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What are the most surprising data exploration discoveries you've made in your work?
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I've been working with customer data for about three years now and honestly, some of the data exploration discoveries I've made have completely changed how we approach marketing.
The other day I was just messing around with some purchase history data and found that customers who buy on Tuesdays actually have a 40% higher lifetime value than weekend shoppers. Totally unexpected since we always assumed weekends were peak buying times.
What about you guys? Any interesting data exploration discoveries that made you rethink your assumptions? I'm always looking for those hidden patterns that aren't obvious at first glance.
That Tuesday finding is really interesting! I had something similar happen with weather data. I was analyzing retail sales and found that moderate rain (not heavy downpours) actually increases in-store purchases by about 25% compared to sunny days. People apparently don't want to be outside in light rain but heavy rain keeps them home entirely.
My most surprising data exploration discoveries have been in healthcare data. I was working with patient readmission rates and found that patients discharged on Fridays had significantly lower readmission rates than those discharged earlier in the week. Took us forever to figure out it was because family members were more available to help over the weekend.
What's wild is how often these data exploration discoveries seem obvious in hindsight but you'd never think to look for them initially.
I love hearing about these kinds of data exploration discoveries! In my personal tracking, I found something similar but on a smaller scale. I was tracking my coffee consumption and work output and discovered that my third cup of coffee actually decreases my productivity by about 30%. First two cups help, third one hurts. Would never have guessed that without actually looking at the data.
The most valuable data exploration discoveries for me have been around habit stacking. Found that if I do my morning meditation right after making my bed (instead of at some random time), I'm 80% more likely to actually do it consistently. Small patterns like that add up.
Do you think most companies are missing out on these kinds of insights because they're not doing enough exploratory analysis?
As a database guy, I see this all the time. People focus so much on the obvious metrics that they miss the real data exploration discoveries.
One of my favorites was when a client was complaining about slow query performance. After some digging, I found that their peak usage wasn't during business hours like they assumed - it was actually between 2am and 4am when their automated backup systems were running. The data exploration discoveries showed that their indexing strategy was completely wrong for their actual usage patterns.
Another one: found that deleting old log files actually made certain queries slower because the database optimizer was using different execution plans. Sometimes the counterintuitive stuff is what matters most.
The key is just spending time poking around without a specific question in mind. That's when you make the best data exploration discoveries.
I review apps for a living and one of the most interesting data exploration discoveries I made was about user onboarding.
I analyzed data from about 50 different apps and found that the optimal number of onboarding screens is actually 3, not 5 or 7 like everyone uses. Apps with 3 screens had 40% higher day 7 retention than those with more. But here's the weird part: apps with only 1 onboarding screen performed almost as badly as those with 7+.
The data exploration discoveries around user behavior are always the most surprising to me. Like how changing a button from blue to green can increase conversions by 15% in some markets but decrease them in others.
Makes you realize how much we're just guessing until we actually look at the data.
In my coding work, I've made some cool data exploration discoveries around bug patterns.
Was analyzing commit history and found that bugs introduced on Fridays are 3x more likely to be severe than bugs introduced earlier in the week. Probably because people are rushing before the weekend.
Also found that the most bug-prone time of day is actually right after lunch, not late afternoon when everyone assumes people are tired. My theory is that people come back from lunch and jump into complex tasks without properly warming up their brains first.
These data exploration discoveries have actually changed how I schedule code reviews and testing now. No more major changes on Friday afternoons!
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