Marketing AI Acceleration Playbook

Workflows 13 workflows

Function	Problem	AI Solution	Tool Stack	Success Metrics
Strategy	Campaign briefs take too long and lack real audience insight	Campaign Brief Generator Input target audience, goal, and budget into a structured Claude prompt Claude outputs a full brief: messaging angles, channel mix, content themes, and KPIs Compresses a full day of cross-functional meetings into 10 minutes	Brain Claude.ai Interface NotionGoogle Docs Connector Manual (to start) Data ICP definitionPast campaign results	Efficiency Brief cycle timeDays from request to approved brief Performance Campaign launch velocityCampaigns shipped per quarter
Strategy	Audience segmentation is based on gut feel, not behaviour	Segmentation Analyzer Export CRM contact activity and engagement signals (email opens/clicks, page visits, content downloads, form fills, product usage) into Claude Claude clusters behavioural patterns and proposes 4-6 named segments Each segment gets a distinct messaging strategy and channel recommendation	Brain Claude API Interface Google SheetsNotion Connector Zapier Data HubSpot / SFDCEmail + web analytics	Efficiency Cost per segment modelAnalyst hours saved vs. manual segmentation Performance Segment conversion rate% lift vs. unsegmented baseline
Strategy	Campaigns launch blind - no signal on which accounts are ready to buy	Predictive Intent Engine Pull topic-level surge scores from Bombora (which companies are researching your category) and G2 Buyer Intent (who's reading your reviews and comparing you to competitors) Cross-reference intent signals against ICP firmographics from Clearbit or ZoomInfo (industry, headcount, revenue, tech stack) Claude ranks accounts by combined intent + ICP fit score - campaigns start targeted, not broadcast	Brain Claude API Interface Google SheetsSalesforce Connector Zapier Data Bombora surge reportsG2 Buyer IntentClearbit / ZoomInfo	Efficiency Cost per predicted accountVs. broad-spray campaign spend Performance Intent-to-pipeline rate% of flagged accounts entering pipeline in 60 days
Research	Competitive monitoring is manual, reactive, and always late	Weekly Competitive Digest Zapier triggers a weekly Perplexity search for each competitor (news, product launches, pricing changes, "[competitor] hiring site:linkedin.com") Perplexity handles the web search layer since LinkedIn is publicly indexed by Google even though direct scraping is blocked Search results are piped to Claude, which interprets hiring patterns, identifies strategic signals, and writes a ranked digest Delivered to Slack every Monday - Perplexity finds, Claude thinks	Brain Claude APIPerplexity Interface SlackNotion Connector Zapier Data Competitor URLsPublic job listings	Efficiency Research hours savedHours/week reclaimed from manual monitoring Performance Counter-messaging rate% of signals that trigger a campaign response
Content	Written content is slow - one piece takes days and doesn't repurpose	Text Content Multiplier Feed Claude one approved blog post and brand voice guidelines Outputs 3 LinkedIn variants, 5 tweet/X formats, a short-form email snippet, and a TL;DR for internal Slack One source piece becomes 10 text assets in 15 minutes	Brain Claude.ai Interface NotionBuffer Connector Zapier Data Brand voice guideSource content	Efficiency Cost per asset$ per publish-ready piece vs. agency rate Performance Content output ratioAssets produced per source piece
Content	Visual and video content for IG, TikTok, and Reels is a bottleneck	Visual Content Pipeline Claude generates copy, captions, and creative direction from a campaign brief Output feeds into Figma templates (static posts, carousels, stories) and CapCut (short-form video with auto-captions) Midjourney generates custom imagery when stock won't cut it One brief produces a full week of visual assets across IG, TikTok, and LinkedIn	Brain Claude APIMidjourney Interface FigmaCapCutCanva Connector Zapier Data Brand kitCampaign briefAsset library	Efficiency Design hours per postTime from brief to publish-ready visual Performance Social engagement rateAvg likes + shares + saves per post
