LinkedIn Campaign Manager B2B Ad Plan
Plan a B2B ad campaign on LinkedIn with audience criteria, offer, ad formats, budget maths and a lead follow-up process.
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[VERIFY] is an editorial flag, not a blank to fill. Wherever the prompt shows [VERIFY], check that item against a reliable source before you use it.
Help me plan a B2B advertising campaign on LinkedIn. What we sell and typical deal value: [OFFER_AND_DEAL_VALUE]. Job titles, industries and company sizes we target: [TARGET_ACCOUNTS_AND_ROLES]. Budget and timeline: [BUDGET_AND_TIMELINE]. Content or offers available (guide, demo, webinar): [AVAILABLE_OFFERS]. How leads are followed up and by whom: [LEAD_FOLLOW_UP]. Provide: an audience definition with inclusion and exclusion rules and a check that the audience is neither too narrow nor too broad, with the minimum and maximum sizes left for me to confirm in the tool [VERIFY]; an offer and messaging matrix by role with the columns Role, Pain point, Hook, Proof needed, Call to action; ad format recommendations with reasons [VERIFY formats and specs]; two sample ads each for text, headline and call to action; and a lead handling plan with response time targets and a first follow-up email under 100 words. Then model the funnel: budget divided by an assumed cost per click gives clicks; clicks times landing page conversion gives leads; leads times qualification rate times close rate times deal value gives expected revenue; show every step and compare it with the budget. Label every rate as an assumption to be replaced with actual data, and add a sensitivity row for half the conversion rate. Interface names, bidding options, minimum budgets and policies change, so mark them [VERIFY]. Do not invent benchmarks, costs or targeting options. Follow platform advertising rules and local privacy and marketing consent rules. Add a worked example with invented figures: 6,000 budget, 14 cost per click, 5 percent conversion, 20 percent qualified, 10 percent close, and a deal worth 8,000.
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See an example result (fictional data)
Invented figures, with every rate an assumption. Clicks: 6,000 / 14 = 428.6, about 429. Leads: 429 x 0.05 = 21.4, about 21. Qualified: 21 x 0.20 = 4.2. Deals: 4.2 x 0.10 = 0.42. Expected revenue: 0.42 x 8,000 = 3,360, against a spend of 6,000. Reading: on these numbers the campaign loses money in one pass, so the question is whether sales cycles, repeat purchases or a lower cost per click change the picture. Sensitivity: at half the conversion rate (2.5 percent), leads fall to about 10.7 and revenue to about 1,680. Test with a small budget first and replace each assumption with figures from the account.
Illustrative only, made-up data. Your results will differ and must be reviewed.