Web Analytics Consultancy
Marketing Measurement & Attribution

Some of the 500+ brands we've worked with
See all referencesApproved task contracts
Choose the measurement question before the model
Decision systems


Marketing Attribution Modeling
Credit is the question here, not cause. Last-click keeps handing brand search the conversion while one reallocation decision waits on a defensible split.


Incrementality & Lift Measurement
A split of credit is no longer enough, and you can hold a channel or a set of regions dark long enough to see whether those conversions happen anyway.


Marketing Forecasting & Scenario Planning
The decision points forward — a hire, a budget, stock to order — so the output is a range with named drivers and a backtest, not a credit split.
When this owner applies
Separate channel contribution from media execution
Measure channel contribution, incrementality, uncertainty, and future scenarios without taking ownership of live media execution.
Capability boundary
Models inform the decision, media teams act on it
Analytics owns models and evidence. Paid-media teams own campaign and budget execution.
Evidence-led delivery
Agree the evidence before building the model
Every engagement has named inputs, owners, human approval gates, reproducible QA, explicit limitations, and an operating handover.
We measure channel contribution, incrementality, and campaign ROI with transparent mathematical models. Zeo specialists configure attribution frameworks, incrementality tests, and media scenario planning, while your marketing leadership retains control of live ad budgets.


From measurement question to an owned decision
Map acquisition channels
We audit campaign naming conventions, UTM parameter consistency, ad platform conversion pixels, and cost-data integrations.
Build attribution models
We evaluate rule-based and data-driven attribution models against actual customer touchpoints to expose channel bias.
Design incrementality tests
We structure geo-lift or holdout experiments to measure the true incremental revenue generated by paid campaigns.
Deliver scenario planning
We build interactive budget allocation tools that simulate expected returns under varying ad spend scenarios.
From our clients
What clients say about measurement work
A client describing the planning and reporting problems we started from.
Channel results
Case Studies
Paid and organic programmes measured on the same commercial outcomes.
People who build your measurement system
Zeo designs measurement systems that connect a business decision to governed collection and reporting you can check. The people shown here work on the part of that system this page covers.

Yiğit Konur
Founder & Chief Strategy Officer

Ezgi Gülsen Yaylı
SEO Manager

Abdullah Tanıdır
Performance Marketing Team Lead

Sevda Yurtvermez
Performance Marketing Team Lead

Serap Yurtvermez
Performance Marketing Team Lead

İlker Emir
Senior Performance Marketing Executive

İpek Ezer
Performance Marketing Executive

Onur Durdağı
Performance Marketing Executive

Deniz Çağın Demirci
Frontend Developer

Mirzamin Aghazada
UI/UX Designer

Yağmur Bayram
Sr. SEO Analyst
Tools we use
The measurement stack behind the work
Collection, tagging, product analytics and reporting are separate problems with separate tools. These are the ones we build measurement on.
Core web analytics platforms
- Google AnalyticsEvery attribution or incrementality model we build gets compared back to GA4's own last-click numbers as the baseline, since a client needs to see what a proposed model changes relative to what they already trust. GA4 stays the reference point across attribution, incrementality, and forecasting work, not the deliverable itself.
- SimilarwebFor scenario planning that has to account for competitive pressure, not just a client's own trend line, we check Similarweb for a named competitor's estimated channel mix shifts. That external signal is what keeps a forecast from assuming the competitive landscape stays flat when it visibly is not.
BI, dashboards & reporting
- Looker StudioA forecasting or attribution deliverable does not end at handover; we keep the range and named scenarios visible in Looker Studio afterward, watched for the specific signals that mean the model has drifted and needs a rebuild. That ongoing watch is what keeps a scenario plan from quietly going stale a quarter after it was delivered.
- SupermetricsWhen a client's ad platform mix includes a source Windsor.ai does not connect to, we pull that feed through Supermetrics instead, blending it into the same input layer for the attribution model. Both tools do the same connector job here; which one handles a given platform depends on coverage.
- Power BIFor a client whose finance or marketing-ops team already builds forecasts and reports in Power BI, we deliver the scenario plan there instead of migrating them to Looker Studio, since a forecast that lands in a format the finance team already trusts gets adopted faster than one in an unfamiliar tool.
Product & mobile app analytics
- AppsFlyerWhen a client's acquisition channels include app installs, we pull mobile attribution data through AppsFlyer and merge it into the same channel-contribution model as the web-side GA4 data. That merge is what keeps a mobile-heavy client's attribution model from silently undercounting the app as an acquisition channel.
- AdjustFor a client whose app already integrates Adjust rather than AppsFlyer, we pull mobile attribution data from there instead, folding it into the same cross-channel model. Which mobile measurement partner we use follows the client's existing SDK, not a fixed default in this practice.
- BranchWhen the acquisition question is specifically about a user moving from a web ad or link into the app, a deferred deep link completing a signup, we bring in Branch, since deep-link attribution across that handoff is its specific focus. That narrower scenario is what distinguishes Branch's role here from AppsFlyer or Adjust's broader mobile attribution.
Attribution & e-commerce analytics
- Triple WhaleFor an ecommerce client whose acquisition spans several ad platforms, we build the blended-ROAS attribution view in Triple Whale, since it is purpose-built to unify ad spend and revenue across platforms in a way GA4 alone does not. That ecommerce-specific framing is why it enters this practice for retail and DTC clients specifically.
- NorthbeamWe build the multi-touch attribution model directly in Northbeam, weighing it against last-click and simpler rule-based approaches before recommending a change. It is the modeling layer specifically, distinct from Triple Whale's more report-and-dashboard-oriented ecommerce attribution view.
- Ruler AnalyticsFor a client whose actual sale closes over the phone rather than on the site, we route attribution through Ruler Analytics, since it ties a tracked call back to the marketing touchpoint that generated it. That offline-conversion bridge is what keeps a phone-heavy business's attribution model from crediting only the visible online form fills.
- Windsor.aiWe pull ad spend and platform-reported conversions through Windsor.ai as the connector layer beneath the actual attribution modeling, since Northbeam or Triple Whale still need consistent input data from every platform a client advertises on. That connector role sits upstream of the modeling itself.
Next step
Turn measurement into reliable business decisions


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