Explore AI workflows built by marketing experts

Automated Custom Reporting and Dashboards

Using the Claude plugin in Excel, performance marketers can turn hours of Monday-morning reporting into a few minutes of automated dashboarding — pulling from sources like GA-4, BigQuery, Google Ads, or Meta Ads. The same approach applies to any channel-level or overall reporting workflow, freeing up weekly time that compounds quickly across a team.

Multi-Topic Marketing Research Agent

SignalSweep sweeps 126+ sources — Reddit, X, Amazon, SEC filings, ad libraries, patents, app reviews, and more — and synthesizes them into a source-cited intelligence brief in about 30 minutes for a few dollars in API costs, replacing what typically takes 40-80 hours of analyst and agency time each month. Deployed as a Python CLI on your own infrastructure with your own credentials, it pays for itself by Week 2 and compounds from there, since each new research topic is marginal effort rather than a new project.

AI Conversion Rate Optimizing Agent

Feed in a landing page URL, answer three quick questions, and get back a set of behavioral-science-backed recommendations for improving conversions. Clients who act on the suggestions typically see a 3–15% conversion lift without increasing their ad spend.

Google Ads Campaign Launch Automation

Turn a landing page into a fully built Google Ads campaign — complete with keywords and behaviorally informed ad copy — in minutes instead of the full day it typically takes. The result is faster time to market with stronger ads, since copy is grounded in actual landing page content and behavioral science triggers rather than starting from scratch.

Media Mix Model Budget Allocation Analysis

A structured approach to building and operationalizing a Media Mix Model that captures the full picture of marketing performance — including non-click channels like TV — and delivers actionable incrementality insights and budget recommendations. Companies that act on MMM outputs routinely unlock 5–15% revenue gains simply by reallocating existing budgets across channels.

AI Marketing Advisor

Reviews how your team is currently using AI across marketing functions — tools, workflows, and coverage gaps — and delivers a prioritized list of the highest-impact opportunities to act on next. You walk away with a clear map of where you are and a concrete starting point, not a strategy doc.

AI Driven Customer Segmentation

By running K-means clustering through Claude in Excel, you can segment your entire customer database and calculate LTVs by segment in roughly half the time it would take manually. The resulting segments give you a clear foundation for tailoring messaging, ads, and promotions by customer type — a practice that can drive 10%+ revenue gains for teams not already segmenting.

Creative Performance Analysis and Content Brief Generation

A single automated loop handles creative strategy insights, content briefing, and AI-generated iterations—consolidating what typically requires three separate roles into one and saving roughly 10+ hours a week and $10k–$100k a year. It runs alongside your existing processes, not instead of them, so you get faster cycles from insight to action while improving creative quality and cutting costs at the same time.

Automated Weekly Social Media Content Engine

A structured 4-week content cycle rotates 16 post types across awareness, consideration, conversion, and post-purchase stages, delivering five ready-to-review posts per week across Facebook, Instagram, and Google Business — cutting content creation from 10–15 hours a month to under two. AI drafts copy, hashtags, and Notion calendar entries in minutes, so even teams without dedicated marketing staff can maintain a consistent publishing cadence with just a quick human review before anything goes live.

Automated Branded Deck Creation

By combining reusable skills like voice guidelines and presentation standards, any team member can generate on-brand, ready-to-share decks in about 15 minutes instead of the three-plus hours it typically takes to build and format them manually. Once the skills are set up with your company's specific inputs, the output stays consistent across every team — removing the usual back-and-forth on formatting, tone, and compliance.

GenAI for Product and Lifestyle Content

Cut long content product lead times and expensive UGC or studio shoots by 10x. Run an AI-based creative strategy and content creation process.

Personalized Marketing Newsletters for Top Contacts

An automated workflow pulls the latest technology and marketing articles via RSS feeds, uses AI to evaluate them, and assembles a personalized newsletter tailored to each contact's role, industry, and experience — delivering relevant marketing intel to top contacts without manual effort. The system handles quality checks, email formatting, and sending through HubSpot, while keeping contact profiles updated, replacing what would otherwise be hours of manual research and writing per recipient.

