format drop-down menu, Column Clustered in the Chart drop-down menu and click OK. If you have a Microsoft PowerPoint document open, Q will ask you if the export should be done in the open document or a new one. Direct it according to your needs.
Q will open Microsoft PowerPoint, send the data from the tables you produced and highlighted for exporting, and generate the corresponding charts. Note that these charts are fully editable. You can change the formatting as you please and create a template that should be used for future exports. To do that right-click the formatted chart in Microsoft PowerPoint and select Save as Template…. Make sure you save it in the exact Microsoft folder it is automatically pointed to. This is because Q will show the templates in Q that are in that folder.
Next time you export to Microsoft PowerPoint from Q, select the desired table(s) in the report tree, click on the Microsoft PowerPoint icon, select the same format as before and in the Chart drop-down menu select the template you created.
So, there you have it – getting started with Q is super easy! This is the first in a series of introductory blog posts on the basics of Q. In my next post I teach about Q’s heartbeat and the importance of getting it right and everything will automate itself.
Whether you are a paying customer, doing a trial, or just want to ask a question about Q, you can reach our great support team at firstname.lastname@example.org. We’d love to hear from you!
If you’d like a one-on-one demonstration with a member of my team, click here to book.
Author: Chris Facer
Chris is the Head of Customer Success at Displayr. Here, and previously at Q (www.q-researchsoftware.com), he has developed a wealth of scripts and tools for helping customers accomplish complex tasks, automate repetitive ones, and generally succeed in their work. Chris has a passion for helping people solve problems, and you’ll probably run into him if you contact Displayr Support. Chris has a PhD in Physics from Macquarie University.