We show you which marketing drives revenue. Our team builds the tracking, attribution, creative testing and reporting behind your campaigns, finds where your funnel leaks, and audits what you already have. We work with your team to set the KPIs, so every call on budget, creative and targeting starts from the same numbers.
Yes. We audit the systems behind your reporting to understand how reliable the numbers are. That includes tracking setup, attribution logic, CRM integration, platform discrepancies, and data flow between tools. From there, your team gets a clearer view of which metrics can guide decisions and which areas need stronger validation.
The right attribution model depends on how customers discover, evaluate, and purchase your product. For example, an ecommerce brand may use data-driven attribution with stronger weight on conversion-driving touchpoints, while a B2B company may need multi-touch attribution to understand how campaigns contribute to pipeline over several months. We match the model to how revenue is actually generated.
The dashboard structure depends on how your business evaluates success. Some teams need visibility into revenue and pipeline performance, while others focus on customer acquisition, retention, or channel efficiency. We build reporting around these priorities so stakeholders can quickly understand performance, spot emerging trends, and prioritize the next actions.
Marketing attribution is the process of determining which marketing interactions contribute to a conversion or business outcome. It helps you understand how channels and touchpoints influence actions such as purchases, leads, or sign-ups.
Attribution focuses on assigning credit for a conversion across marketing touchpoints. Measurement is broader. It evaluates overall marketing performance through methods such as attribution, incrementality testing, media mix modeling, and business-level KPIs.
In simple terms, attribution asks what contributed to the conversion, while measurement asks what impact did the marketing actually have.
We review measurement frameworks on a weekly basis to ensure tracking, reporting, and attribution remain aligned with current campaign activity. When platform updates, customer behavior shifts, or business priorities change, we adjust the framework so teams continue working from accurate and relevant data.
Yes. Our team can bring together data from advertising platforms, analytics tools, CRM systems, ecommerce platforms, and other business sources into a unified view. This gives stakeholders a clearer understanding of how different channels contribute to growth and supports more confident investment decisions.
Unified marketing measurement combines multiple measurement methods to create a more complete view of marketing performance. It can bring together attribution, media mix modeling, incrementality testing, experiments, and business data.
Its primary purpose is to reduce reliance on any single model and give teams stronger evidence for budget and channel decisions.
AI can help enterprise teams analyze larger datasets, identify patterns, detect performance changes, and generate insights faster. It can also reduce the manual work involved in reporting and analysis.
However, these insights are only as useful as the data and measurement methods behind them. AI can strengthen analysis, but reliable data, clear KPIs, and sound measurement methods still determine the quality of the results.
The right attribution model depends on your customer journey, sales cycle, available data, and marketing mix. Last-click attribution may be useful for some decisions, while multi-touch or data-driven models can provide more context across longer journeys.
We recommend using attribution alongside incrementality testing and other measurement methods when possible, rather than asking one model to explain every marketing outcome.
