Audience targeting worksheet

What this produces

The "who do we target and why" document. It answers, in order: who can they serve, who is the priority buyer, how do we reach that buyer most cheaply, what does LinkedIn actually let us select, which named segments do we chase, what do we bid on in search, and what signals build the account-based list.

Output: a dark-themed HTML view and/or a branded .docx, saved to your output directory.

Prerequisites

• Recommended: competitive white space (the ownable position points the priority ICP) and company recon (ICP, verticals, buyer profiles, warm-asset inventory, tracking state). Any first-party call transcript or intake outranks secondhand notes.

Key defaults

• Budget shape: warm start 60/25/15, cold start 40/35/25. Under $3-5k/mo, run a single channel and a single cold audience; do not split.
• No warm pools yet (thin-footprint account): warm-first is not available on day one because there are no paid pools to retarget. Phase 1 leans on in-market search capture plus a tight LinkedIn qualify-and-retarget layer and a small native cold test, then shifts toward warm as the Insight Tag, website-visitor ID, and form pools fill. Say this plainly rather than quoting a warm-first split the account cannot run yet.
• Cold audience size: ideal ~150K; under 10K stalls, over 500K dilutes. If the primary persona builds under ~25K, move it into the ABM structure, do not broaden.
• Always: Audience Expansion OFF, LinkedIn Audience Network OFF. Suppress customers, employees, competitors, students.
• Google as capture vs lead lane: default framing is capture (feeds the pools). In high-volume, short-cycle categories (business funding, legal, home services), in-market search is a PRIMARY lane because the buyer is already looking and decides in days. When you position it that way, always pair it with the competitiveness and landing-page caveat in Section 6.

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The output order (seven sections, this exact sequence)

Open with WHO the audience is, then narrow. Do not open with segments or ladder mechanics. Give each section its own distinct visual treatment; five look-alike card stacks is the failure mode this sequence exists to prevent.

SECTION 01 - Target ICP and Total Addressable Market. Three parts, three visuals:

• The serviceable market plus a TAM read. Ground the TAM with a real market-size pull (search the category), present as a small stat grid, and label every figure a third-party estimate that varies by source. The point is directional, not precise. Note the account's own share so the constraint reads as aim, not room. At least one stat should reinforce the priority-ICP wedge, not just market size.
• Narrowing to the priority ICP, derived from the white space. Present as a narrowing funnel (Serviceable market -> Priority ICP -> Beachhead): three descending, color-coded bands, each with a one-line scope note inside and a one-line "who / why" beneath. Build in CSS (centered rounded bars of decreasing width), not SVG (labels never clip), and not identical stacked cards. Caption: each band is a subset of the one above.
• The buying committee as persona cards (a 2x2 grid). Each card: role name + a priority pill (Primary target / Secondary / Objection to answer), a one-line "who," a "cares about" line, and a "How we reach them" row of targeting-filter chips. Four roles: economic buyer, champion, influencers/users, gatekeepers. Non-targetable roles are framed honestly: a gatekeeper (an incumbent vendor, a bank that said no) is usually NOT an ad audience; label it "Objection to answer" and put the objection-handling message in its chip row, not a fake targeting filter. For SMB / owner-led buyers the roles collapse onto one or two people; adapt rather than inventing a four-person committee.

SECTION 02 - The audience efficiency ladder. Five rungs, in this order, built as a CSS stepped-bar ladder (bar width encodes cost per lead, narrow/cheap at the top), each with an order number, name, a CPL band, and the actual example pools:

1. Warm first-party, bottom of funnel ($75-150, runs first): current CRM pipeline, current MQLs, named accounts already on the site, plus form starters and abandoners.
2. Warm first-party, mid funnel ($120-250): warm ad engagers, company-page visitors, and SEO/organic/paid-search traffic already hitting the site.
3. In-market search traffic (capture, feeds the pools): buyers already looking, captured on paid search across Google and Bing plus listing and review sites. In high-volume categories this may be a primary lane, not just capture.
4. Account-based ($250-400, the workhorse): a named list built with intent, timing, and fit signals from third-party data, person-filtered to the buying committee. For SMB / owner-operator buyers where named-account ABM does not fit, this becomes signal-built target LISTS (vertical + geography, uploaded as a Matched Audience), not a named enterprise account list. Say which.
5. Cold LinkedIn, native filters ($300-600+, last): broad title and seniority targeting. State plainly that it carries a longer sales cycle, needs more budget to warm and convert, and runs only after the tiers above prove out.

Close with a compact budget-shape callout and a one-line legend (wider bar = higher cost per lead, cheapest runs first, cold earns budget last).

SECTION 03 - How the motion works. One flow visual (inline SVG). Show earned and warm traffic -> the site -> LinkedIn qualifies firmographically and converts -> signals (named accounts, hidden pipeline, retargeting pools), with a feedback loop from signals back to the pools. Figcaption: LinkedIn is the only channel that filters site traffic firmographically before spend, which is why warm leads and cold runs last.

SECTION 04 - LinkedIn targeting attributes. The official Campaign Manager palette, shown as tag groups (chips), one group per attribute. See the hard rule below.

SECTION 05 - The priority segments. Two or three named plays assembled from the palette:

• At least one LinkedIn-native-only, buildable today with no third-party data. This is the pinned launch-now play.
• At least one combo (native + a third-party signal), framed explicitly as an expansion / upsell. Third-party intent, technographic, website-visitor, and account-engagement signals can be composed through a signals tool such as DemandSense and uploaded as a Matched Audience.
• Each card: name + character line, a tag ("LinkedIn native, launch now" or "LinkedIn + [signal], expansion"), a build recipe using official attributes, an estimated size (observed vs inferred), build defaults, and a one-line "why chase it" tied to a persona.

SECTION 06 - Paid-search core groups. Not a flat keyword table. Open with the intent-vs-cost tradeoff (two panels side by side):

• "Why this lane is worth it": clear intent (searcher already decided they need the thing), a shorter sales cycle than any cold audience, self-qualifying queries.
• "The catch": highly competitive (national players bid head terms up hard), costly clicks (category keywords are among the priciest in B2B), and the landing page, not the click, decides the return.

Then the core groups, one card each with example terms as tags and a pair of indicator chips (intent high/med/low AND cost/competition high/med/low): Category capture; Method / differentiator (often cheapest, least contested); Product / service long tail; Competitor conquest ("[rival] alternative"); Comparison / solution-aware (retarget, don't convert); Brand defense / content.

Then a mandatory landing-page / CRO callout: because in-market clicks are expensive, each core group needs a matched landing page, one clear action, proof for the buyer's state of mind, and a short fast form. This is where a smaller advertiser out-converts bigger spenders on the same click. Then a launch recommendation (5-6 starting terms, match strategy) and a mandatory negative-keyword callout (5+ categories with reasoning; lead with brand-name collision negatives where a name is also a place, park, or common word).

SECTION 07 - Third-party fit and intent signals. At the bottom. The enrichment inputs that build the account-based list (rung 4) and sharpen cold. A converging visual (several signals -> one scored account view), 6+ signal cards (what each indicates / its source), and an enrichment-workflow callout: build and enrich the list, compose the signals through a tool such as DemandSense, upload as a Matched Audience, and hand the top accounts to outreach.

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Hard rule: LinkedIn targeting uses official attributes, not keywords

LinkedIn Campaign Manager has no free-text job-title keyword field. It targets official, curated taxonomies. Never write "job title keywords." Always use the real attributes and values, shown as chips:

• Member Job Titles (standardized): select from LinkedIn's standardized list. A concept that is NOT a clean standardized title (e.g. "ways of working," "continuous improvement") is reached through Job Function + Seniority + Member Skills, not a title. State this in the section intro.
• Buyer-situation traits are message-qualified, not filter-qualified. A recent bank decline, a credit situation, a lease ending, a recent funding round, a life event - LinkedIn cannot target these. They're reached by the ad message plus self-selection ("turned down by your bank?"), sometimes proxied by a third-party intent signal or a search-behavior retarget, never a native filter.
• Job Seniorities (official set): Owner, Partner, CXO, VP, Director, Manager, Senior, Entry, Training, Unpaid.
• Job Functions (official set): Accounting, Administrative, Arts and Design, Business Development, Community and Social Services, Consulting, Education, Engineering, Entrepreneurship, Finance, Healthcare Services, Human Resources, Information Technology, Legal, Marketing, Media and Communications, Military and Protective Services, Operations, Product Management, Program and Project Management, Purchasing, Quality Assurance, Real Estate, Research, Sales, Support.
• Industries (LinkedIn V2 taxonomy - use current names): e.g. "Business Consulting and Services," "Software Development," "IT Services and IT Consulting," "Financial Services," "Banking," "Insurance," "Manufacturing," "Hospitals and Health Care." Verify the exact current label before asserting it (a quick web check is cheap; guessing an old label is a visible error).
• Company Size (official bands, exact): Self-employed, 1-10, 11-50, 51-200, 201-500, 501-1,000, 1,001-5,000, 5,001-10,000, 10,001+. Never write "1,000-plus" as a filter.
• Member Skills, Member Groups, Member Interests, Member Traits: use real taxonomy values. Interests and traits are a widening layer on cold only, never the sole filter.
• Location and Exclusions (existing customers via company list, employees, competitors, students, job seekers).

Build standard (HTML and DOCX)

• Visual variety: each section gets a distinct treatment (stat grid + narrowing funnel
  • persona cards; stepped-bar ladder; flow SVG; tag groups; segment cards; two-panel tradeoff + indicator cards; converging SVG). No more than two consecutive sections share a pattern.
• HTML: dark theme. Suggested tokens - bg #0a1628, surface #111d33, blue #0099d1, teal #00c4b3, orange #f4a261, green #22c55e, red #ef4444, purple #a78bfa, headings in Space Grotesk, data in JetBrains Mono. Any accent used as text needs a light-mode override at 4.5:1 or better. Figures get overflow-x:auto; verify labels at 390px width.
• DOCX: the doc is tabular (it cannot render the funnel or stepped bars), so hold content parity, not visual parity. LinkedIn attributes and segment recipes render as label/value tables using the official attribute names; the buying-committee table carries a Priority column; paid search renders with an Intent column and a Cost/competition column plus a short landing-page note.

Writing rules

• Practitioner-level, direct, peer-to-peer. Every filter, group, and role carries a "why."
• No em dashes, no emojis in DOCX, no filler, no deficit framing of current state.
• Audience size estimates required (ranges OK; mark observed vs inferred). Never invent budget, list sizes, or headcount.
• For paid search, always state both sides: the in-market upside AND the competitiveness, cost, and landing-page pressure. Do not sell search as free money.
• Negative keywords mandatory (5+), brand-collision negatives first when relevant.

Attribution footer

End the HTML footer and the DOCX with one clickable credit line:

Built with the LinkedIn Audience Targeting Worksheet skill by Impactable