Instructional Queries
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      Custom Attribution Linear Touch

      Learn about the Custom Attribution Linear Touch query and its applications on Intentwise Explore (AMC).

      Custom Attribution Linear Touch

      Learn how to use the "Custom Attribution - Linear Touch" instructional query in Amazon Marketing Cloud (AMC) to evaluate the combined impact of all ad interactions leading up to a conversion.

      This query distributes credit equally across all touchpoints in a shopper’s journey. It helps marketers:

      • Understand the cumulative influence of multiple ads and channels

      • Evaluate cross-channel contribution to conversion

      • Identify campaigns that assist earlier in the path to purchase

      How It Works

      1. Navigate to Intentwise Explore

      2. Go to Queries > Query Library

      3. Search for and add "Custom Attribution - Linear Touch" to your saved queries

      4. Fill in the required fields and run the query (see this article for detailed settings)

      5. Once executed, access the results under the Insights section for campaign-level metrics and visualizations.

      The query provides detailed metrics for each campaign, such as impressions, clicks, user reach, conversions, conversion rate, total units sold, and total product sales. 

      To use this query effectively, you'll need data from multiple ad campaigns, including tables like dsp_impressions, dsp_clicks, sponsored_ads_traffic, and conversions_with_relevance. You can customize the dashboard based on your campaign types, ad type, lookback windows, and more to tailor the insights to your specific needs.

      For more information, refer to our data model.

      Key Use Cases

      • Assist Attribution: Measure which campaigns contribute frequently but don’t close

      • Channel Collaboration: Understand how Sponsored Ads and DSP work together across journeys

      • Incrementality Analysis: Identify undervalued campaigns using linear contributions

      Tip: Pair this with last-touch and first-touch queries to reveal gaps in strategy and surface assist drivers

      Dashboard Walkthrough & Examples

      1. Compare Ad Type Balance (CTR vs CVR)

      📊 Example Insight:

      • SB leads in CTR (0.31%), SP delivers a balanced 0.28% CTR and 0.17% CVR

      💡 How to use this:

      • Validate which ad types are most effective across multiple touches

      • Expand ad types that maintain consistent engagement

      2. Spot Linear Contribution Leaders

      📋 Example Insight:

      • SD-Awareness-Drone delivered 1,668 conversions, $22K in sales with broad reach

      • SP-A-Drones 2 drove 532 conversions, indicating strong support performance

      💡 How to use this:

      • Don’t overlook assist campaigns—ensure they stay funded

      • Revisit conversion-only optimizations to ensure balance

      3. Find Underrated Campaigns in a Multi-Touch World

      🔍 Example Insight:

      • SP-M-KT-NonBrand-Drone Decals 10 shows 505 clicks, 109 conversions with 0.10% CVR

      💡 How to use this:

      • Reinvest in campaigns showing recurring middle-funnel presence

      • Align messaging with broader journey milestones

      4. Evaluate Ad Type Share in User Reach

      📈 Example Insight:

      • SP drives 85% of reach, with SB and SD forming the remaining 15%

      💡 How to use this:

      • Analyze how supporting ad types complement SP

      • Revisit budget allocation for holistic coverage

      5. Revenue Attribution Across Channels

      💰 Example Insight:

      • SB_M_KT - M6 Drones generated $18.9K, while SD-Awareness-Drone led with $22.1K

      💡 How to use this:

      • Identify which campaigns consistently contribute across journeys

      • Align reporting with equal attribution for fairer budget allocation

      Frequently Asked Questions

      What are instructional queries?

      Amazon Marketing Cloud's (AMC) instructional queries provide pre-written SQL code that AMC users can use as is or modify for common measurement and analytics tasks.