Google Display Ads – Attribution

Custom Attribution: Assign Fractional Conversions to Google Display Ads and Automate Workflows

Custom Attribution projects involve setting up technical infrastructure to aggregate data from various marketing sources, measure conversions, and apply a custom algorithm to calculate the true effect of Google Display Ads in cross-channel marketing activities. Digitl provides consulting, workshops, and technical automation to facilitate these projects.

Attribution & Conversion Accuracy in Google Display Ads Reporting

Custom Rule-Based Attribution Model

A custom rule-based attribution model provides a nuanced understanding of how different channels, including Google Display Ads, contribute to conversions. This model allows assigning credit to various touchpoints based on predefined rules that reflect the customer journey. It can incorporate click-based data from multiple channels, such as social media, email marketing, and organic search, along with Google Display Ads. By defining specific rules, such as assigning lower credit to brand keywords or weighting interactions based on their position in the funnel, businesses gain a more accurate picture of channel effectiveness. This granular view enables better budget allocation and optimization across all channels.

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De-Duplication of Conversions by Assigning Fractional Conversions

De-duplication of conversions for Google Display Ads ensures accurate attribution across marketing channels. When a conversion involves multiple touchpoints, fractional credit can be assigned to each channel rather than attributing it solely to the last click. This approach provides a more realistic view of how different channels contribute to the final conversion. By distributing conversion credit proportionally, businesses gain a clearer understanding of the customer journey and can optimize budget allocation across channels more effectively. This fractional attribution model prevents over-crediting any single channel and reveals the true impact of each touchpoint.

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Attribution Pattern Analysis

Attribution pattern analysis identifies recurring user journeys – such as sequences of clicks, views, or visits – that lead to conversions. By examining these behavioral paths, marketers can evaluate which combinations of channels and interactions most frequently contribute to success. These insights enable smarter credit allocation, informed budget shifts, and refined messaging across the funnel. Over time, recognizing such patterns improves the granularity and reliability of attribution models.

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Timely Attribution Updates

Timely attribution updates ensure that each customer interaction – whether it occurs seconds or hours before a conversion – is reflected in performance analysis. Integrating automated data refresh mechanisms helps capture the latest user behavior, updating conversion paths and credit assignments accordingly. This ensures responsiveness improving measurement precision, especially in dynamic environments with fast-changing customer journeys. It also supports faster feedback loops for media and budget optimization decisions.

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Additional Services by Digitl for Google Display Ads

Marketing Technology Services that support Google Display Ads teams with knowledge and resources about Tech and Data.

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Implementation

Setup and integration of Display advertising within marketing infrastructure, including the implementation of triggers and tags for performance tracking and advanced analysis.

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AI

Gemini, ChatGPT, and other AI models to increase efficiency of media buying and optimization of workflows by using AI Agents and GenAI modules.

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Dashboards & Reports

Automated aggregation of data for KPI reporting to analyze the effect and performance of Google Display Ads campaigns. Creation of appealing Dashboards that go beyond pure metrics.

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Data Integration

Integration of offline, CRM or user data. Use predictions or other KPIs in your marketing technology infrastructure to activate them with Google Display Ads campaigns.

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Process Automation

Orchestration of automated workflows in AWS, Azure, or Google Cloud for data activation, predictions, advanced analysis or reporting to drive efficiency of Google Display Ads campaigns.

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Advanced Analysis

Advanced analysis of Google Display Ads campaigns with audience demographics, content performance analysis, and cross-channel attribution modeling to understand its true impact.

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Marketing Mix Modeling

Marketing Mix Modeling (MMM) to analyze the impact of Google Display Ads campaigns on overall marketing performance or use statistics for incrementality testing to understand the added value on performance or branding KPIs.

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User Segmentation

First-party data based on demographics, interests, behavior, and engagement patterns to activate audiences or analyze the effect and performance of Google Display Ads campaigns.

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App Tracking

App tracking data – including installs, in-app events, and post-install conversions – for KPI reporting to analyze the effectiveness of Google Display Ads campaigns, driving app engagement and acquisition.

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Advanced Services

Custom technical solutions, data integration, scripts or workflow orchestration for advanced marketing technology stacks or in Cloud platforms (AWS, Azure, Google Cloud) to maximize efficiency.

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Tech Audit

Technical audit of Google Display Ads campaigns to evaluate the integrity and efficiency of tracking implementations. This includes a comprehensive review of pixels, tags, and audience lists to ensure accurate data collection and attribution.

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