Advanced analysis for DV360 campaigns applies distinct methodologies to evaluate campaign performance. Predictive modeling uses historical data to estimate conversion likelihood. Marketing Mix Modeling (MMM) quantifies the contribution of DV360 within the broader media mix. Geo-based incrementality testing isolates true campaign lift through region-based experiments. In-platform diagnostics complement these methods by identifying performance drivers such as device, inventory, and creative – supporting data-informed optimization.

Automation services for DV360 focus on streamlining campaign operations and ensuring consistent quality across large-scale programs. This includes automated naming conventions, frequency and budget governance, monitoring & alerting, and workflow orchestration via tools like Dagster and Data Build Tool (dbt). Digitl builds custom logic and alerting pipelines to ensure campaign setup integrity, pacing accuracy, and timely reporting – enabling more scalable, controlled execution.

In DV360, data enrichment improves targeting and measurement by adding external signals to campaign inputs. This includes importing audience segments, integrating situative or other event data, and applying predictive scores (e.g., conversion probability). These enrichments typically occur outside of DV360 – within CDPs, analytics platforms, or cloud pipelines – and are imported as custom audiences or used to plan media strategy. Enrichment helps ensure campaigns are aligned to real business priorities and audience relevance.

DV360 supports various integration points for bringing in first-party and offline data. This includes Customer Match via hashed uploads for CRM imports (for instance based on Customer Data Platform integrations), Floodlight-based conversion tracking, and secure clean room integrations for privacy-compliant segmentation. Digitl implements cloud-based pipelines to connect external data sources and integration of high-value audiences for activation. Such data usage ensures targeting precision and attribution integrity across campaigns.

Custom bidding in DV360 enables advertisers to create their own bidding logic by creating algorithms that prioritize outcomes beyond standard KPIs. This includes bidding on data representing customer lifetime value, lead quality, or attention-based signals such as scroll depth, time on screen, or viewability. Digitl supports the creation, testing, and deployment of Custom Bidding scripts – aligning bid decisions with upper-funnel performance and brand metrics or conversion value and ROAS models.

Knowledge Building ensures internal teams are equipped to work effectively with DV360’s technical features and custom workflows. This includes enablement around audience structuring, platform configuration, custom reporting, and the logic behind automation and bidding strategies. Digitl helps with this through structured onboarding, documentation, and tailored training formats – from team workshops to solution-specific knowledge transfers. The goal is to increase internal autonomy and reduce reliance on external resources for daily execution.