Find the leading indicator.
Sendlyr reads your product data to identify the early behavior, window, and coverage that matter.
How it works
Your product data enters Sendlyr. We find a leading indicator, your lifecycle stack guides users toward it, and measured outcomes return so the indicator sharpens.
The system
Sendlyr reads your product data to identify the early behavior, window, and coverage that matter.
Your lifecycle stack drives users toward the indicator, with testing to confirm what changed.
Measured outcomes return to refine the behavior, timing, and coverage.
Five working steps
Each step keeps the behavior, lifecycle guidance, and measured outcome connected.
Connect the events, eligible cohort, and outcome from the systems you already use.
Identify the early behavior, time window, and coverage most useful for lifecycle guidance.
Turn the indicator into a clear direction for your existing lifecycle stack.
Bring the behavior and business result back into Sendlyr with the uncertainty visible.
Use the new evidence to sharpen the behavior, window, and coverage.
Evidence guardrails
Shows an association. It does not prove the behavior caused the outcome.
Identifies an early behavior connected to the defined outcome. It guides the lifecycle stack; it is not the outcome itself.
Shows what changed after the lifecycle guidance, with the uncertainty stated. See the corrected Typesy case study, where the behavior moved and conversion did not.
Earns a go, stop, or iterate conclusion only from the complete readout.
What leaves the room
Behavior, event quality, coverage, timing, and relationship to the outcome.
The behavior your existing lifecycle stack should guide users toward.
What changed, the stated uncertainty, and how the evidence improves the indicator.
Bring your product data
We will assess data, cohort, lifecycle-stack, and outcome fit before the Pilot begins.
Request a Signal Validation Pilot