Campaign Landing-Page Experimentation

Evidence should determine a landing page's next version.

We trace where visitors get stuck, write a hypothesis that can be disproved and check the build before anyone sees it. Once the experiment is live, we watch the guardrails alongside the primary metric. Wins, nulls, negative results and invalid runs all stay in the record because each one changes what the team should do next. Your campaign is already sending live traffic to a page, and the next change needs a reviewable basis before it ships.

You get a reviewable landing-page decision backed by the evidence, guardrails, and recorded verdict.

A CRO specialist at a split-path testing bench comparing two landing-page variants

Some of the 500+ brands we've worked with

See all references
  • Pegasus Airlines
  • Tazedirekt
  • Silverline
  • Albaraka Türk
  • AVVA
  • Ajansspor

How the work runs

Six checks between the idea and the decision

Each step leaves a record the next person can inspect. AI may cluster approved evidence, compare the paused build with its checklist and draft a first summary. It doesn't invent a cause, choose the winner or touch a live account. Named people approve the hypothesis, exposure and release.

How we hold ourselves to it

  • Separate what you observed from what you assume it means
  • Write the decision down before exposure begins
  • Protect visitors, measurement, and page performance with guardrails
  • Keep null, negative, and invalid results as real learning

  1. Diagnose the friction before proposing a variant

    Read analytics, qualitative evidence, campaign context, accessibility, performance, and technical behavior together. Each heatmap, recording, interview, or metric is one input, logged with its source and confidence, and no single one stands as proof of cause.

    Evidence register listing each analytics, qualitative, accessibility and technical input with its own source.

    AI assist
    Clusters the approved observations into a register and flags contradictions or missing evidence.
    Human gate
    The CRO strategist and research owner approve the register before a hypothesis gets written.
    Owners
    CRO strategist + research owner

  2. Anchor the test to one approved business event

    Name the primary conversion, such as a purchase, qualified lead, booked action, or approved proxy, along with its value, delay tolerance, and the person who owns that definition. A diagnostic click does not stand in for it.

    Named primary conversion with its value, delay tolerance and the person who owns the definition.

    AI assist
    Structures the supplied guardrail notes into a single brief and flags missing fields.
    Human gate
    The CRO strategist and client owner sign off on the decision-value brief.
    Owners
    CRO strategist + client owner

  3. Write a hypothesis that can be proven wrong

    State it plainly: if we change X for eligible users, Y should move because Z. Declare the primary metric, guardrails, expected direction, practical threshold, and the condition that would invalidate it, while keeping the campaign's audience, message, and eligibility intact.

    Falsifiable hypothesis with its primary metric, guardrails, expected direction, practical threshold and invalidation condition.

    AI assist
    Drafts hypothesis candidates from the approved evidence register, each one linked back to its source.
    Human gate
    The CRO strategist and research owner approve the registered hypothesis before design starts.
    Owners
    CRO strategist + research owner

  4. Build it paused, then check it twice

    Configure the control and variant without publishing them. Compare the paused build against the approved experiment contract, staging QA exports, and the release checklist: copy, layout, accessibility, responsive behavior, performance, events, assignment, and consent included.

    Signed preflight pack: the paused build checked against the experiment contract, the QA exports and the release checklist.

    AI assist
    Compares the paused build with the approved contract and QA exports, and flags every discrepancy.
    Human gate
    An independent human reviewer signs the preflight checklist before the experiment owner authorizes exposure.
    Owners
    QA reviewer + experiment owner

  5. Go live, watched

    Activate only the approved scope. Confirm that delivery and measurement are working, then monitor guardrails such as sample-ratio mismatch, event loss, material regression, consent defects, and harmful experiences as closely as the primary metric.

    Live monitoring log covering sample-ratio mismatch, event loss, material regression and consent defects from the first hour.

    AI assist
    Watches the approved guardrail metrics and flags a possible stop-condition breach for review.
    Human gate
    The experiment owner reviews any flagged breach and decides whether to pause exposure.
    Owners
    Experiment owner + analytics owner

  6. Read the result, then record the decision

    Reconcile assignment, analytics, and business-outcome counts before trusting the verdict. Ship, iterate, stop, gather more evidence, or call it invalid, and keep the evidence, the uncertainty, and the next review date attached to whichever one it is.

