A test earns its place when the question, measurement and decision are clear before anyone sees a variant. We investigate where people get stuck, run the experiment and read the result with Analytics.

Some of the 500+ brands we've worked with

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  • Mini
  • Marks & Spencer
  • Madame Coco
  • Aksigorta
  • Neova Sigorta
  • Bundle
  • Jollytur
We agree on the evidence, validity checks and decision owners before implementation starts.

Conversion & experimentation

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Campaign Landing-pageExperimentation

The campaign promise and journey evidence shape the landing-page experiment. We write the decision rule before exposure begins.

Live campaign traffic changes the test. The ad's promise, eligibility and tone stay intact on the page while one change is measured against the approved conversion.

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FrictionResearch

We read behavior data, qualitative feedback, technical constraints and campaign context together. No single tool gets treated as proof.

No heatmap or handful of recordings settles a cause on its own. Every input is logged with its source and confidence before a hypothesis may be written.

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ExperimentQuality Control

The experiment contract records the primary metric, guardrails, exposure plan, QA status, stopping logic, exclusions and analyst review.

A verdict holds only when guardrails, stopping logic and the analyst review were agreed before exposure.

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Conversion ResearchAudit

Before we write a hypothesis, we bring analytics, session data and qualitative research into one map of journey friction and opportunity.

Competing theories about one page are the signal for this one. Analytics, recordings, accessibility and technical checks come back as a register ranked by evidence strength.

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Experiment HypothesisRoadmap

We order experiment hypotheses by the evidence behind them, the proposed mechanism, expected impact, risk and dependencies.

More hypotheses than run windows is the condition here. Impact, evidence strength and effort get scored on one rubric, and conflicting tests move into separate windows.

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A/B TestDesign & Analysis

We define the A/B test before build, check it before launch and report the result against the original decision rule.

Take this one while the statistics are still open, because minimum detectable effect, sample size, randomization unit and stopping rule get settled before the build.

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Form & CheckoutOptimization

Forms and checkout expose friction field by field. We use the biggest drop-off points to decide what belongs in the experiment plan.

A step-level drop with no field behind it points here. Focus, error and abandonment events per field separate a confusing input from one that simply loads slowly.

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Funnel Friction & JourneyDiagnostics

We map behavior and qualitative evidence across the funnel to see where people leave and where the problem may have started.

Use this one where the journey crosses several pages and the visible exit may not be the cause, since backtracking and re-entry have to stay in the evidence.

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ExperimentImplementation & QA

Before launch, we record how the variant behaves across devices, who receives it, whether tracking works and what the performance and visual checks found.

Once tests run often enough that checks by feel become the risk, the release gate moves here, covering the device matrix, assignment logs, accessibility and a rehearsed rollback.

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Experiment LearningRepository

Past tests stay searchable with their evidence, decision and contradictions attached. That history helps us sharpen new hypotheses and avoid running the same unsupported idea twice.

Past tests stop being useful once nobody can find them. Here they are rebuilt into one record format, tagged by mechanism and audience, with contradictions flagged for review.

Where this work is owned

Reliable Analytics comes first because experiments need trustworthy measurement. CRO covers the research, hypothesis, QA, analysis and implementation decision for the experience in scope. Even a well-run test can end with a null, negative or invalid result.

We keep observations separate from assumptions, agree on the decision in advance and use QA and guardrails to protect users and measurement. Null and negative results stay in the record because the next decision may depend on them.

A test earns its place when the question, the measurement, and the decision owner are settled in advance.

We trace the journey through user evidence, event definitions, and traffic shape, record the technical limits and consent requirements, then write an experiment contract naming the mechanism, primary metric, guardrails, eligible population, variants, expected decision, and the reasons a result may be invalid. Zeo runs research, design, QA, analysis, and the implementation recommendation; the business decision and the release stay with your owner, and reliable Analytics is a dependency we do not also own. Null, negative, and invalid results stay in the record, because the next decision often depends on them more than a win would.

Each question stays attached to its validity checks, result and decision owner.
  1. The journey and its measurement baseline

    We trace the journey through user evidence, event definitions and traffic shape. Before a hypothesis moves forward, we record the technical limits, consent requirements and who owns the business decision.
  2. Write the experiment contract

    The mechanism and primary metric define the claim under test. The same contract carries guardrails, eligible population, variants, expected decision and the reasons a result may be invalid.
  3. QA before wider exposure

    Copy, layout and accessibility go through review alongside analytics, audience assignment, performance and rollback. Exposure increases only after those checks.
  4. Decide with uncertainty visible

    Sample-ratio checks, segments, guardrails and practical effect sit beside the main result. Together they support a ship, iterate, stop or gather-more-evidence decision.

These clients describe the planning, measurement, and communication they experienced while working with Zeo.

Serkan Haşlak
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International success stories and the segmentation and diversity of Zeo Agency's clients were the main reasons we chose to work with them in the first place. At our very first meeting, we were convinced by their expertise. They think like us, they work like us, and they behave like us. What sets them apart from other service providers is discipline and communication. After working with them, we saw a significant increase across Foriba's digital channels. Thanks to them, we gained quality traffic and potential customers, which gave us more meetings with good leads and directly affected sales.

Serkan Haşlak - Marketing Director

Dr. Kadir Kırmızı
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Before working with Zeo, we had serious problems, especially with planning and measurement. Because we couldn't get complete measurements and reports, we struggled to evaluate our work. Evaluating the data correctly, in line with scientific rules, was the most important thing for us. At Zeo, there is a culture of measurement and evaluation above all else. We are impressed that their approach is entirely data-driven. We are glad that they take ownership of their work, give constant feedback, and stay in a continuous improvement cycle. Together, we have found ways to win more customers while spending less.

