Queue literacy
Define behavioral queues with observable entry and exit rules.
Flagship course
Cohort Signal Studio
An eight-week practice studio where you convert messy behavioral signals into segment grids your stakeholders can fund, debate, and retire on purpose.
Learning outcomes
Transparent clusters
Build segments you can explain without invoking a mystery model.
Decision triggers
Document when a segment should change budget, messaging, or product priority.
Modules
1 · Inventory without paralysis
Audit events, properties, and gaps. Ship a minimum viable taxonomy.
2 · Queue construction
Translate journeys into ordered behavioral queues with time windows.
3 · First-pass grids
Cluster with transparent rules; name segments last.
4 · Decision-trigger worksheet
Connect each segment to a budget or roadmap lever.
5 · Drift detection
Install checks for silent cohort decay.
6 · Stakeholder critique
Practice short readouts that invite disagreement.
7 · Capstone grid
Deliver a living segment map with retirement criteria.
8 · Production handoff
Document owners, refresh cadence, and open questions.
Instructor
Kanya Srisuk
Former marketplace analytics lead based in Bangkok. Kanya coaches Cohort Signal Studio with a bias toward readable rules over opaque scores. She has facilitated Grid Intensives for fintech and retail teams across Thailand.
Informational price for Cohort Studio: THB 24,500. No checkout on this site — see Pricing.
Learner notes
“The Module 4 worksheet exposed that our ‘loyal’ segment had no budget owner. Awkward, useful.”
★★★★★ · “Capstone feedback was blunt. I needed that more than another dashboard template.”
FAQ
Who should enroll?
Analysts, researchers, and PMs who already touch event data and can bring a real product question.
What tools do we use?
Spreadsheets, your existing warehouse exports, and simple visualization. We do not lock you to one SaaS.
What is a real limitation?
Cohort Signal Studio will not replace a full data-engineering rebuild. If your event stream is fundamentally broken, we can diagnose the gaps — we cannot invent clean data mid-course.
Is there a refund window?
Yes. Review eligibility on the Refund page before enrolling.