Flagship course
Plan Conversion Analytics Lab
Eleven weeks to make upgrade and plan conversion readable inside your own app — including the parts your current schema still labels as noise.
Who it is for
Product pairs, growth analysts, and data people who already ship a subscription or freemium app. You should be able to export an event sample. You do not need a mature experimentation platform.
It is a poor fit if you want paid-user acquisition tactics, creative testing, or a vendor certification. Those are outside the lab’s charter.
Learning outcomes
- A named inventory of every live plan, add-on, and paywall state
- An Upgrade Signals lexicon with capacity, comparison, and commitment shelves
- Cohort windows that match your billing cycle rather than a default 7-day template
- A ten-page diagnostic with a mandatory limitations section
- A shared vocabulary your PM, analyst, and finance partner can use in the same meeting
Modules
1. Mapping the plan surface
Screenshot, name, and version every way a user can pay more. Family plans, storage add-ons, and “restore purchase” paths are first-class objects, not footnotes.
2. Upgrade Signals vs vanity funnels
We retire impression-heavy upgrade funnels and replace them with markers that actually change belief. This module is the public method described on Upgrade Signals.
3. Cohort windows that survive seasonality
Thai festival calendars, payday cycles, and school holidays as analytics constraints. Students rebuild at least one mis-windowed chart from their own product.
4. Paywall state taxonomy
Hard-paywall, soft-paywall, feature gate, trial expiry sheet, grace period, and billing retry — each with events that should never share a name.
5. Pricing ladder diagnostics
Annual vs monthly vs add-on rungs. We look for false “upgrades” caused by currency rounding, storefront price tiers, and complimentary months.
6. Closing readout & Bangphlat review
Students present the ten-page diagnostic. Remote seats join by video; Bangkok seats may use the Charansnidvongs studio for the final hour. The limitation section is graded.
Instructor
Araya Wongsawat
Araya founded Backup Nodehub after eight years leading product analytics at a Bangkok subscription platform. She still reviews every Lab Cycle event dictionary herself. Guest desks occasionally include a former App Store operations lead; Araya remains the named instructor.
Informational pricing
A Lab Cycle seat is listed at USD 1,860. That figure covers teaching, the booklet, studio hours during the eleven weeks, and one alumni desk hour afterwards. It does not cover travel, implementation engineering, or a Residency.
This page cannot take payment. To request a seat, use the form below or write to info@backup-nodehub.digital. See also studio seats & fees.
FAQ
Do we need a specific analytics vendor?
No. Students have arrived with warehouse SQL, a product analytics SaaS, or a messy mix of both. The lab is vendor-agnostic. We do ask that you can export a sample; if legal blocks that, we work from a reconstructed schema and mark the limitation clearly.
Can two people from the same company share one seat?
One seat is one participant in studio hours. A second colleague may sit in lectures quietly, but only the named student submits the diagnostic. If both need critique, buy two seats — we would rather say that than pretend otherwise.
Is there a real limitation we should know before enrolling?
Yes. The lab does not cover advertising monetisation, interstitial frequency, or rewarded-video economics. If your “upgrade” is actually an ad-removal SKU sitting beside a subscription, we will teach the subscription side and explicitly leave the ad side out. Teams who need both often feel that gap in week four. We would rather you know now.
What language is the lab taught in?
English, matching this site. Thai-language clarifying asides happen in Bangphlat rooms when the whole table prefers it; written artefacts remain in English so mixed regional teams can share them.
Notes from past cycles
“Week five’s ladder diagnostic showed our ‘annual upgrade’ spike was mostly people buying the wrong storefront currency. Finance already knew; product did not.”
I wanted a faster dashboard module. Araya kept sending us back to naming paywall states. Annoying at the time. The taxonomy is what our new PM still uses.