AI workflows can run continuous checks on campaign performance metrics such as ROAS, conversion rates, and spend pacing. Based on defined rules or predictive models, budgets can be reallocated or bid strategies adjusted automatically – maximizing efficiency without manual intervention. In addition, automated optimization reduces the risk of human error and ensures campaigns stay aligned with overall business objectives in real time. These processes create a scalable framework that adapts to changing market conditions and goals.

The implementation of the Amazon Ads infrastructure begins with a structured alignment phase. This stage establishes a shared understanding of marketing objectives, measurement goals, audience strategy, and data usage. Clarifying roles, responsibilities, and processes early on provides the foundation for clean technical setup and effective account enablement. Structured collaboration ensures that Amazon Ads setups reflect strategic intent, operational clarity, and are built for scalable execution.

Implementation and configuration of Amazon Marketing Cloud (AMC) to enable clean data ingestion, secure querying, and tailored dashboard creation. Digitl supports advertisers in setting up access, schema structure, and initial data pipelines – allowing for a solid foundation for reporting and analysis. With AMC in place, advertisers gain the ability to run advanced attribution models, incremental lift studies, and audience path analyses, generating actionable insights for future campaign planning.

Amazon’s Conversions API enables the import of first-party web, app, and offline conversion events from supported third-party data platforms – such as HighTouch – into Amazon DSP. These conversion signals can be used for campaign measurement, reporting, audience building, and optimization. Digitl supports the setup of such integrations, including mapping supported identifiers, managing prerequisites, and enabling conversion delivery.

Amazon Marketing Cloud (AMC) queries are scheduled and managed to keep audience segments, measurement tables, and reporting layers updated. Digitl ensures privacy thresholds, naming standards, and governance rules are respected in each automation step. This structured approach ensures consistency across reporting cycles and reduces the risk of discrepancies in data outputs.

Amazon Marketing Cloud SQL is a query language used within AMC to access and analyze advertising data. It allows advertisers to perform various analyses, such as measuring campaign performance, understanding customer behavior, and creating custom audiences for targeting. AMC SQL is based on standard SQL syntax, making it accessible to those familiar with SQL.

Attribution models are implemented through structured SQL queries within AMC. Digitl supports the setup of flexible logic to apply different models – such as fractional conversion attribution methods – based on campaign type, format, or funnel stage. These models provide advertisers with a transparent framework for comparing strategies and validating performance outcomes across multiple touchpoints.

Marketing Mix Modeling (MMM) can isolate the contribution of upper-funnel Amazon Ads placements – including viewable impressions on Prime Video, Twitch, Fire TV, and Amazon Music. These formats are evaluated without dependence on user-level IDs, enabling measurement of incremental impact using statistical modeling. The insights gained allow advertisers to quantify brand-building effects while optimizing media allocation across channels.

Digitl supports clients with creating a tailored roadmap for activating audiences through Amazon Marketing Cloud. This includes defining use cases that benefit from AMC’s event-level data, such as retargeting based on purchase behavior, suppression of recent converters, or reaching multi-category shoppers. Activation paths are planned to ensure data thresholds, audience eligibility, and privacy requirements are met. Digitl supports the creation of audience SQL logic, testing and validation, and the scheduling of refresh cycles.

Effective measurement starts with reliable data. Digitl supports the ingestion of complete, accurate, and timely datasets – ensuring that data and conversion signals are aligned across all relevant sources. Structured onboarding processes, schema validation, and threshold monitoring are used to maintain data quality throughout the technical environment. In addition, continuous checks and automated alerts highlight anomalies early, preventing downstream reporting errors. This proactive approach ensures that advertisers can trust the integrity of their data for decision-making.

This is an area of audit that reviews whether Amazon Ads tracking is implemented in a way that allows for reliable measurement of user behaviour. It includes validation of the Amazon Ad tag setup in Campaign Manager, including correct implementation of base code and event tracking for key interactions such as purchases or add-to-cart events. The configuration of ASINs for attribution is also evaluated to ensure accurate performance reporting at product level. For mobile app campaigns, the audit checks whether a mobile measurement partner (MMP) is properly associated to enable app event tracking.