I Analyzed 200K Sessions Across 170 Countries on My Chemistry AI. Here's What Surprised Me.

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 semes