Features for AI-assisted experimentation operations

    ConversionLab gives teams the operating layer around A/B tools: research, ideas, prioritization, execution context, results, and an Agent that can work across the history.

    Core capabilities

    Everything needed to run a compounding experimentation program

    From insight capture to post-test learning, every stage is connected and auditable.

    Research and survey intake

    Capture insights, run survey workflows, label evidence, and keep the source context attached before ideas are created.

    Ideas and priority models

    Turn evidence into testable ideas and score them with configurable models so backlog debates use shared criteria.

    Experiment execution context

    Manage hypotheses, variations, lifecycle states, audiences, pages, metrics, ownership, comments, and approvals.

    ConversionLab Agent and daily briefing

    Review the daily brief, spot the next actions, and ask the Agent questions across team context while respecting AI Availability controls.

    Source Import and integrations

    Bring Airtable histories into ConversionLab and connect A/B testing vendors without making them own your memory.

    Results, analytics, and governance

    Review variant outcomes, execution signals, notifications, activity history, definitions, and team access in one place.

    Use cases

    How teams apply ConversionLab in day-to-day work

    These are the common adoption paths for CRO, growth, and product experimentation leaders.

    Ask better questions of your experimentation history

    Use the Agent and daily brief to find stalled experiments, repeated ideas, missing owners, and relevant prior learnings.

    See Agent workflows
    ConversionLab dashboard with the Agent prompt

    Migrate scattered historical work into one model

    Map existing Airtable records into insights, ideas, experiments, metrics, pages, and audiences before teams start planning new work.

    Discuss migration paths
    ConversionLab import screen with Airtable, CSV, and Google Sheets options

    Turn test execution into reusable learning

    Keep hypotheses, variants, SRM checks, outcomes, decisions, and post-test learning available after the execution tool changes.

    View plan options
    ConversionLab analytics dashboard with experimentation metrics and charts
    Next step

    Map your current experimentation process to the product

    We’ll show where your current stack creates context loss and how ConversionLab closes the loop from evidence to outcome.

    Book a tailored walkthrough