Lytik identifies meaningful changes in how people use your product, explains the evidence, and connects each recommendation to an experiment so you can measure what worked.
Product teams already collect substantial behavioral data. The harder task is identifying which changes matter, understanding the evidence around them, deciding what to improve, and measuring whether the decision worked.
Lytik follows one sequence: a Signal surfaces a change, evidence and confidence support it, a recommendation suggests what to do, an experiment tests it, and the result is measured.
Across your product, Lytik surfaces changes worth a closer look — not every fluctuation.
A Signal describes what changed, where, and for whom, in words a person can act on.
Each Signal is paired with the behavioral context that surrounds it — journeys, segments, timing, and related metrics.
An honest indication of confidence based on the available evidence, not a guarantee of causation.
Findings become recommendations with a suggested action, owner, and priority for your team to review.
A recommendation can become an experiment or a tracked change so the effect is measured rather than assumed.
The measured outcome is linked back to the Signal and recommendation that prompted it, closing the loop.
See which behavioral changes deserve attention and what to build or test next, with evidence attached.
Understand activation, conversion, and attribution together, and connect each recommendation to a measurable test.
Extend existing analytics with an intelligence layer that surfaces and explains changes instead of requiring manual investigation.
Get a plain-language view of what changed, what is being tested, and what happened — without reading every dashboard.
Examples of the kind of value Lytik surfaces — not an exhaustive list, and not a fixed taxonomy.
Which changes in product behavior deserve attention?
Where are users leaving an important journey?
Which features are associated with stronger activation or retention?
What should the team investigate or test next?
Did a product change produce the intended result?
Which findings require review now?
Behavioral analytics provide the context for the intelligence loop — supporting the work rather than competing with it.
Active users, sessions, events, and trends.
Where users convert and where they drop off.
Cohort retention over time.
What gets used, by whom, how often.
The real paths users take.
Revenue and conversions tied to channels.
Targets with on-track status.
Notified when metrics move.
How your metrics compare to peers.
Test changes and measure significance.
A written summary of what changed and what to do.
Ask questions about your data in plain language.
Lytik is configured around your product, your data, and your priority questions — not a self-service signup.
Review of the product, data sources, and priority questions
Connection or configuration of relevant behavioral data
Definition of meaningful goals, journeys, features, and segments
Configuration of the Lytik workspace
Review of initial Signals and findings
Team orientation and ongoing refinement
Request a demonstration using a representative product scenario, or tell us about the questions your team is trying to answer.