Marketing Operations Checklist

Brief should name the business objective, primary KPI, target persona, ICP fit criteria, offer, and success threshold. The marketing manager owns the brief; reviewers add edits in-doc rather than via Slack DMs so the approval trail is timestamped.

For B2B, pull the account list from CRM or 6sense / Demandbase intent data and confirm fit criteria (industry, employee count, tech stack). For B2C, define the audience in the MAP — Klaviyo / Iterable / Braze segment with explicit inclusion and suppression rules.

Allocate spend across paid search, paid social, display, email, and organic. Document expected CPA and ROAS by channel so post-launch pacing decisions have a baseline. Get finance sign-off before any media is committed.

Map each asset to a funnel stage (TOFU / MOFU / BOFU), owner, draft date, and publish date. Asana, Airtable, or Notion are typical homes; the source-of-truth calendar shouldn't live in someone's local file.

Copywriter drafts the messaging house — value prop, supporting points, proof points — then resizes it for ad copy, email subject lines, landing-page hero, and social captions. Voice should match the brand book; flag any unverified claims for fact-check.

Designer produces creative in Figma against the locked-in dimensions for each placement (1200×630 for social share, 1080×1350 IG feed, 1200×628 LinkedIn, etc.). Upload finals to the DAM (Bynder / Brandfolder / Frontify) with proper tagging — no rogue Dropbox links.

Brand reviews voice / visual identity; legal reviews claims, comparative statements, and any required disclaimers. Capture approval in the project tool with a timestamp — Slack DMs are not an audit trail. For regulated verticals (health, financial services), build the substantiation file alongside the asset.

Use GTM Preview and GA4 DebugView to confirm the conversion event fires on actual form submit — not on email-blur or page-load. Mis-mapped events inflate conversions 5x and distort downstream budget allocation. Verify pixel firing on Meta, LinkedIn, and Google Ads test events.

Send through Litmus or Email on Acid for major-client rendering (Outlook desktop is the usual breakage point). Verify SPF, DKIM, and DMARC alignment on the sending domain. Confirm the unsubscribe link, physical mailing address, and consent-basis language meet CAN-SPAM and GDPR / CASL where audiences overlap.

Confirm the CMP (OneTrust, Cookiebot, Didomi) blocks Meta Pixel, LinkedIn Insight Tag, and other marketing tags until consent is granted. A banner that promises consent-first while the page fires pixels at load is the most common privacy-promise gap on launch day.

Stage paid budgets at 50% of plan for the first 48 hours so you can pull back fast if pacing or creative breaks. The performance marketer launches Google Ads, Meta, and LinkedIn within the same hour so attribution windows align.

Queue posts in Sprout Social, Hootsuite, or Buffer per the locked content calendar. Every link uses the campaign UTM convention from planning — no hand-typed parameters at post time.

Demand-gen manager reviews spend pacing, CPC, CPA, and early conversion data against the planned thresholds. Flag any channel running over 150% of target CPA for creative or audience adjustment.

Only triggered when the 72-hour review flags underperformance. Cut bids on high-CPA placements, swap underperforming creative variants, or tighten audience exclusions. Document each change in the campaign log so the post-mortem can attribute lift correctly.

Consolidate GA4, Google Ads, Meta, LinkedIn, and email-platform data into the reporting view (Looker Studio, Tableau, or the marketing-ops warehouse). Reconcile platform-reported conversions against CRM-attributed pipeline before publishing numbers.

Compare actuals to the primary KPI and target captured in the brief. Note attribution caveats — last-touch vs. multi-touch will tell different stories, especially for ABM campaigns where the assist-touches drive most of the influenced pipeline.

Only triggered when the campaign missed its KPI. Walk the funnel — impressions, CTR, landing conversion rate, MQL→SQL, SQL→opp — and isolate where the drop-off happened. The fix is rarely "more budget"; it's usually a specific stage with a fixable problem.

Capture what worked, what didn't, and which audiences / creative / offers to retire or scale. Update the campaign playbook in Notion or Confluence so the next campaign starts from this baseline rather than rediscovering the same lessons.