IntentMatch Video

Identifies and matches high-intent audiences for Amazon DSP Brand+ video campaigns to improve targeting efficiency and reduce reliance on broad or static segments.

The Problem

“Improve Amazon DSP Brand+ video targeting by identifying high-intent audiences”

Organizations face these key challenges:

1

Broad audience targeting produces low relevance and wasted impressions

2

Static segments become outdated as customer behavior changes

3

Manual audience optimization is slow and labor-intensive

4

Intent signals are spread across multiple data sources and hard to combine

Impact When Solved

Increase conversion efficiency by prioritizing high-intent viewersReduce spend wasted on low-propensity audience segmentsRefresh audience targeting dynamically as intent signals changeImprove campaign planning with ranked audience recommendations

The Shift

Before AI~85% Manual

Human Does

  • •Define Brand+ video audiences using demographics, interest groups, and static retargeting pools
  • •Review campaign performance reports for CTR, view-through, and conversion trends
  • •Manually adjust audience targeting and exclusions based on recent results
  • •Combine signals from campaign, site, and commerce data to refine segment choices

Automation

  • •Provide standard campaign reporting summaries
  • •Surface basic audience and conversion metrics
  • •Refresh predefined audience lists on a scheduled basis
With AI~75% Automated

Human Does

  • •Set campaign goals, budget priorities, and audience strategy guardrails
  • •Approve recommended high-intent audiences for Brand+ campaign activation
  • •Review tradeoffs between reach, efficiency, and conversion goals

AI Handles

  • •Analyze behavioral, contextual, campaign, and commerce signals to score audience intent
  • •Rank and match high-intent audiences to each Brand+ video campaign
  • •Continuously refresh audience recommendations as intent signals change
  • •Monitor targeting performance and flag audience shifts or low-efficiency segments

Operating Intelligence

How it works

AI runs the first three steps autonomously.

Humans own every decision.

The system gets smarter each cycle.

Confidence95%
ArchetypeRecommend & Decide
Shape6-step converge
Human gates1
Autonomy
67%AI controls 4 of 6 steps

Who is in control at each step

Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

Loop shapeconverge

Step 1

Assemble Context

Step 2

Analyze

Step 3

Recommend

Step 4

Human Decision

Step 5

Execute

Step 6

Feedback

AI lead

Autonomous execution

1AI
2AI
3AI
5AI
gate

Human lead

Approval, override, feedback

4Human
6↺ Loop
AI-led step
Human-controlled step
Feedback loop
TL;DR

AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.

The Loop

6 steps

1 operating angles mapped

Operational Depth

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