Essentially, my survey has >100 responses. It is inductive. I don’t know what I’m going to find, I am not testing a hypothesis.

the survey questions can be broken down into two simple groups; demographics (people) and the views of said people.

an outline of the questions and the data type are below.

I have generally only done deductive statistics previously, using experimental methods. Im therefore a little lost on inductive research.

I'm looking to try and find any patterns from the below. I.e. if qualification level is linked to some of the options that people put first in one of the ranking questions. Whether years’ experience means they are more or less likely to have heard of the product / know someone that has. Whether someone that thinks the biggest drawback is time (question 5), also says they think they need the most time to do the thing (question 6).

It could be that none of the inductive examples above would actually pull out in statistics….

however, to start with I am just looking for views about how to analyse?

Any help or guidance would be great

Demographics

1. Age – free number (nominal – continuous)

2. Sex – check box choice (nominal)

3. Qualification level - check box choice (categorical)

4. Years’ experience - check box choice (categorical)

5. Current role - check box choice (categorical)

Views

1. Have you heard about X? – Yes/No choice (categorical)

2. Have you ever used X? Likert (ordinal – once coded)

3. Know anyone else that uses X? Likert (ordinal – once coded)

4. Overall benefits of X? Likert (ordinal – once coded)

5. Overall drawbacks of X? Likert (ordinal – once coded)

6. How much time you should have to complete X? - check box choice (categorical)

7. Detailed benefits of X – Rank 1-7 (ordinal)

8. Detailed drawbacks of X – Rank 1-7 (ordinal)

9. Detailed facilitators of X – Rank 1-7 (ordinal)

10. Confidence of using X – Likert (ordinal – once coded)

11. How to improve confidence– Rank 1-4 (ordinal)