Data Driven Attribution Model

Walk through building a data-driven attribution model directly in Excel using Claude and the Shapley Value algorithm, starting from click data pulled from your data warehouse. Compared to rules-based approaches like last click or first click, this method produces more actionable budget allocation insights and can drive an estimated 5% revenue lift.

Amazon Product Launch Research and Validation

A structured, agent-powered system runs opportunity research, product validation, and go-to-market planning for Amazon launches in parallel — collapsing 2–4 weeks of analyst work into 3–5 days and delivering a launch-ready package (scored opportunity, unit economics, listing copy, PPC architecture, external-traffic plan) that cuts the $30K–$100K in avoidable launch mistakes by 50–80%. The result is fewer dead SKUs, faster time to revenue, and scoring discipline that can redirect $100K–$500K per year away from low-EV bets toward higher-return launches.

Automated Inbound Lead Routing by Criteria

Incoming leads are automatically matched to the right PS team member based on business rules, capacity constraints, and historical assignment patterns — saving roughly 15 minutes of manual routing work per lead. The system also improves assignment quality over time by learning from historical patterns, so leads consistently reach the best-fit person without anyone managing the process by hand.

Automated AI Skill Building and Validation

A structured framework for building, finding, and refining AI skills that cuts build time from 3–5 iterations to 1–2 and reduces context window usage by 64%, turning what's usually ad-hoc prompting into repeatable engineering. The methodology produces production-grade skills from the first deploy, with built-in validation that catches failures before they cost your team time mid-session.

Diminishing Returns Analysis for Ad Spend

By fitting response curves to your ad data, CurveLab pinpoints the exact spend level where each incremental dollar stops paying for itself — typically revealing 15–35% of budget sitting beyond the efficient frontier, which translates to hundreds of thousands in recovered spend per year. It runs in-browser in seconds per experiment, replacing months of manual analysis or six-figure MMM engagements with an afternoon's work.

Google Search Ads Performance Review Automation

A five-layer system architecture gives Claude everything it needs to run Google Search Ads end to end — parsing raw CSV exports, classifying keywords by profitability, flagging negative search terms, cross-referencing with Amplitude data, and verifying that past recommendations were actually applied — cutting roughly 90% of routine campaign operations while feeding a persistent knowledge base that sharpens guardrails and QA checks with every run. The built-in feedback loop ties each optimization cycle back to real performance data, which drove approximately 40% higher ROAS by catching waste faster and compounding small improvements over time.

Automated Social Media Brand Sentiment Tracking

A lightweight, AI-powered system that monitors brand mentions across social platforms, scores daily sentiment, and gives you a clear read on how people feel about your brand — without paying for bloated social listening tools full of features you'll never use. By bringing brand monitoring in house with a bespoke setup that fits your actual needs, you can save thousands of dollars a month while getting cleaner, more relevant insight.

Automated Monthly Marketing Reports in PPTX

Pull performance data from your social reporting platform and CRM, feed it to Claude, and get back a complete narrative draft with performance summary, data flags, cost-per-lead calculations, and a hold/increase/decrease spend recommendation — cutting per-account reporting from 6–8 hours to under 90 minutes while ensuring every report follows a consistent structure regardless of team bandwidth. Your team reviews and delivers a client-ready PPTX on time, with spend decisions confirmed by deadline and no follow-up needed.

AI-Powered Social Ad Creative Generator at Scale

A templatized workflow lets you feed in variables — product SKUs, creator stills, pain points, brand guidelines — and use AI to generate dozens of ad variations from a single creative asset, cutting production time from hours to minutes. It's especially useful for e-commerce and creator-driven brands that need to A/B test backgrounds, copy, and specs without burning designer cycles on every variant.

AI-Powered BI Stack

A fully AI-built BI stack — from automated data ingestion and modeling to dashboards and a plain-English chatbot — that replaces 10–15 hours of weekly ad-hoc analyst work and delivers self-serve answers in seconds instead of 30–60 minutes. A single modeled data layer eliminates conflicting numbers across reports, letting teams shift campaign optimization decisions from weekly cycles to same-day.