Advertising technology

Client-specific advertising data and automation workflows.

Incremetrix supports the data, integration, and automation work that makes retail media operations repeatable: connecting sources, normalizing reporting, encoding rules with operator review, applying AI-assisted analysis where it speeds up the work, and measuring what changed.

Scoped to each engagement

Technology work is scoped to each client engagement and delivered as integrations, reporting infrastructure, dashboards, or automation workflows rather than as a standalone software product. Work happens inside the client’s own accounts and environments.

Capabilities

Four areas of technology work.

Each is built for the account it serves, documented, and handed over in a form the client’s team can operate.

Data connections

API and structured-data integration support under client agreements. Advertising platform reports, retail and sales data, and inventory feeds, connected in the client’s own environment wherever possible.

  • Advertising API access arranged under the client’s own accounts and agreements
  • Scheduled report retrieval and structured exports
  • Data QA: completeness, freshness, and reconciliation checks

Reporting pipelines

Repeatable data preparation and dashboard or reporting workflows. One structure across networks, so Amazon, Walmart, Target, and Wayfair performance can be read side by side.

  • Normalized campaign, product, and placement reporting
  • Dashboards built in the client’s tooling or a shared workbook
  • A written definition for every metric that appears
  • AI-assisted summaries of recurring reports, reviewed before they are sent

Automation

Rule-based campaign and monitoring workflows where they are technically appropriate and where the client wants them. Rules are written down, changes are logged, and an operator reviews before anything material moves.

  • Budget pacing and cap alerts
  • Bid and placement rules with guardrails
  • Anomaly detection on spend, traffic, and conversion
  • Campaign QA checks on settings and targeting
  • AI-assisted classification and pattern detection, such as grouping search terms or flagging unusual campaign behavior

Measurement infrastructure

Structures that connect advertising activity with business outcomes: consistent attribution windows, joins to business KPIs, test designs, and reporting that makes results comparable over time.

  • Measurement plans and KPI definitions
  • Incrementality test design and readout, where the account supports it
  • Period-over-period and product-level comparisons

How a workflow runs

Data in, reviewed decision out, result measured.

The same shape applies to a reporting pipeline, a pacing alert, or a bid rule. The operator review step is not optional.

  1. Retail media data platform reports and APIs
  2. Normalized reporting one structure across networks
  3. Decision rules thresholds and guardrails
  4. Operator review a person confirms
  5. Campaign action logged change
  6. Measurement what changed

Measurement results feed the next round of rules and review.

Scoping

How technology work is scoped.

Four steps, agreed in writing before anything is built.

  1. Identify the repeatable or data-heavy work

    Where time goes, where errors happen, and which decisions wait on data that arrives late or in the wrong shape.

  2. Confirm data access and agreements

    What the client’s accounts and agreements allow, which sources are in scope, and who owns the environment the work runs in.

  3. Build, document, and test

    The pipeline, dashboard, or rule set, with written definitions and a test period before it touches live decisions.

  4. Operate with review, then hand over or maintain

    Run with operator review on material actions. The client keeps the documentation and can pause any rule at any time.

Discuss a data or automation workflow.

Describe the recurring work, the data sources involved, and the decisions that wait on them. We will scope what is worth automating and what should stay manual.