Buyer briefs and get_products request shape

This supplement prepares buyer-side implementers to turn a human campaign request into a precise get_products call. The goal is not to make the brief verbose. The goal is to put intent in the brief and hard constraints in typed fields so the seller can curate inventory without guessing which parts are negotiable.

This module teaches the AdCP 3.2 targeting-aware discovery contract. Use it against sellers and SDKs that declare 3.2 support. The public training-agent lab will enable these calls after the 3.2 beta SDK release; implementation is tracked in issue #6199.

Mental model

Input	Use it for	Avoid putting here
`brief`	Buyer intent, semantic audience language, context, tone, business goal, and requirements without a typed representation	Constraints that already have structured fields
`filters`	Hard offer filters—metadata, dates, budget, availability, commercial fit, and reporting capabilities—that exclude non-matching products	Delivery targeting or soft preferences
`targeting_overlay`	Exact delivery constraints known now; availability, pricing, and forecasts must account for them	Product characteristics or values the buyer has not chosen yet
`required_overlay_support`	Targeting dimensions whose values will be selected independently on packages later	Current targeting values or a request for one product per value
`brand`	The buyer brand identity the seller uses for eligibility, safety, and fit	A second copy of the campaign brief
`catalog`	Commerce or product-set context when the campaign is catalog-driven	General brand positioning
`refine`	Specific changes to a prior discovery response	New unrelated discovery goals

What goes in the brief

Use the brief for context that a seller or curator needs to make judgment calls:

campaign objective: awareness, consideration, qualified traffic, store visits, conversion, renewal
audience description in human terms
product, offer, seasonal context, or creative direction
must-understand sensitivities such as family suitability or competitive adjacency
success language that is not a metric filter, such as “favor trusted editorial environments”

Example:

{
  "idempotency_key": "550e8400-e29b-41d4-a716-446655442008",
  "buying_mode": "brief",
  "brief": "Launch Nova Running's spring trail shoe line with outdoor enthusiasts. Favor trusted adventure and fitness contexts, avoid discount-led positioning, and prioritize packages that can support a brand-lift readout.",
  "brand": {
    "domain": "novarunning.example"
  }
}

What goes in filters

Use filters when a product that fails the condition should not come back. That exclusion rule is identical in brief, wholesale, and refine; the mode changes how the seller curates and versions the result, not whether a valid filter applies. Good filter candidates:

required channels or formats
required measurement or reporting capabilities
pricing currency constraints
budget ranges
fixed-price requirements
product categories for wholesale/catalog use

Example:

{
  "idempotency_key": "550e8400-e29b-41d4-a716-446655442009",
  "buying_mode": "brief",
  "brief": "Launch Nova Running's spring trail shoe line with outdoor enthusiasts. Favor trusted adventure and fitness contexts.",
  "brand": {
    "domain": "novarunning.example"
  },
  "filters": {
    "channels": ["ctv", "display"],
    "pricing_currencies": ["USD"],
    "required_metrics": ["impressions", "clicks"]
  }
}

If the buyer says “ideally CTV, but display is okay,” keep that preference in the brief. If they say “CTV only,” use filters.channels.

What goes in targeting

Use targeting_overlay for exact delivery constraints the buyer knows now:

{
  "targeting_overlay": {
    "geo_countries": ["US"],
    "demographics": {
      "age": { "min": 25, "max": 44, "include_unknown": false }
    }
  }
}

Use required_overlay_support when the dimension is mandatory but its values will be chosen later:

{
  "required_overlay_support": {
    "geo_metros": { "systems": ["nielsen_dma"] },
    "placement_selection": true
  }
}

This does not ask for products broken out by DMA or placement. It asks for products on which packages can select those values later. Hard prose targeting remains binding. If an exact constraint appears only in prose, the seller must infer its wire meaning. Prefer the structured field. When that structured interpretation materially affects eligibility, pricing, or forecasting, the seller must return response-level targeting_resolution.brief_targeting; inspect it before purchase. Also inspect sparse targeting_resolution.modifications; selecting that configured product_id accepts the disclosed differences.

Brief vs. refine

Use buying_mode: "refine" when the buyer is reacting to a previous discovery response. A refine request should point at what changed: remove a product, adjust budget, request more premium placements, narrow geography, or ask for alternatives. Do not send a totally new campaign in refine; start a new brief request instead.

Implementation checklist

Read get_adcp_capabilities.adcp.supported_versions, pin a compatible 3.2 release in adcp_version, and validate the echoed served release before using targeting-aware discovery.
If release precision is absent, major-only, or 3.1-or-earlier, omit the 3.2 fields and fall back to retained legacy targeting filters or explicit brief prose; unknown fields may otherwise be silently ignored.
Normalize the human request into intent, hard constraints, and follow-up changes before calling the seller.
Preserve the buyer’s business language in brief; do not collapse it into only keywords.
Put product characteristics in filters and exact delivery constraints in targeting_overlay.
Use required_overlay_support only for dimensions whose values will be supplied later.
Inspect every returned targeting_resolution; silence confirms an unchanged structured overlay, not prose interpretation.
Keep brief out of wholesale mode.
Persist the request tuple with the response so later refine calls and wholesale_feed_version comparisons are scoped correctly.

Practice prompt

A buyer says:

We need a six-week US launch for Acme Meals’ new family dinner kits. We want CTV or online video, only USD pricing, something suitable for parents with kids, ages 25–44, and we need completion-rate reporting. We will choose DMAs after planning.

Expected decomposition:

Brief: family dinner kit launch, parent audience, suitable contexts, six-week launch.
Filters: video-capable channel/format constraints, USD pricing, completion-rate reporting.
Targeting overlay: US and ages 25–44.
Required overlay support: Nielsen DMA selection later.
Brand: Acme Meals domain or BrandRef.

Getting Started

Building with AdCP

Protocol

Using AAO

FAQ

Trust & Security

Reference

Certification

Buyer briefs and get_products request shape

Buyer briefs and get_products request shape

Mental model

What goes in the brief

What goes in filters

What goes in targeting

Brief vs. refine

Implementation checklist

Practice prompt

​Buyer briefs and get_products request shape

​Mental model

​What goes in the brief

​What goes in filters

​What goes in targeting

​Brief vs. refine

​Implementation checklist

​Practice prompt

Buyer briefs and get_products request shape

Mental model

What goes in the brief

What goes in filters

What goes in targeting

Brief vs. refine

Implementation checklist

Practice prompt