Automation & action integrations that turn decisions into controlled execution

Affiliates running traffic across multiple offers and sources can't manually watch every campaign. The gap between a paused loser and a burned budget is often hours — or a night's sleep.

RedTrack's Automation lets you define the conditions under which a campaign stops, scales, or rotates — based on cost, revenue, and attribution data RedTrack tracked independently, not what a network chose to report. EPC and ROI thresholds trigger real changes in your connected ad platforms, not just notifications you'll see later. For teams using separate traffic management tools, the same data routes outward via API — so your existing stack stays in control.

Scaling paid spend without losing control means changes need to follow consistent logic, not daily gut checks. That's hard when your data is scattered and your execution tools don't share a source of truth.

RedTrack structures your conversion data — purchase revenue, attribution, LTV signals — and makes it available for execution wherever your team applies it. Use RedTrack's Automation to pause underperforming campaigns or shift budget toward what's working. Route the same data to the campaign management tools or optimization platforms your growth team already relies on. The logic stays consistent. The execution stays yours.

Agencies face a structural problem at execution time: every client has different platforms, different thresholds, and different tolerance for automated changes. Without a shared data source, applying consistent rules across accounts means rebuilding logic from scratch for each one.

RedTrack standardizes how conversion data is captured and structured across every account. Automation rules can be applied from the same data layer — so the logic your team uses for one client can be replicated across all of them. When clients use their own campaign management tools, RedTrack data routes to those systems via API. Execution becomes predictable by design, not by effort. And when a client questions a change that was made, you're pointing to the rule that triggered it — not reconstructing what happened from memory.