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ML is not that good at predicting consumers' choices

statmodeling.stat.columbia.edu

31–40 of 228 posts

Re: ML is not that good at predicting consumers' choices

#31

This review omits techniques from reinforcement learning (especially bandits) that have been used successfully in industry for years now.

I think that the main issue is less the technique (although… yes, please use RL if you can) and more the lack of data. Browsing gives very little insight: dwell-time is a poor proxy for interest, and mixes horrid ideas that are so bad they are worth sharing with friends and confusing photos where you need to squint to figure out if it’s what you are looking for.

Both e-commerce and social media are really not good at gathering express feedback for what people want and valuing that expressly. Please, let me tell you that I did spend time looking at this thread about the latest reality TV scandal but I don‘t want to hear about it ever again! Please, let me tag options as “maybe” or let me tell you what you’d need to change for me to buy that shirt. Public, performative Likes and Favourite lists that are instantly reactivation spam-fodder… Come on, you know better.

I used to work for a big e-commerce site (the leading site for 18-25 y.o. females). We had millions of references (really) and it was a problem. The search team had layers upon layers of ranking algos, incredible papers at conference… but still, low impact on conversion. It was more than anything else that we could do, but nowhere as transformative as it could be. Instead, I suggested copying the Tinder interaction in a companion app:

* left, never see that item again;

* right, add it to a long list of stuff you might want to revisit. We probably would have to separate that from the Favourite list to avoid clutter, but maybe not, to make that selection worthwhile.

The learning you could get from that dataset, even with a basic RL algo to queue suggestions… People thought it was “too much” which I’m still bitter about.

Re: ML is not that good at predicting consumers' choices

#32
post #3

While not exactly aligned to the research, I've been surprised how poor Nest Thermostat's learning feature is. The main selling point for Nest is having a "learning thermostat". Perhaps my schedule is just not predictable enough, but the auto-generated temperature schedules it generates after its "learning" period is not even close to what I would manually set up on a normal thermostat. Maybe I'm just an "edge case"…

"Why am I sweating right now? Oh, the Nest set the temperature too high again!" And then after a few instances, I just turn off all the automation and set up a schedule like normal. Same with the "away from home" which seems to randomly think I'm away and I have no idea why. Oh, and the app doesn't show me filter reminders, only the actual device, which I never touch all the way downstairs. There's not even any statu…

Same story. We moved into a house that had a Nest preinstalled. Got everything set up, and noticed after a couple of days we would always wake up freezing in the early morning. Nest was all over the place and I just turned off the automation.

Re: ML is not that good at predicting consumers' choices

#33

It is the same on Netflix. I have phases where I watch a certain genre for a few weeks and then move on. For example after a few Scandi crime series it is time for something else. However, at the same time my daughter loves Animé and pretty only watch that. It is really hard for an ML algorithm to grab these nuances.

Netflix makes a far more obvious sin: not having “who is watching” as boolean choices. If I am watching with my partner, I want both of our accounts to mark that series as viewed. And I really want Netflix to tell me what I’m watching with her so that I don’t continue watching it without her because I will be single if that happens (again).

Re: ML is not that good at predicting consumers' choices

#34
ML is there to maximize business income--nothing else.

If ML was benefiting me, it would know that 90% of the time I fire up Hulu I plan to watch the next episode of what I was watching last time. And it would make that a one click action. Instead I have to scroll past promotional garbage...every single time. Assholes.

Re: ML is not that good at predicting consumers' choices

#35
post #3

While not exactly aligned to the research, I've been surprised how poor Nest Thermostat's learning feature is. The main selling point for Nest is having a "learning thermostat". Perhaps my schedule is just not predictable enough, but the auto-generated temperature schedules it generates after its "learning" period is not even close to what I would manually set up on a normal thermostat. Maybe I'm just an "edge case"…

"Why am I sweating right now? Oh, the Nest set the temperature too high again!" And then after a few instances, I just turn off all the automation and set up a schedule like normal. Same with the "away from home" which seems to randomly think I'm away and I have no idea why. Oh, and the app doesn't show me filter reminders, only the actual device, which I never touch all the way downstairs. There's not even any statu…

Maybe it considers environmental impact of air conditioning in its models and tries to nudge users into tolerating higher temps.

Re: ML is not that good at predicting consumers' choices

#36
post #22

You just bought a washing machine... could I interest you in a washing machine?

GPT can solve this! I prompted it with "Sarah bought a washing machine and a ". It completed "dryer.".

Another "If you buy a hammer you might also want to buy " -> "a nail". Ill forgive the singular.

Just to be clear those are not cherry picked - they were my first two attempts.

Re: ML is not that good at predicting consumers' choices

#37
post #22

You just bought a washing machine... could I interest you in a washing machine?

While the chief absurdity is very clear (also mocked by Spitting Image - J.B. on a date: "You loved that steak? Good, I'll order another one!"), I am afraid that the intended idea may be that your memory about the ads of what you just bought will last as much as said goods.

Utter nightmare (unnatural obsolescence, systemic perversity, pollution...) but. I have met R'n'D who admitted the goal was just to have something new to have people want to replace the old, on unsubstantial grounds.

Re: ML is not that good at predicting consumers' choices

#38
post #34

ML is there to maximize business income--nothing else. If ML was benefiting me, it would know that 90% of the time I fire up Hulu I plan to watch the next episode of what I was watching last time. And it would make that a one click action. Instead I have to scroll past promotional garbage...every single time. Assholes.

Honestly a lot of this ML to me seems eerily similar to how in older times people would use sheep entrails or crow droppings to try and predict the future. I mean basically that is what ML is, trying to predict the future, the difference is they called it magic, we call it math, but both seem to have about the same outcome, or understandability.

Re: ML is not that good at predicting consumers' choices

#39
post #19
post #12

Earlier quoted context omitted.

random will perhaps

It's funny you say random because if consumer choice was actually random with some known distribution it would be extremely predictable, no ML needed.

Known distribution doesn't mean extremely predictable.

For example, if your water consumption is log-Cauchy, I will have a very hard time predicting it because the variance is infinite.

Re: ML is not that good at predicting consumers' choices

#40
post #3

While not exactly aligned to the research, I've been surprised how poor Nest Thermostat's learning feature is. The main selling point for Nest is having a "learning thermostat". Perhaps my schedule is just not predictable enough, but the auto-generated temperature schedules it generates after its "learning" period is not even close to what I would manually set up on a normal thermostat. Maybe I'm just an "edge case"…

Google destroys any great product they acquire (except google maps and YT I guess).
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