    Reconciled readout and a decision-log entry naming the verdict, its evidence, its uncertainty and the next review date.

    AI assist
    Drafts an observation-first decision brief from the approved data, labeling each recommendation observed, attributed, modeled, or unknown.
    Human gate
    The CRO strategist and research owner approve the decision. The client owns the final production call.
    Owners
    CRO strategist + client owner

What lands with your team

What needs to survive after the dashboard closes

A screenshot won't explain the test months later. These four records show what was tested, how the build was checked, what the systems reported and why the team made its decision.

  • Research and hypothesis record

    The evidence register, the falsifiable hypothesis, the guardrails, and the invalidation conditions in one versioned, owned document.

    Accepted when

    The register, the hypothesis, the guardrails and the invalidation conditions are versioned and owned before any variant is designed.

    Cadence: Before design starts

  • Preflight and rollback pack

    Signed functional, analytics, accessibility, and performance QA, the release checklist, and the exact steps to contain a change if a guardrail trips.

    Accepted when

    Functional, analytics, accessibility and performance QA are signed and the containment steps are written before exposure starts.

    Cadence: Before every experiment

  • Reconciliation note

    Assignment, analytics, and business-outcome counts compared side by side, with any material difference investigated before the verdict is trusted.

    Accepted when

    Assignment, analytics and business-outcome counts are compared side by side, and any material difference is investigated before the verdict is trusted.

    Cadence: Before every decision

  • Decision log

    The ship, iterate, stop, gather-evidence, or invalid verdict, including its evidence, uncertainty, owner, next review date, and any null or negative results.

    Accepted when

    Every experiment closes with a named verdict, its evidence, its uncertainty, an owner and a review date, including null and negative results.

    Cadence: At analysis point

Before the work starts

When this work is the right next step

A landing page may look finished without evidence that it should change. A heatmap, a handful of session recordings, or one metric is a useful clue about what may be wrong. Meanwhile, the campaign that sent the visitor made a promise, and the page has to keep it: same offer, same eligibility, same tone, all the way to the form. Skip either check, and a page redesign turns into an argument nobody can settle.

A good fit when

  • Your live campaign sends enough traffic to the page, so the planned sample can close within a window that still supports the pending decision.
  • The page's primary conversion is defined and trusted, but nobody has yet tested whether the next change moves that approved business event.
  • Design, engineering, analytics, and final approval are in place, so a winning page variant can move from readout to release.
  • One heatmap or a handful of recordings gets treated as proof of what's wrong across the whole page.
  • A click or a form start gets called a win before anyone checks whether it became the outcome the business actually approved.
  • The page's copy quietly stops matching the ad or email that sent the visitor there.
  • The brief says "make it better," with no metric, no threshold, and no way to be proven wrong.

Better handled as other work when

  • Campaign traffic is too thin to reach a reliable read before the flight ends, so research, instrumentation repair, or a controlled release fits better.
  • The primary conversion event is undefined or distrusted, so analytics and business-outcome counts cannot support the verdict required for a live page change.
  • No one can approve or implement a live page change on the required timeline, so the experiment would end with evidence that cannot be shipped.

People who own a single channel

Paid Search, Paid Social, CRO, and Programmatic each run under a named owner at Zeo. The consultants below are matched to the channel this page is about, so you can see who you'd actually work with.

Content we've produced on this topic

Videoby İlker EmirWays to Increase Conversion Rate | Ilker Emir, ZeoArticleby Zafer YıldızConversion Structure & Conversion Creation in Google Analytics 4

Tools we use

Tools behind this work

  • Contentsquare

    filters straight to the frustrated moments, which is where the friction diagnosis starts

  • AB Tasty

    builds the whole redesigned page as a variant, not just one swapped element

Start with the decision that's holding up the page

Scope one landing-page experiment

The live page and its campaign promise give us the starting point. We'll review the evidence and measurement, then define the smallest experiment that could answer the decision you're stuck on.
Review the experiment plan

The questions we hear most

No. The method follows from traffic, risk, technical limits, and decision cost. A low-volume page may be better served by research, instrumentation repair, usability evidence, or a controlled iterative release with explicit limits.