Content	SEO content loses relevance before it ranks	Dynamic SEO Pipeline Live SERP (Search Engine Results Page) webhook triggers Claude when a tracked keyword shifts rank Claude identifies the content gap, rewrites or updates the post Pushes a draft for human review - reacts to SERP changes in hours, not weeks	Brain Claude API Interface Google DocsSurfer SEO Connector Zapier Data Semrush SERP feedKeyword tracker	Efficiency Update cycle timeHours from rank drop to updated draft Performance Organic rank positionAvg position for tracked keywords
Campaign	Email personalisation doesn't scale beyond first name	Segment-Level Email Personaliser Define 4-5 audience segments in a structured prompt Claude generates distinct email variants per segment from a single core message Each gets a tailored subject line, opening hook, and CTA Pushed into Marketo or HubSpot as separate versions	Brain Claude API Interface MarketoHubSpot Connector Zapier Data Segment definitionsCRM tags	Efficiency Cost per email variant$ vs. copywriter rate per version Performance CTR by segmentVs. generic single-version baseline
Campaign	Ad copy testing is too slow - teams ship 3 variants when they need 20	Ad Copy Factory Input product, audience, and objective Claude generates 15+ variants across headline, body, and CTA combinations Scored against historical CTR patterns via a second Claude prompt Top performers pushed into Google or Meta Ads via API	Brain Claude API Interface Google AdsMeta Ads Connector Zapier Data Past ad performanceAudience profile	Efficiency Copy output speedVariants per brief per hour Performance Ad CTR liftAI vs. human variant win rate
Campaign	No proof that AI creative outperforms human creative	Champion-Challenger Framework Every campaign runs a structured A/B split: human control vs. AI challenger Results feed a live scorecard tracking win rates by channel, segment, and message type Over 90 days, builds the statistical evidence base for further AI investment	Brain Claude API Interface Google SheetsNotion Connector Zapier Data Campaign exportsA/B test results	Efficiency Test setup timeHours to stand up a challenger variant Performance AI win rate% of tests where AI beats human control
Demand Gen	Lead nurture sequences are generic and bleed MQLs	Behaviour-Triggered Nurture Writer When a lead engages with specific content (pricing page, case study, webinar), a Zapier trigger fires Claude generates a 3-email follow-up tailored to that intent signal and buying stage Different sequences per signal, auto-enrolled in Marketo	Brain Claude API Interface MarketoHubSpot Connector Zapier Data Lead behaviour eventsContent taxonomy	Efficiency Cost per MQL$ per qualified lead via AI sequences Performance MQL-to-SQL rate% of nurtured leads accepted by sales
Analytics	Performance data never feeds back to improve the next campaign	Closed-Loop Performance Digest Zapier pulls weekly CSV exports from GA4 (via Data API), HubSpot, and Google/Meta Ads into a single Google Sheet A second Zap sends the consolidated data to Claude API Claude writes a plain-English summary: what moved, why, and one recommended action Insights auto-update the Strategy prompt library so the next brief is smarter ↵ Feeds back to Strategy prompts	Brain Claude API Interface SlackNotion Connector Zapier Data GA4 Data APIHubSpot APIAds API exports	Efficiency Reporting time savedHours/week reclaimed Performance Insight action rate% of recommendations acted on in 7 days
Governance	AI content ships without legal, brand, or data safety checks	HITL Checkpoint Layer Every AI output above a defined risk threshold (public copy, customer data, regulated claims) routes to a mandatory Notion review queue Slack approval flow notifies the reviewer and tracks turnaround time A separate PII-scrubbing prompt strips identifiable data from CRM exports before they touch any external LLM ⚠ HITL required before external publish	Brain Claude API Interface Notion queueSlack approval Connector Zapier Data Brand guidelinesLegal taxonomyPII rules	Efficiency Review turnaroundHours from AI output to approved status Performance Brand incident rateViolations per 100 AI outputs

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