The Diagnostic.
A focused 4-week sprint that opens the engine, reads the cohorts, and returns a prioritised intervention list. You leave knowing exactly which dial to turn first.
I help mobile game studios grow — user acquisition, ad monetization, mediation, and analytics, built over 575M+ downloads. The same systems earn the second session for apps, SaaS, and any digital product with commercial complexity.
Former Head of Revenue & Distribution at Games2win · Meta FAN Ambassador · Speaker at Google, Meta, Adjust, MoEngage, and CleverTap events
DWG—P01 I spent 15 years at Games2win across two stints — most recently as Head of Revenue & Distribution — running monetization, UA, and analytics across 575M+ downloads. Now I'm the person studios call when their numbers stop telling the story.
Gaming is where the rigour was built; the same systems travel to apps, SaaS, and any digital product with commercial complexity.
Every engagement runs through the same five lenses — drafted as line-art tokens, used as the visual menu of the practice. Pick one or stack them; the work flows the same way.
Mechanics, retention, monetisation. The behavioural engine inside every game that earns its second session.
Product, UX, feature architecture. How a screen becomes a habit — onboarding to power-user.
Cohorts, funnels, curves. The maths under the magic — turning playtime into a measurable system.
Monetisation, LTV, pricing. Where designed behaviour meets the P&L — without breaking trust.
Communities, virality, social loops. Who tells whom — and how that compounds into reach.
First choose the commercial problem. Then choose the working shape: a focused diagnosis, an embedded operating role, or a standalone artefact your team can ship. Scope is set on the first call.
A focused 4-week sprint that opens the engine, reads the cohorts, and returns a prioritised intervention list. You leave knowing exactly which dial to turn first.
Ongoing partnership — usually 2 days a week, 3-month minimum. I sit inside the product and revenue rituals, building the system as we ship it. The workhorse.
Standalone artefacts you can hand to a board, a buyer, or a team. Investor memos, monetisation teardowns, narrative decks, category POVs. Delivered in 2–6 weeks.
Four stages. Each one ends in a tangible artefact, so the engagement has a visible spine — and you never wonder what you're paying for, or what's coming next.
Workshop the system as-is. Map the loop, the funnel, the cohorts. Listen to ten interviews, read six months of telemetry. Find the truth on the page.
Sketch the intervention. Prioritise by effort × leverage. Pre-mortem the risks. Pre-commit to the metrics we'll move and the ones we'll watch but not chase.
Ship in two-week beats. Each one paired with a measurement plan, a guardrail, and a kill criterion. Embedded inside your standups, not parallel to them.
Convert wins into the operating system. Write the runbook, document the new defaults, codify the rituals. The engagement ends, the muscle stays.
Due to the competitive sensitivity of live product metrics, ad network setups, and analytics pipelines, full outcomes and diagnostic details are shared directly with qualified studios, founders, and product leads under mutual NDA.
View Confidential Dossier & request references“In conversations where most people show up with one piece of the puzzle, Tejas would come in with the whole picture -> monetisation, store performance, growth, how they talk to each other. … A lot of people have managed a revenue function but very few have actually built one from ground up to scale. Tejas is one of the few.”
“Tejas is a rare leader who combines high-level strategic vision with a deep, technical understanding of the ecosystem. … His feedback on monetization products is some of the most insightful in the industry; he doesn’t just look at the "what," but provides the "why" that helps partners build better products.”
“What stands out about Tejas is how hands-on he is with measurement infrastructure. He doesn’t treat it as something to be abstracted at an executive level; he engages with it like a practitioner. He asks sharp, informed questions around attribution windows and cohort performance, and he’s not hesitant to challenge the data when something doesn’t line up.”
14 free model calculators built to clarify product leverage. No paywalls, no signup, no fluff. Fit cohort retention, optimize mediation waterfalls, evaluate payback limits, and decompose business metrics.
Fit a power-law decay curve to your cohort metrics. Project Day 365 survival and estimate cohort LTV.
Run simulation → D—05 · Networks MediationCalculate market-blended eCPMs, identify waterfall leakage, and estimate the financial lift from mediation optimisation.
Calculate yield → D—02 · Apps PaybackModel CAC payback windows and ROI curves. Evaluate cash exposure limits and campaign health grades.
Grade campaigns → D—03 · Analytics KPIDecompose your business funnel into sub-metrics. Simulate optimisations across retention, engagement, and acquisition.
Decompose funnel →A practical ASO operating model for mobile teams: connect store intent, creative promise, first-session delivery, retention, ratings, and paid acquisition into one learning loop.
A rewarded ad is not only an ad format. It is a product event. The same placement can be a continuation mechanic in one context and an escape route in another.
Players don't usually leave on the day they stop opening the app. The exit starts earlier — when play quietly turns into maintenance.
Leaving a long role is described as freedom. What I notice more is the absence of structure — and the work of deciding what gets protected.
"Paid growth got expensive and privacy changes broke a lot of the attribution studios used to lean on. The teams that hold up are the ones that can read a cohort curve and act on it — and that skill is still rarer than it should be."
I ran up to $700K a month in UA at 45% blended ROAS, and I can tell you the budget was never the hard part. The hard part is knowing which cohort deserves it, and having the analytics and monetization system to prove it.
The Game Scientist is the practice built on that work — product, revenue, and analytics read together, without picking a tribe. It started in games, and the same read holds for apps and digital products carrying real commercial complexity.
Thirty minutes, no slides, no pitch. Bring one number you can't explain — we'll spend the call inside the system that's hiding behind it.