Years of Classes Taught, and the Algorithm Prices Her Against Last Week's Signups
Iloilo tutors on overseas platforms watch their rates drop as the app benchmarks them against cheaper newcomers. The ones who set a floor in Discord get undercut by the app that hosts their classes.
Picture a tutor in Iloilo who has taught English on an overseas platform for a while now. She opens her dashboard and finds her suggested rate lower than it was a few months ago. Nothing changed about her work. The app signed a batch of new tutors in a cheaper market, and the number reset underneath her.
This is how dynamic pricing works when you are the product being priced. Tutors say the platform benchmarks their hourly rate against whoever it onboarded most recently, and it onboards constantly. Every fresh signup from a market with lower wages appears to pull the average down. Experience, which is supposed to be leverage, becomes something the system discounts.
Seniority reads as overhead
Older tutors cost the platform more per booking. Tutors report that students get nudged toward cheaper profiles while the veterans' bookings slow down. You can keep your rate high and watch your calendar empty, or you can match the floor and keep the lights on. Most match the floor.
The pitch for these platforms is that you set your own price. You do, technically. Then the app decides who sees it, where you rank, and how your "recommended rate" compares to the person who started last Tuesday. The lever exists. The hand on it belongs to the company.
What makes it sharper is that the benchmark keeps moving. The platform keeps recruiting in markets where tutors will work for less, and each new cohort becomes the new reference point. The floor is not fixed. It drops every time someone newer and hungrier signs the terms.
The Discord holds the line, the app routes around it
Tutors are not passive about this. In group chats and Discord servers, they coordinate, agree on a rate nobody will teach below, share screenshots of lowball students, and warn each other about the latest drop. It is old-fashioned labor solidarity, built over voice channels between classes.
The problem is that the thing they are organizing against hosts their classrooms. The app sees the empty slots a rate-floor creates and fills them with whoever will take the price. A coordinated refusal, tutors say, just seems to surface a cheaper profile instead. You can hold the line in the Discord, but the booking engine routes around you.
There is no union contract here, no collective bargaining recognized by anyone with authority over the platform. There is a terms-of-service agreement each tutor accepted alone, and a pricing model that treats their collective floor as a gap in supply to be closed.
So the math lands where it always does. A tutor in Iloilo with a stack of good reviews can find herself earning less per hour than before, teaching more hours to make the same month, and paying the same rent. The algorithm calls it market efficiency. On her end it reads as a pay cut she never agreed to, delivered by an app that will happily host the meeting where she complains about it.
