Getting a properly clean and tidy dataset is key. So before you start splicing and dicing your data, you need to be sure that the data is ready. So in lieu of given table specs, you’re going to be giving dataset specs.
The good thing about Crunch is that if something is missing in the data (eg: new questions need to be created or perhaps you need to add in additional data), this can be done by your DP department and it instantly updates the work you’re doing at your end.
That being said, the better the dataset is setup, the more seamless your experience will be.
Likewise, for DP departments, the better they can set up the data collection platforms, the more seamless their experience will be in processing the data for you. So the process for an optimum workflow really begins with questionnaire design and implementation.
For now, we’re focused on what you need to do as a research manager, working with your DP department to set it up.
How to brief a DP department
As mentioned you will be giving your DP department “dataset specs” instead of “tab specs” - the specifics of which depends on how you communicate with your DP department and your questionnaire.
Remember, the manipulation of your data is not a one-pass-opportunity from a Crunch perspective:
- Your DP can make further manipulations to the dataset
- You can make certain manipulations (such as NETs on question categories, filters, weights, other variables) within the app yourself
Things that you probably don’t need you DP to set up for you anymore (as you may have required from tab specs in the past):
- Merged categories (bandings)
- Banners (unless they have complicated columns)
- Weights (unless they are advanced weights)
Data specs checklist for Research Managers
We recommend working through the following checklist, based on your questionnaire and study, so that you have the optimal set up for your dataset from the start.
- List the multiple response questions within your questionnaire and their categories
- This way DP will ensure that all the variables involved in that questions are collated together.
- This includes multiple check-box questions (which Crunch calls Multiple Response) and scale-type grids (which Crunch calls Categorical Arrays)
- List of any questions that may need to be rebased
- For instance, a certain filter applied to a question based on a skip or an answer to a question prior.
- List any scale-type questions for which:
- You need summary tables for top 2 box, bottom 2 box etc
- You need the mean on a particular scale (eg: -5 to +5 or 0 to +10?)
- You need the questions banded up in a particular way (0-2, 3-4, 5-6, 7-10)
- List of the questions that require NPS recoding or banding
- For example, likelihood to recommend questions that have a scale (0-10 typically)
- List the scale/numeric questions where you need the mean calculated more than one way
- For example, excluding 0 or DK, as well as including 0 or DK
- List any "calculated" variables which are not specified in the questionnaire
- For example, “take Birth Year and create a new Age variable”
- List any questions that need to be “depiped”
- That is, a concept is piped through to a questions
- Sometimes the concepts are done in rotation, or randomized, and need “delooping”
- If you need any hierarchical reforming of the data (called stacking)
- For example, you collect information at the respondent level, but you need to analyse it at the brand-level.
- If you need any weighting variables set up in advance
Also, be sure to add additional things of your own.