Use attribution, incrementality, and scenario evidence to understand channel contribution while paid-media teams retain live execution.

Some of the 500+ brands we've worked with

See all references
  • Hyundai
  • DenizBank
  • Watsons
  • Exquise
  • Adore Mobilya
  • Ajansspor
  • Cyberpark

Measure channel contribution, incrementality, uncertainty, and future scenarios without taking ownership of live media execution.

Analytics owns models and evidence. Paid-media teams own campaign and budget execution.

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.

An evidence-based marketing measurement workflow from channel mapping to budget optimization.
  1. Map acquisition channels

    We audit campaign naming conventions, UTM parameter consistency, ad platform conversion pixels, and cost-data integrations.
  2. Build attribution models

    We evaluate rule-based and data-driven attribution models against actual customer touchpoints to expose channel bias.
  3. Design incrementality tests

    We structure geo-lift or holdout experiments to measure the true incremental revenue generated by paid campaigns.
  4. Deliver scenario planning

    We build interactive budget allocation tools that simulate expected returns under varying ad spend scenarios.

A client describing the planning and reporting problems we started from.

Dr. Kadir Kırmızı
Turna

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.

Dr. Kadir Kırmızı - General Manager

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.
Share your data stack and tracking challenges. We will design a clean collection architecture and actionable reporting infrastructure.
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