Domain

Marketing Analytics: Making Marketing Performance Visible

Google Ads is portrayed as the most successful marketing channel, but when the invoice arrives, it remains unclear whether that invested budget was proportionate. The standard attribution model gives all credit to the last click. Reality looks different: approximately twenty different touchpoints participate in the conversion process. Probabilistic attribution models, carefully designed channel mix models, and scenario-driven analysis offer the data-driven quality that budget decisions deserve.

From the last click to the full picture.

Methods
01

Attribution Modeling

Your display banner created initial brand awareness. The email link provided the concrete call to action. Google Ads drove the final interaction. How do success factors distribute across these different elements? Multi-touch attribution answers this question in a data-driven and scientifically sound way. Instead of rigid models that either proceed linearly or attribute everything to the last source, we determine what specific contribution each touchpoint made to conversion success.

Multi-TouchData-Driven AttributionTouchpoint AnalysisMedia Mix
02

Campaign ROI & Performance

Generating leads is comparatively inexpensive. Converting those leads into paying customers comes with significantly higher costs. A campaign generating 1000 leads with 2% conversion is no closer to success than one with 100 leads and 50% conversion. We close this analytical gap by tracking individual leads through the entire conversion cycle. This reveals which lead actually became a customer and from which sources truly sales-ready prospects emerge.

Campaign TrackingROI MeasurementConversion AnalysisFunnel Optimization
03

Marketing Mix Modeling

Your current budget distribution consists of 40 percent for TV, 20 percent for Google, and 40 percent for direct mail. Marketing Mix Modeling answers the critical question of whether this distribution maximizes the output gained. The method empirically quantifies how an additional 10 percent investment in one channel affects overall performance. We consider relevant external influencing factors such as seasonal fluctuations, weather conditions, and competitor activities. The resulting scenarios show not what you should do, but specifically what effects emerge from particular measures.

MMMBudget OptimizationScenario PlanningChannel Comparison

Attribution models compared

Who gets the credit?

The same customer journey, two perspectives: last click assigns all credit to the final contact; multi-touch makes the contribution of every touchpoint visible.

Credit per touchpoint
  1. Display bannerBrand awareness
  2. Email linkCall to action
  3. Google AdsFinal interaction

Last click: Google Ads receives all of the credit; the display banner and the email link receive none.Multi-touch: the credit is shared between the display banner, the email link and Google Ads.

Attributed creditIllustrative

Why Barling for Marketing Analytics

Differentiation
01

Attribution Requires Sophistication

Standard attribution models have systematic shortcomings. First-click attribution overlooks the important nurturing and relationship building in later phases. Last-click attribution distorts reality through overvaluing the final impulse. Linear distribution often works correctly only by chance. We therefore rely on algorithms that empirically learn customer paths rather than guessing them.

02

Revenue, Not Interactions

Your marketing machine continuously generates leads. These leads are often inadequately handled by sales, so much of the volume goes stale or is lost. Typical attribution models stop at the lead and do not capture which interactions actually result in paying customers. This measurement gap is significant. We track the entire customer journey through contract closure and beyond. This allows us to quantify which campaigns actually complete customer acquisition successfully.

03

Scale While Maintaining Consistency

The UK business unit reports an ROI of four to one. Germany states the ratio as six to one. Are these figures comparable? They cannot be if different attribution methods, various channel definitions, and divergent measurement standards underlie them. We therefore build a structure of central governance with decentralized operational autonomy. Each regional brand runs its campaigns according to local requirements, but all use the same standardized reporting framework.

Contact

You still don't know where your marketing budget really goes. We can change that.