I run a niche AI SaaS — Chemistry AI, an AI-powered chemistry problem solver. Students type or snap a photo of a chemistry problem and get step-by-step solutions in seconds.
About 10 months ago, the product started getting real traction. After nearly 200,000 sessions and visitors from 170+ countries, I got curious: when do students actually use AI for studying?
Not "when do journalists think they use it". When does the raw traffic data say they do?
I dug into my analytics. Here are five things I found.
1. The Academic Calendar Controls Everything
Here's monthly traffic, indexed so the peak month = 100%:
Month Traffic
───────── ────────────────────────────
Jun '25 █ 6%
Jul '25 ███ 14%
Aug '25 ███ 17%
Sep '25 ██████████ 49%
Oct '25 ████████████████████ 100% ← peak
Nov '25 ███████████████████ 95%
Dec '25 ████████████ 59%
Jan '26 █████████ 43%
Feb '26 █████████ 47%
The pattern is unmistakable. Traffic quadrupled between early September and late October - the first eight weeks of fall semester.
Then the semester ended, and things got dramatic.
December 13 - the Saturday after many US schools finish finals - traffic suddenly dropped to less than half of the previous Saturday.
By Christmas Day, it was just 12% of the October peak. For nearly two weeks the site was a ghost town.
Then, around January 6, traffic started climbing again as spring semesters kicked off. By February it stabilized at roughly half the October peak - a typical spring semester level.
Even Thanksgiving week showed a clear ~30% dip compared to surrounding weeks. American students clearly have priorities. 🦃
Takeaway: If you're building for students, your traffic is the > academic calendar — midterms, finals, and breaks are all visible in the data, down to the exact day.
2. There Are Two Daily Homework Rushes
Since the US is my largest market (~50% of traffic), I'll anchor this to US Eastern Time. Keep in mind this blends activity from 170+ countries:
Hour (ET) Traffic
────────── ────────────────────────────
3 AM ██████████ 51% ← minimum
5 AM ██████████ 52%
7 AM █████████████ 66%
9 AM ██████████████████ 89%
11 AM ████████████████████ 98%
12 PM ████████████████████ 100% ← global peak
2 PM ███████████████████ 97%
4 PM █████████████████ 86%
6 PM ████████████████ 82% ← afternoon dip
8 PM ███████████████████ 94%
9 PM ████████████████████ 98% ← homework rush
10 PM ███████████████████ 96%
11 PM █████████████████ 84%
Two peaks:
Peak 1: Midday (11 AM – 2 PM ET). This is when the US school day is active and it's evening in South/Southeast Asia — India, Philippines, and Indonesia are my 3rd, 4th, and 5th largest markets. Multiple time zones stack on top of each other.
Peak 2: Evening (8 – 10 PM ET). The classic homework rush. Students procrastinated all day, and now it's crunch time.
There's even a visible afternoon dip around 5-6 PM - dinner, commuting, a brief illusion of free time - before the evening peak kicks in.
The daily minimum is at 3 AM Eastern, but traffic is still at 51% of peak. Because with users in 170+ countries, it's always homework time somewhere.
The site never sleeps. Neither, apparently, do chemistry students.
3. Nobody Studies on Saturday
Day Traffic
─────────── ────────────────────────────
Monday ███████████████████ 94%
Tuesday ███████████████████ 97%
Wednesday ████████████████████ 100%
Thursday ███████████████████ 97%
Friday ████████████████ 82%
Saturday ███████████ 56%
Sunday ████████████ 62%
Weekday traffic is 60% higher than weekends. That's not a subtle difference - it's a canyon.
Saturday is dead last. Sunday recovers slightly (perhaps driven by the "oh no, it's due tomorrow" effect).
Friday is already 15% below Monday-Thursday, suggesting the weekend mindset kicks in early.
But here's the interesting part: Monday has the lowest bounce rate (17.4%) and the longest average session - 5 minutes 44 seconds, compared to Thursday's 5:26. Students are most engaged on Mondays.
My theory: Monday is when assignments are due. People aren't just glancing - they're working through problems seriously. By Thursday, they're speed-running.
4. 170+ Countries, and It's Always Homework Time Somewhere
Google Search Console shows clicks from over 170 countries.
Chemistry uses the same periodic table everywhere - H₂O is H₂O whether you're in Kansas or Kathmandu.
Top markets by click volume:
# Country Share of traffic
1 🇺🇸 USA ~46%
2 🇨🇦 Canada ~11%
3 🇮🇳 India ~5%
4 🇮🇩 Indonesia ~4%
5 🇵🇭 Philippines ~3%
6 🇪🇬 Egypt ~3%
7 🇬🇧 UK ~3%
8 🇦🇺 Australia ~2%
The US dominates - but it's still less than half. The majority of usage comes from a massive long tail of countries, most contributing 1% or less individually, but adding up to over 50% combined.
Some of those countries surprised me. I didn't expect Egypt to be a top-6 market, or Mongolia and Sri Lanka to show up at all.
But it makes sense: an English-language AI solver is accessible to anyone with internet and some English proficiency - and in many of these countries, quality chemistry tutoring is expensive or simply unavailable.
The practical effect of this global spread? Time zone diversity is a feature. My daily traffic minimum (around 3 AM Eastern) is still 51% of peak - because when American students are asleep, it's afternoon in South and Southeast Asia.
There's also a clear language barrier visible in the data.
Countries where English isn't widely spoken - Brazil, Vietnam, Thailand, Argentina - show significantly lower search rankings for my site and, consequently, fewer clicks. That's a clear signal about where localization could unlock growth.
Takeaway for SaaS builders: If your product solves a universal
problem, the long tail of "small" countries can collectively become your biggest market. But don't mistake good search rankings for user enthusiasm - in small markets you often rank higher simply because there's less competition.
5. 43% Come Back — and Power Users Are Fascinating
I expected most visitors to be one-and-done: solve the problem, close the tab, never return. The data says otherwise:
Visit frequency - Share of sessions
First visit - 57%
2-3 visits - 22%
4-7 visits - 11%
8-15 visits - 6%
16+ visits - 4%
43% of all sessions come from returning visitors. For a homework tool, that's surprisingly sticky.
But the truly fascinating segment is the power users - a small group who've visited 100+ times. Their behavior is completely different from everyone else:
⏱️ Average session: ~2 minutes
📄 Pages per visit: ~1
📈 Lowest bounce rate of any segment
They've turned the AI into a reflex: open the site, paste the problem, get the answer, close the tab. No browsing, no exploring, no hesitation. Pure muscle memory.
These users don't need the UI to be fancy. They need it to be fast.
What This Means (If You're Building a SaaS)
Five things I'd take from this data:
- Respect the calendar. If your users are students, your traffic follows institutional rhythms. Plan launches, A/B tests, and infrastructure for peak season — not Christmas.
- Optimize for the evening rush. 8–10 PM is when uptime matters most. That's not when your engineering team is at their desks.
- Global coverage = resilience. Traffic from 170+ countries means my daily minimum is still 51% of peak. Time zone diversity is a feature.
- Power users are a different product. The person visiting their 200th time has totally different needs from a first-timer. One needs onboarding; the other needs speed.
- Small markets, big hearts. Egypt, Mongolia, Sri Lanka — I never targeted them, but they found the product. If your tool solves a universal problem, let the long tail surprise you.
What about you? Have you dug into your traffic data and found surprising patterns? I'd love to hear what your users are up to when they think nobody's watching.
If you're curious about the product behind the data:
Chemistry AI - an AI-powered solver for chemistry homework and beyond.
Top comments (0)