[niko001]

Really interesting approach! I can see this being useful. How are you dealing with short/medium-term changes in consumer sentiment, I assume your model is currently fairly static? For example, the results to "Would you buy an e-bike?" might change over time as cities add charge-points or additional bike paths, prices for e-bikes go down, etc. And as a more extreme example, the answer to typical YouGov questions like "Who will you vote for in the next presidential election" will obviously change daily based on a multitude of factors that aren't present in your training data.

[timshell]

The data we trained on has year, so we can specify the year you ask the question (the default is 2023). You can also see how answers change over time. [1] shows how the distribution for "Do you support the President" changes from 2000 to 2023 (see the 9/11 spike, end of Bush era, Obama era, Trump era, etc.)

[1] https://roundtable.ai/sandbox/2dd4e9d32c24e9abff01810695e948...