Is Deway a Userpilot replacement?

For teams that want adoption to work without running an experimentation program, yes. For teams that specifically want to A/B test onboarding flows as a growth motion, Userpilot remains a good fit.

How long does switching from Userpilot to Deway take?

Deway installs with one line of code and learns your product in 72 hours. There is no flow migration or experiment reconstruction — Deway does not use the Userpilot content model.

How is Deway pricing different from Userpilot?

Userpilot carries a platform license plus the product-team hours spent building flows, segments, and experiments. Deway offers a free proof of concept, and paid pricing scales with usage — without the authoring backlog.

Does Deway support A/B testing?

Deway is not an A/B testing tool. Instead of testing variants of an authored flow, it observes what users are trying to do and guides them directly. If A/B testing onboarding is a core workflow for your team, Userpilot is better suited.

Userpilot alternative

Deway vs. Userpilot

Userpilot runs adoption as a continuous experimentation program — flows to build, segments to define, experiments to tune. Deway skips the experiment backlog and reads user intent directly. Same outcome. None of the program.

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Free proof of concept. No experiment backlog.

Side by side

Deway vs. Userpilot

	Userpilot	Deway
Core model	Build flows, segment users, run experiments, iterate.	Read intent in real time. Guide without authoring.
Setup	Build flows, segments, and goals before users see anything.	72 hours. One line of code.
Who runs it	A product team member owns the flow and experiment backlog.	Nobody. AI learns and guides autonomously.
Time to insight	Hypothesis → build → ship → wait for statistical signal.	Adapts continuously from observed user intent.
Who gets helped	Users who match your segments and experiments.	Every user, based on what they are actually trying to do.
Maintenance	Flows and segments require updating when the product changes.	Self-evolving. Zero rebuild.
Broken flows	Surface through analytics review.	Detected automatically. Escalated with full context.
Cost structure	Platform license plus ongoing product-team hours to build and tune.	Free proof of concept. Pricing by usage.

Core model

UserpilotBuild flows, segment users, run experiments, iterate.

DewayRead intent in real time. Guide without authoring.

Setup

UserpilotBuild flows, segments, and goals before users see anything.

Deway72 hours. One line of code.

Who runs it

UserpilotA product team member owns the flow and experiment backlog.

DewayNobody. AI learns and guides autonomously.

Time to insight

UserpilotHypothesis → build → ship → wait for statistical signal.

DewayAdapts continuously from observed user intent.

Who gets helped

UserpilotUsers who match your segments and experiments.

DewayEvery user, based on what they are actually trying to do.

Maintenance

UserpilotFlows and segments require updating when the product changes.

DewaySelf-evolving. Zero rebuild.

Broken flows

UserpilotSurface through analytics review.

DewayDetected automatically. Escalated with full context.

Cost structure

UserpilotPlatform license plus ongoing product-team hours to build and tune.

DewayFree proof of concept. Pricing by usage.

Adoption as an experimentation program

Userpilot is built around the idea that onboarding is a continuous optimization problem — pick a flow, form a hypothesis, build a variant, test it, iterate. That model works, and teams get real wins from it. The cost is a permanent backlog: someone has to run the program, author the flows, define the segments, and maintain the whole thing as the product evolves.

Experiments vs. intent

A/B tests are good for answering narrow questions: does variant A convert better than variant B? They're slower at a different question: what is this specific user trying to do right now? Deway answers the second question directly. It observes intent and guides the user — no hypothesis, no variant, no waiting for significance.

Who gets helped

In a flow-and-segment model, only users who match an authored path get a guided experience. Everyone else gets nothing. In an intent model, every user gets what they need because the guidance is generated against what they're actually doing, not against a pre-built flow.

When Userpilot is the right choice

If your team wants hands-on control — your own A/B tests, your own segments, your own experiment cadence — and you have the product-team bandwidth to run that program, Userpilot gives you the building blocks. Teams that run adoption like a growth experiment pipeline do well with it.

If you'd rather the adoption layer work without an experiment backlog, that's Deway.

Frequently asked

Try Deway on your own product

One line of code. Live in 72 hours. No experiment backlog.

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