Spending differences and boring questions - view on the website
There are very few examples of exponential growth - poorly designed surveys might be one of the few examples that we all suffer through.
There are broadly two types of surveys:
(i) surveys where your goal is to measure a population and
(ii) surveys where your goal is commercial
There are times when these overlap, but it's less often than you think.
Categorical questions (gender, age range, profession) make sense when you want to understand a population e.g. a Census. These make much less sense in commercial applications, which is why I'm surprised to see them as often as I do.
Let's say you work in retail and find that, on average, women spend 20% more than men. Great - how can you use this? Do you assume all women will spend 20% more? When a woman is at the checkout, and their spending is lower than you expect, do you go and tell them to buy more stuff? If a man is spending too much do you ask him to return some items? Of course you don't. Why did you collect and analyse this data if you can't use it?
I could present the same examples for age, profession and income. Most surveys are poorly designed, illicit little useful information and waste the time of everyone involved. If you're going to include categorical questions in your survey, justify how you will use these to serve the people you're surveying. If you can't just leave it out.
Once you cut out all the crap questions, you've got space to ask something interesting. What might be interesting in retail? Is there a difference between why genders shop? Does one gender tend to 'replace' what they already have and another gender buy the same item in a different style? If you knew this was the case, maybe you'd have better conversations with your customers.
Andrew
Want more? Great.
On LinkedIn, I describe why this concept is hard to implement (there’s a bonus haiku).
Here's a short data bite if you want to hear me expand on the idea.