Asking ChatGPT for advice about research methods – a Kano example #AI Tip

Two or three times a year I receive a message from an agency saying their client wants to do a study using the Kano Model. They ask whether I can explain it to them so they can respond. In the future, they will get a faster and cheaper answer by asking ChatGPT (or any other leading AI platform). I also get queries about various techniques, such as MaxDiff, ServQual, and Driver Analysis. ChatGPT will respond faster and cheaper than I will to all of these.

#AI Tip – Ask AI for multiple suggestions, to leverage the human element

Here is another tip from my courses on how to use Copilot and ChatGPT for market research and insights. Generative AI can be used to ask for suggestions on how to do a specific task. For example, we might ask the AI platform to design a research project. However, I have found that it is a good idea to ask for multiple suggestions.

When should you use ChatGPT and when should you use the API version?

Should you use the web-based ChatGPT or create routines that call the ChatGPT API? In this post I set out my advice.

Analysing Open-ended Comments (almost) for free

Do you have a set of open-ended comments that you’d like to analyse, for example from a survey? With ResearchWiseAI you can do that. You can read how to do it in this post.

Creating Virtual Ray, a Custom GPT

One of the neat features of ChatGPT is the ability to create Custom GPTs. A Custom GPT allows you to build a bespoke tool on top of ChatGPT, creating a unique product. In this post I am going to tell you how I created a simple ‘Virtual Ray’ via a Custom GPT.

ChatGPT or Microsoft Copilot – which is right for you?

Here is my take on the differences between Microsoft’s Copilot and OpenAI’s ChatGPT and some thoughts on which is best for you.

Draft Synthetic Data Manifesto

In this note I set out what I believe to be Synthetic Data, why we need to define synthetics data, and some guidelines that I think vendors and buyers should adopt. I have been involved in a wide range of discussion with a wide range of organisations, but these views are my views, they do not represent the views of anybody else.

AI and Synthetic Data Dominate ESOMAR Congress in Athens

Last week saw over 1000 insight and market researchers from 78 countries gather in Athens for ESOMAR’s Annual Congress. With three stages and a host of side events, the range of topics discussed was immense, but one theme stood out above all the rest and that was AI. One aspect of AI in particular was widely discussed, reviewed and commented on – namely Synthetic Data.

Most good research depends on synthetic analysis!

One of the things that has caught my eye about the recent discussion about synthetic data have been the different reactions to the word synthetic. Whilst most of the debate has focused on the underlying methods, there have been numerous sideswipes at the word “synthetic”. At first this struck me as odd, so I did some introspection and reading to find out why my reaction differed from that of others. I quickly realised that, in many cases, it reflected people’s arts/science background along with various life experiences, cultural phenomena, and interests.

Python, one of the reasons ChatGPT is pretty good at maths

One key reason ChatGPT is good at handling mathematical tasks and data analysis is its integration with Python, especially in its premium versions. Python not only powers the solutions provided but also allows users to see how those solutions are generated. In this post I show how you can take advantage of this.