Dr. Kadir Kırmızı - General Manager

Serhan Demirel
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Before we started working with Zeo, we believed we couldn't get a return on our investment in Google Ads or run performance optimization properly. Once we were confident that campaign performance management was in expert hands, we could devote all of our time to development and integration. Our old campaigns gave way to campaigns that are built faster, localized without any burden on us thanks to Zeo's business partners, constantly optimized, and trackable in real time via dashboards, with conversion tracking that comes through in practical, detailed, and easy-to-read reports. We see Zeo as part of our team, no matter the location.

Serhan Demirel - International Digital Marketing Manager

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.

Campaign structure, bidding, feeds, call tracking and reporting each live in their own tool. These are the ones our team runs accounts in.

Advertising platforms we buy on

  • Google Ads
  • Microsoft Advertising
  • Meta Ads
  • TikTok Ads
  • LinkedIn Ads
  • Amazon Ads
  • Pinterest Ads
  • Snapchat Ads
  • X Ads
  • Reddit Ads

Ad creative and landing pages

  • UnbounceWhen an experiment needs a standalone landing page rather than a variant of an existing CMS page, we build it in Unbounce, whose Smart Traffic feature can route visitors to whichever built variant is converting best for them. This is a page-creation tool, feeding the testing platforms above rather than running the statistical test itself.
  • InstapageFor an experiment that has to prove which ad creative drove which landing-page variant, Instapage's AdMap gives that visual ad-to-page pairing directly, which Unbounce's builder doesn't carry as a named feature. It is the second landing-page-creation option on this page, picked for that specific traceability need.
  • HubSpotWhere the client's own marketing stack is already HubSpot, building the test page there keeps the conversion event and the resulting lead record in one system rather than piping a third-party landing-page tool's data into a separate CRM. It's a third landing-page-and-CRM option on this page, chosen specifically for HubSpot-native clients.
  • ClickFunnelsWhen the hypothesis under test is a multi-step sequence, an offer page into an upsell into a checkout, rather than a single page, ClickFunnels is built specifically around that funnel structure. This is a fourth page-building option, distinct from the single-landing-page tools above by scope: a whole sequence, not one page.
  • LeadpagesWhen a test needs a page live quickly, Leadpages' AI builder generates a working variant from a plain description in roughly a minute, with A/B testing and heatmaps already built in rather than bolted on. It's the speed-optimized option among this page's landing-page tools, not the default choice when there's time to build in Unbounce or Instapage instead.
  • LandingiFor a test that spans many page variants sharing a common section, Landingi's Smart Sections update that shared block once and sync it everywhere, rather than requiring a page-by-page edit across every variant. This is the option on this page built specifically for a many-variant test, not a two-arm A/B split.

CRO and experimentation

  • ContentsquareWhere people get stuck, this page's own hero question, gets diagnosed first in Hotjar (now part of Contentsquare): heatmaps and session replay show the click and scroll pattern, and rage-click flags point straight at the friction moment. This is the diagnostic layer that feeds the experiment contract, run before any variant gets built rather than after.
  • OptimizelyWhen a hypothesis reaches into CMS-managed content or layout rather than a single page element, we build and run that test in Optimizely, whose platform pairs experimentation directly with its own content system. This is one of two execution platforms this page's tool set carries; the choice between it and VWO comes down to whether the client's content already lives in Optimizely's CMS.
  • VWOFor a standard web A/B or multivariate test, VWO runs it on a sequential-testing model, so a mid-test check is not the same thing as a stopping decision. Its Plan module is also where hypotheses get scored and where finished-test insights get filed, which is what keeps a program running past a single experiment's results.
  • AB TastyWhen a hypothesis restructures a whole flow rather than swapping one headline, that variant gets built in AB Tasty's Visual Editor, a no-code, low-code tool the vendor documents as covering multi-page tests alongside the standard single-page A/B and multivariate kind. This is the third execution platform on this page, chosen over VWO or Optimizely specifically when the redesign spans more than one page.
  • Crazy EggAlongside Hotjar's diagnostic layer, Crazy Egg's Confetti Maps segment click evidence by traffic source, which is what catches a pattern that only shows up for one channel's visitors rather than pooling everyone into a single map. It runs as a second, differently-segmented read on the same friction question Hotjar answers first.
  • ConvertFor a client where even a brief flicker during variant load would undermine trust in the test, Convert's SmartInsert technology is built specifically to avoid that flash. It is a fourth execution-platform option on this page, distinct from VWO, Optimizely, and AB Tasty by that one delivery-quality difference rather than by feature breadth.

Measurement and attribution

  • Google AnalyticsWriting the experiment contract means picking a randomization unit, and that choice only holds if it matches how the account's GA4 property already scopes its data; user-scoped and event-scoped dimensions are genuinely different constructs there, not interchangeable labels, and getting that wrong is a silent error a dashboard won't flag on its own. This check runs before any of the four testing platforms above ever executes a variant.
  • Google Tag ManagerA test can look statistically clean and still be measuring nothing real if a tag silently didn't fire, so QA before wider exposure, this page's own third process step, runs the built variant through GTM's preview and debug tooling first. Catching that gap here, before traffic scales, is cheaper than discovering it after the result is already unreliable.
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