Beeminder aggregate analysis

I’m just wondering whether any analysis has been done across the beeminder dataset of how people make progress towards goals.

I suspect that weight loss would be an interesting one to explore. Is it more effective to never derail or not. Do people who meet their goals have easier or harder targets. Do people who meet weight loss goals have more or fewer goals than others?


We actually have some datasets we’ve shared with researchers and can share with you all too! One thing that makes answering these kinds of questions surprisingly tricky is that there’s so rarely a concept of “meeting goals” and we generally don’t have data to distinguish such from giving up. Then there’s the fact that never derailing could mean you’re doing great and are super motivated to not derail… or it could mean you set your slope so conservatively that you’re just doing what you always did and it’s all pointless.

Anecdotally we know that people who derail a lot and pay us a lot are the ones for whom Beeminder is inducing massive positive behavior change. Which of course makes sense – why else would they be willing to pay those pledges but that it works?

As for data, we’ve also made this especially hard on ourselves by being so general. Like a lot of Do More goals are completely opaque to us and it’s very hard to determine anything about how much real-world success is happening on those. Even if we know you have a weight loss goal we often don’t even know the units. We’ve recently made units a bit more focal in the UI and have plans to make them more so.

So, yeah, great question. Harder than it sounds to get answers, but if you want to look at anonymized datasets, let us know!

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Sadly such analysis is beyond both my available time and my skill set as is obvious from the number of challenges I hadn’t thought of :wink: