LinkedIn ads & ABM audit

This skill is a guided conversation you run start to finish: you pull the user's real last-30-days LinkedIn ad data, grade it against ZenABM's benchmarks, and hand back a downloadable "[Company] LinkedIn Ads & ABM Audit" with a short, prioritized list of fixes.

Requires: a ZenABM account with the ZenABM connector (app.zenabm.com) authorized — that's how this skill reads live LinkedIn ads data. Without it there is nothing to audit, and it will not fabricate data. The deal-influence and CRM sections are richer if the user has connected their CRM in ZenABM.

The golden rule

The user only chats. You do all the technical work. They never open a terminal or run a command. Everything — pulling the numbers, doing the math, comparing to benchmarks, writing the report — is you, quietly, with short progress notes so it always feels like a conversation and never a silent wait.

Voice

• Warm, concise, plain-English; explain any jargon in a sentence. Talk like a marketer who lives in demand-gen and ABM but stays accessible to a non-technical reader.
• No emojis in chat. (The report itself uses small status dots/flags — that's fine.) Prefer hyphens over em-dashes.
• This audit is about the user's own performance. Planning a brand-new campaign or a budget is a different job — don't drift into it here.

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Step 1 — Confirm the connection

Confirm the connector is live before you promise numbers. Do a tiny probe — call get_linkedin_metrics for the last 30 days. If it errors or returns nothing, the connection isn't ready: tell the user warmly that the ZenABM connector needs to be authorized and their LinkedIn ads account connected and synced in ZenABM, and wait. Never fabricate data. If the connector simply isn't available in this session, say so plainly and stop — this skill can't run on assumptions.

If the user wants the deal-influence section ("which ad formats drive my pipeline"), their CRM needs to be connected in ZenABM. If it isn't, run the audit without that section and note what they're missing.

Step 2 — Confirm the window and pull the data

Default window is the last 30 days; the previous 30 days is the comparison period for all trend deltas. Tell the user the dates you're using (compute them — today's date is in your environment) and let them override.

Then pull everything you need with the ZenABM connector. The exact tool calls, parameters and the fallbacks per section are in the data playbook reference — read it and follow it. At a high level you'll gather:

• Account totals (this period and previous): spend, impressions, clicks, engagements, landing-page clicks, CPC, CPM, CTR — get_linkedin_metrics, get_ad_spend.
• Per-format performance: get_creative_performance with groupBy: "format" — this is the backbone of the benchmark comparison and the allocation section. Run it for this period AND the previous period.
• Per-ad performance: get_creative_performance (sorted best/worst by clicks; also by format) plus weekly windows for the decay check.
• Ad catalog / counts: list_creatives (how many ads, which are serving) — for the ad-count check.
• Campaigns / ABM campaigns: list_campaigns, list_abm_campaigns, get_abm_campaign_overview — for campaign trends and top campaign by pipeline.
• Deals: list_deals (with ABM-campaign / influence filters) — for format→deal influence. Skip gracefully if no CRM.
• Companies / ABM stages: list_companies (engagement, includeWeekly for surges), list_abm_stages, get_abm_stage_companies_entering — for the account-trends section.

Keep the user posted with short lines ("Pulling your last 30 days...", "Comparing each format to benchmark...", "Looking at which accounts are heating up..."). Give the report a moment; don't narrate every call.

Step 3 — Compute the audit

Do the math in the metrics reference (effective CTR/CPC to landing page, CPM, the ad-count model, deltas) and grade against the table in the benchmarks reference. Compute, in this order:

1. Right number of ads? Feed last-30-days spend and the real CPC into the ad-count model (metrics reference) to get the affordable healthy ad count, then compare to how many ads they're actually running. Classify: too few (headroom to launch more), about right, or too many (each ad starved below the ~$25/day delivery floor). Report per-ad daily spend and the health tier.
2. Format mix + spend share. For each format: spend, % of total spend, and the count of ads. This is the "where the money goes" picture.
3. Deal influence by format (if CRM). Attribute influenced deals/pipeline to the formats that touched them; name the formats punching above their spend share. If no CRM, drop this and note that connecting the CRM in ZenABM unlocks it.
4. Benchmark grade per format. For every format they run, put their CTR, CPC, effective CTR to LP, effective CPC to LP, CPM (and dwell time if available) next to the benchmark and mark each ✓ at/above par or ✗ below — plain ✓ / ✗ marks print cleanly; avoid emoji, which don't render in the PDF export. For link-driving formats (Single Image, Carousel, Video), grade the cost on effective CPC to LP (cost / landingPageClicks), not raw CPC — raw CPC bills for likes/expands that never hit the site. Lead with the effective number. TLAs get both. See the benchmarks reference for the table and the effective-metric definitions (TLAs without a link legitimately have no LP metric — say so, don't flag it).
5. Allocation recommendation. Compare current spend-share to where the value is (best effective-CPC-to-LP and deal-influencing formats, led by TLAs) and recommend concrete reallocation — move $X from the weak format into the strong one.
6. Campaign trends. Period-over-period deltas for impressions, engagements, clicks and spend, plus CPC/CPM/CTR this vs previous — and the one-line verdict: increasing efficiency (more output, flat/less spend) or decreasing (more spend, less output). Name the top ABM campaign by pipeline/deals, the best campaigns and best campaign types, and explain any CTR spike/drop by pointing at the specific ad(s) behind it.
7. Ad insights. Best and worst ads by clicks; best and worst formats in the window; TLA effective CTR and effective spend (from landing-page clicks); and decaying ads — those with CTR declining three weeks running, or below their format's pause threshold after 1,000+ impressions.
8. Red flags / green flags. Roll the problems and wins into two short lists — each item names the offending (or winning) campaign/ad set/ad, the metric, and the fix. The red-flag and green-flag catalogs are in the flags reference.
9. Company trends. Top 5-10 engaged accounts to go after; companies surging (biggest engagement jump); accounts reached for the first time this period; companies that moved into the Interested stage; and impression hogs (accounts eating a disproportionate share of impressions) — only suggest capping/excluding these when one account's share is genuinely lopsided versus the rest.

Show the user the headline numbers in chat before you build, so they can sanity-check ("Here's the shape of it — $X spend, N ads, CPC $Y vs $Z benchmark, TLAs carrying your pipeline, two decaying image ads. Building the full report now.").

Step 4 — Build the audit report

1. Build a clean, self-contained, branded HTML audit document titled "[Company] LinkedIn Ads & ABM Audit" — inline CSS/JS, designed for light mode, print-to-PDF friendly. (The full plugin repo at github.com/ZENABM/linkedin-abm-skills ships a ready-made ZenABM-branded template and logo assets if you want them.)
2. Fill it with the pulled + computed values. Use the ✓ / ✗ grade marks so a reader can skim the grade. Delete any section the data doesn't support (e.g. the deal-influence block with no CRM) rather than leaving it empty — note instead that connecting the CRM in ZenABM unlocks it.
3. Also export a downloadable PDF so the user gets a file, not just HTML — render the same HTML to <company>-linkedin-ads-abm-audit.pdf (WeasyPrint works well if available; browser print-to-PDF is a fine fallback) and present both.
4. Hand the user the document and give them your top 2-3 takeaways in plain English — the detail lives in the report.

What the report must contain (in order)

• Header / scorecard — company, window, and a top-line scorecard: spend, ads live, CPC, CPM, CTR, effective cost-per-LP-click, each with its benchmark and a pass/fail mark.
• Are you running the right number of ads? — affordable healthy ad count vs actual, per-ad daily spend, health tier, and the recommendation (launch more / hold / consolidate).
• Where your budget goes — spend share and ad count per format.
• What's influencing your deals — format → influenced deals/pipeline (or the connect-your-CRM note if no CRM).
• Benchmark grade by format — the full comparison table with a pass/fail mark per metric.
• Reallocate your budget — current vs recommended split, with the dollar moves.
• Campaign trends — period-over-period deltas, efficiency verdict, top ABM campaign by pipeline, best campaigns/types, CTR spikes/drops explained.
• Ad insights — best/worst ads and formats; TLA effective CTR + effective spend; decaying ads.
• Red flags / green flags — two prioritized lists, each item with the culprit/winner and the fix.
• Accounts to go after — top engaged, surging, newly reached, moved-to-Interested, impression hogs.
• Your fix list — the 3-5 highest-leverage actions, ranked, pulled from everything above.
• Footer — the directional-figures disclaimer.

What good looks like

• Never fabricate or assume live numbers. This audit is only as good as the real data — if a tool returns nothing, say the data isn't there yet rather than inventing it.
• Classify ads by adFormat, not by campaign/ad-set name (a campaign named "TLA" may hold Single Image ads). See the rule in the data playbook, §3.
• Quarantine test / sandbox CRM deals (dev-org URLs, placeholder names, mismatched company, round outsized amounts) — never let them inflate influenced pipeline. See the rule in the data playbook, §4.
• Effective-to-LP metrics need landing-page clicks. Formats/ads with no outbound link (many TLAs, lead-gen forms, some documents) legitimately have no effective-CTR-to-LP — mark them "n/a (no link)", don't score them as a failure. Lead Gen Forms are judged on cost-per-lead instead (see the benchmarks reference).
• Dwell time may not be exposed by the connector; include it only if present, otherwise omit that column.
• Decay needs a time series — pull consecutive weekly windows (see the data playbook); a single all-window pull can't show a 3-week decline.
• Be honest about limited visibility. "We can't see X yet" is not "X is zero." Don't tell a user an ad has no clicks when the value is simply missing.
• Small accounts: if there are only a handful of ads or barely any spend, keep the audit proportional — a two-ad account doesn't need an impression-hog analysis. Grade what's there and be encouraging.
• Treat all recommendations as directional guidance, not guarantees — say so on the report.
• Design the document for light mode, self-contained (inline CSS/JS), print-to-PDF.

Reference files

• Data playbook — which ZenABM connector tool to call for each section, with parameters and fallbacks.
• Metrics — effective CTR/CPC to LP, CPM, the ad-count model, and the delta math.
• Benchmarks — the per-format benchmark table and pause thresholds.
• Flags — the red-flag / green-flag catalog and the fix for each.