Advanced analytics is not a service line at ETK — it is our trademark. We apply machine learning and AI to build decision tools you operate, not decks you file. This is what sets us apart from every other research firm.
The deliverable is where most research dies. We build ours as interactive applications — filterable dashboards and decision simulators your team operates long after the project closes.
A wind-tunnel for product and pricing decisions, powered by two engines. A Latent Class Choice-Based Conjoint (LC-CBC) model simulates the market — how customers across distinct segments react to your move. A Bayesian Decision Network (BDN) — machine learning — then simulates how competitors react back. Demand-side and competitive response, in one loop.
LC-CBC answers "how will the market respond?" · BDN answers "how will competitors respond?" Toggle the competitor-reaction engine below and watch the result re-settle — the difference between a first-order estimate and seeing around the corner. The demo behaves like a delivered tool; only the numbers are illustrative.
Machine-learning models that detect emerging patterns and simulate scenarios — anticipating market behaviour, not just describing what already happened.
We build our own instruments — Brand Compass™, Distance Matrix™ and bespoke simulators — continually developed in-house and found nowhere else.
We train enterprise teams in statistics and data manipulation — including clients such as Philip Morris — so the capability outlives the project.
Tell us the decision you're facing — we'll show you what a living ETK application looks like built around it.
Start a conversation →