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Advertising

ASIN Target Negation

mx-asin-target-negation

Phase 2 negation review for ASIN targets matched through auto, category, and other product attribute targeting paths, with product-page overlap analysis.

Run it in chat
/mixshift-ai:mx-asin-target-negation <brand>

or just say run asin negation review for <brand>

Comes with the plugin, one install activates every skill. See the install flow. Needs brand setup first.

Why it exists

Auto, category, and other automatic targeting paths pull in ASIN targets nobody chose, and separating the ones that are genuinely wrong-category from the ones that simply have not converted yet at this specific campaign and ad group takes a PDP-by-PDP judgment call that most reviews skip in favor of one generic low-performer bucket.

What you get

ASIN targets sorted into clean negate, review, watch, and protected buckets, judged on product-page overlap and location-specific lifetime performance rather than an account-wide average, so the account manager only has to weigh in on the ones that are genuinely ambiguous.

What your agent can do

  • 01

    Pull ASIN-triggered rows for a configurable window across campaigns and ad groups

  • 02

    Suppress ASINs already under manual targeting and flag the rest for review

  • 03

    Evaluate product-page and form-factor overlap to separate clean negates from review-and-watch

  • 04

    Join lifetime performance by campaign and ad group for context before recommending

StatusLive
CategoryAdvertising
Brand contextRequired
Hosts
Claude CoworkClaude CodeMixShift CLI
Get the plugin

New or existing MixShift customer, both paths start here.

Talk to us

Before you run

Requires brand setup

This skill reads a brand’s context to calibrate its output. Build it once per brand, then every teammate runs on the same shared context.

/mixshift-ai:mx-brand-context <brand>How brand setup works →
What it reads from your brand context
  • Pre-check lifetime-orders floor: the minimum lifetime orders at a location before an ASIN target is eligible to negate
  • ACoS target: the reference efficiency ASIN performance is judged against
  • Lane rules and protected terms: the lane boundaries and anchors read from brand context
  • Manual conquest ASIN corpus: the validated competitor list new auto-discovered ASINs are checked against before being called irrelevant
Gets sharper over time

As the manual conquest ASIN corpus and past PDP judgments accumulate across runs, newly auto-discovered ASINs get matched against a growing set of already-validated competitor PDPs instead of judged cold, so fewer genuinely relevant ASINs get miscalled irrelevant.