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    Test Ideas

    Your queue of upcoming tests, built automatically from your ads, traffic, and pages. Each one arrives ready to launch. You approve, it runs.

    Overview

    Tailor reads your ad spend (Google, Meta, LinkedIn), your traffic, and your landing pages, and keeps a ranked queue of upcoming tests to lift conversion and ROAS. Each test in the queue is fully built: the audience it targets, its expected 30-day reach, the key page changes, and a before/after preview from your live site. Launching is an approval, not a project.

    The queue is standing: new runs add to it rather than replacing it, dismissed tests stay dismissed (and can be restored in one click), and every test you run teaches the next round. Left alone, the queue keeps reflecting where your spend and traffic actually are.

    Tailor AI automatically generating ranked landing page test ideas for a PDF editor product

    Anonymized examples of upcoming-test queues across three industries.

    Ranked by expected impact

    The queue is ordered by expected monthly impact (traffic to the targeted segment times the targeted lift), not by confidence alone. A modest win on a high-traffic page usually beats a big win on a page nobody visits.

    Filling the Queue

    1

    Open Test Ideas

    Find it in the left sidebar at app.tailorhq.ai.

    2

    Pick your inputs

    Choose which ad platforms, data signals, and pages Tailor should consider, and whether you want the best tests across your pages or a page for every paid keyword. A Fine-tune section gives you finer data controls when you want them.

    3

    Set your standing brief (once)

    Tell Tailor who you are and what you optimize for. The brief steers every future run, and you can add a one-off focus line to any single run.

    4

    Let it build

    Runs take a few minutes. You can switch tabs; your browser notifies you when your new tests are ready (enable notifications when prompted, or under Settings → Notifications).

    Larger queues arrive organized into launch waves: a first phase of tests you can run in parallel now, with later waves sequenced behind them. Toggle between the phased view and one flat ranked list.

    Keyword Coverage

    Choosing "a page for every paid keyword" runs a keyword coverage sweep: Tailor maps each paid-search keyword to the landing page it actually hits, flags weak message match, and turns the gaps into ready-to-launch test ideas with the copy changes drafted. A sweep covers hundreds of keywords per run.

    Keyword targeting needs the keyword in the URL

    Serving a tailored experience per keyword relies on your URLs carrying the keyword (usually utm_term). If your tracking templates don't pass it, fix that first. See the Targeting Guide.

    Reading an Upcoming Test

    The queue reads as a ranked table: value proposition, audience, estimated 30-day reach, and the key page changes. Click any row to open the full detail: targeting, before/after preview screenshots from your live site, and the launch, preview, refine, and dismiss actions.

    • 1Numbers checked badges mean the traffic and reach figures were verified against your real data.
    • 2Runtime estimates come from the targeted segment's actual traffic, so a niche audience shows an honest (longer) time to a result.
    • 3Targeting is editable: adjust the UTM or custom parameters a test targets and the audience size re-measures automatically.

    Refine & Edit

    Refine one test

    Tell Tailor what's off ("less formal", "lead with the integration") and it rewrites that test from your feedback.

    Refine all

    One instruction re-voices every headline, subhead, and CTA across the queue. Useful for brand-voice passes.

    You can also edit proposed copy inline before launching, rewrite a single change with AI, remove a change from the test, or jump into the extension to edit the page directly.

    Launch & Learn

    Approving an upcoming test launches a real experiment on your existing URL with the targeting attached. Nothing goes live without your approval, but approval is the only step left. Results feed the next round: runs read the outcomes of your live and rolled-out tests, iterate on champions, and stop queueing what you've dismissed.

    From there, the normal experiment workflow applies: ramp, read results, and promote winners. See the Experiments Workflow guide.

    Best Practices

    • 1Connect your ad accounts first so proposals reflect real spend, not guesses.
    • 2Write the standing brief before your first run. Two sentences about your audience and goal noticeably improve the ideas.
    • 3Dismiss freely. Dismissals teach future runs what not to queue, and you can restore anything in one click.
    • 4Launch the top wave in parallel rather than one test at a time. The waves are sequenced so they don't conflict.