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77 products. 6 brands. Five findings — none on the front of the pack.
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When you check fibre, you are predicting a second nutrient with 81% accuracy.
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50,000 device users · 4 occupation groups · 2 platforms
Professionals log a quarter of all weekend screen hours — yet Android and iOS split the market almost perfectly in half
Two very different stories live inside this dataset. On one side, occupation carves up digital time with surprising sharpness — Professionals alone account for 25.4% of all weekend screen hours across four groups that should, in theory, share it equally. On the other, the platform war that has defined a decade of tech strategy turns out to be essentially a draw: Android holds 50.16% of devices, iOS 49.84%, a gap of just 160 users across 50,000. The data is telling us that who you are professionally shapes how much you stare at a screen on Saturday, but the device in your pocket is essentially a coin toss.
Weekend screen time × Occupation
Professionals account for 25.4% of all weekend screen hours — the single largest share among four occupation groups that together cover the entire dataset
App usage count × Occupation
The same Professional group drives 25.3% of total app usage, confirming that occupation is the master variable for digital engagement intensity
Device type split
Android leads iOS by just 160 devices across 50,000 users — a 0.32-percentage-point margin that is statistically indistinguishable from parity
Gender distribution
Male, Female, and Other each hold almost exactly one-third of the sample, making gender the most balanced dimension in the entire dataset
Executive summary
In 50,000 users, occupation is the only dimension that actually divides people — everything else is a coin toss
Professionals dominate both weekend screen time and app launches with a signal strength six times greater than gender and twice that of device type — occupation is the variable that earns attention. Platform, gender, and every other demographic cut in this dataset resolves to statistical noise; the question worth asking is not who someone is, but what they do for a living.
Key findings
Weekend screen time by occupation
0.47App usage count by occupation
0.46Device type split
0.22Professionals own a quarter of all weekend screen hours across just four groups
Imagine four occupation groups splitting a weekend equally — each should claim roughly 25% of total screen time. Professionals do claim 25.4%, but the gap between the top group and the bottom is 1,676.9 hours in aggregate, and the p90-to-p50 spread of 1,396.2 hours dwarfs the p50-to-p10 spread of just 281.1 hours, meaning the concentration lives entirely at the top. The data is not describing a gentle lean; it is describing a ceiling that only one occupation group consistently touches.
101,609.1
Professional weekend hours
Largest single-group total
25.38%
Share of total
Of 50,000-user dataset
1,396.2 hrs
P90–P50 gap
Top-to-median spread
75.18%
Top-3 combined share
Three groups, three-quarters of hours
3 more findings — plus interactive charts, spectrum analysis, and the full closing
Generated from 50,000 real user records in under 5 minutes.
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Findings arrive as structured chapters with narrative body text — not a bullet list, not a table, not a summary. Written clearly enough that any stakeholder can follow it without a briefing.
The most important finding is always first — ranked by how much it would change a decision, not by p-value. Nothing is buried. Nothing requires hunting.
Charts appear inside the narrative, right where the text references them. No flipping to appendices. Hover over any data point. Filter. Explore.
Where the data shows a strong relationship, Quantiri builds a live predictor. Drag a slider. Watch the outcome update. Decisions stop being theoretical.
The report begins appearing within 3 minutes. No spinner. No loading state. Seeing the reasoning emerge in real time makes every finding more credible.
Every report closes with numbered, sequenced actions — ranked by impact, grounded in evidence, written so anyone on the team can present them without re-explaining the analysis.
Same data.
Different reality.
What goes in on the left. What comes out on the right. The only thing that changes is whether Quantiri is in between.
77 rows × 16 columns. The answer is in here. Somewhere.
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We used to spend three days turning analysis into a deck the board could read. Quantiri does it before the meeting is even scheduled.
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Yes. Quantiri doesn't use pre-built templates. It reads the structure and patterns in your actual data and derives the narrative from what it finds — whether that's retail performance, healthcare outcomes, financial metrics, or anything else.
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