Currently, I am spending four weeks in Japan, a mix of work, including workshops and presentations, and leisure activities (such as hiking and running). Today I checked into an AirBNB in central Tokyo and washed some clothes, after spending the weekend running a marathon on the West coast of Japan. The apartment is tiny, so I hung the clothes in the combined bedroom and living room. I have some standard photos I use to demonstrate using ChatGPT for qual, but I thought I would add a new one, so I took the photo below and asked ChatGPT to analyse it.

One key variable that differentiates one large-language model (LLM) from another is the size of its context window. In this post, I explain what a context window is and why it matters.

I think Deep Research is likely to replace quite a few types of research, some of them in the market research area. To investigate more, I tried two simple experiments. The first was to forecast the results of the recent Canadian Federal Elections  and the second was to forecast what the closing share price for Tesla would be in two weeks from the forecast. Both forecasts turned out to be interesting, as I will show below.

On the evening of 28 April, I requested that Deep Research forecast Tesla’s share price for 12 May and provide me with its reasoning.

It has forecast $300 (compared to the current price of $285.88), in the post I show you its full report.

Here is a post that shows how you can use custom GPTs to create better deliverables for your clients. Let them leverage the power of LLMs to bring your work to life.

Reports, dashboards and PowerPoint decks are depressingly static deliverables, focused on the creator’s perception of the world, rather than being user centric. In this post I will highlight a powerful alternative that leverages AI. I am talking about using Custom GPTs to deliver a responsive and intelligent tool to the user.

Here are six ideas for you to start using Custom GPTs in the field of market research and insights.