Ad Audience Targeting

Audience Targeting

Map who the customer is (ICP) and what they do that signals intent (buying signals) into a layered paid-media targeting plan: which audience tiers to run, how each is defined, sized, budgeted, sequenced for testing, and kept from bidding against the others.

The tier logic, exclusion discipline, overlap math, and funding floors are identical for B2B and B2C. What differs (see the B2B vs. B2C section for detail):

• Universe size: B2B ICPs are often smaller than platform minimums.
• Which tiers dominate: B2B leans firmographic and list-based; B2C leans broad, lookalike, and behavioral.
• Cycle length.
• Success metric: pipeline quality vs. volume CPA/ROAS.

This skill produces the plan, not the platform setup. It places and sizes the retargeting tier but does not design the per-stage retargeting sequence (mbfinotti/advertising-skills@retargeting-funnel), and it assumes a seed list exists but does not select or build it (mbfinotti/advertising-skills@lookalike-audience-seeds).

Evidence gate

• Never assert an ICP, a buying signal, or a tier without sourced data behind it: an ICP document, customer/CRM data, analytics, or past campaign results.
• Missing ICP → stop and request one (or a customer list to derive it from). Never invent an ICP from the product description alone; a plan built on an imagined customer optimizes toward fiction.
• Unknown attributes score neutral, never negative. Absence of evidence is not a negative signal; scoring it negative systematically buries accounts with a thin public footprint, which correlates with size, not fit.
• Record the evidence next to each tier in the plan (source and date), so the plan can be audited when performance surprises.

Clarifying questions

Ask once, briefly, before planning; skip anything already answered.

1. B2B or B2C, and what does the ICP say - who buys, and what evidence backs it?
2. What counts as a conversion, and what is the target CPA (or ROAS)?
3. Roughly how many conversions per week does the account currently produce? (Sets the broad-vs-layered default.)
4. What first-party assets exist: customer list (size), site traffic volume, CRM, engaged followers?
5. What is the total monthly budget for this plan?
6. How large is the addressable universe - thousands of accounts or millions of consumers?
7. Does the offer touch a regulated category (housing, employment, credit, financial products, health, politics)?
8. By what date must results land - is there a hard deadline (launch, quarter close, seasonal window), or is the timeline open?
9. Do you want a one-off win this cycle, or a compounding asset that keeps paying after the campaign ends?
10. What is your effort ceiling - hours per week, who executes, and whether legal/privacy review is available to you at all?

The last three re-rank the tier plan before it is written. Say in the plan which answer moved which tier:

• Hard near-term date promotes first-party and retargeting tiers - they return readable evidence within days - and demotes cold broad, which needs a full learning cycle before it says anything.
• Compounding mandate promotes first-party list growth and cold broad: one builds a seed and a suppression asset the business keeps, the other trains a delivery model that improves with every conversion. A retargeting pool decays to nothing within weeks of the refill stopping.
• No privacy review available at all deletes every tier that needs identifiable data uploaded - first-party custom, and lookalike built from a customer seed - rather than ranking them last; they are not options for this account. A low effort ceiling on its own only demotes them, and promotes platform-native behavioral and broad tiers.

Attributes vs. signals

The translation step everyone skips: an ICP lists _attributes_, a targeting plan runs on attributes _and_ signals. Distinguish them explicitly.

• A signal older than ~90 days is context, never a trigger. Two fresh independent signals (e.g. funding + relevant hiring) outrank one stale one.
• Test for any candidate signal: given ten people/accounts that already pass the attribute filter, does it say which to reach first? If not, it's an attribute wearing a signal costume.

The tier model

Every plan is assembled from these six tiers, ordered by efficiency - outcome bought per unit of effort - never by which is cheapest to stand up. Include a tier only when a real, evidenced signal defines it; an empty tier is a line item, not an audience.

• efficiency: first-party custom > retargeting > lookalike > behavioral/in-market > cold broad > interest & affinity
• value (volume of results the tier can produce at its ceiling): cold broad > lookalike > behavioral/in-market > first-party custom > retargeting > interest & affinity
• effort: cold broad > retargeting > first-party custom == lookalike > behavioral/in-market == interest & affinity
• compliance cost: first-party custom > lookalike > retargeting > behavioral/in-market > interest & affinity == cold broad

The axes disagree on purpose:

• Interest, the cheapest tier to stand up, is the least efficient one.
• Cold broad, the tier with the highest ceiling, is the most expensive to run and the slowest to read.
• First-party leads because a list the business already owns converts after an hour of setup. It also carries the heaviest consent, DPA and data-residency exposure of the six, which is what the compliance axis is there to price.