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Cody Schneider

@codyschneider • 66,799 subscribers

follow to learn GTM + Marketing Engineering to grow your business building @graphed with @maxchehab

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my team didn't want me to give this away for free. But I'm going to do it anyway it's the SEO & AI search dashboard I built in Claude Code it connects to your Google Analytics (GA4) and Google Search Console and Claude Code builds it in 5 minutes and I made a Notion document and a skill file so you can build this in Claude Code yourself in literally minutes the dashboard has three tabs: 1. AI Search - How much traffic is coming from ChatGPT, Perplexity, and Gemini ETC. It aggregates the GA4 data and gives single number 2. Paid ads - which keywords rank top 3 for but still pay for ads on, you should cut these to save budget 3. Organic overview - sessions, conversions, top landing pages, demographics. The single view for what is working I built this because this is how I drive our SEO and AEO forward it gives me the insights I need to allocate budget and prioritize what content to work on next I decided to give it away because most companies have no idea AI search is already sending them traffic like this post and comment "AEOdashboard" and I'll send it over

my team didn't want me to give this away for free. But I'm going to do it anyway it's the SEO & AI search dashboard I built in Claude Code it connects to your Google Analytics (GA4) and Google Search Console and Claude Code builds it in 5 minutes and I made a Notion document and a skill file so you can build this in Claude Code yourself in literally minutes the dashboard has three tabs: 1. AI Search - How much traffic is coming from ChatGPT, Perplexity, and Gemini ETC. It aggregates the GA4 data and gives single number 2. Paid ads - which keywords rank top 3 for but still pay for ads on, you should cut these to save budget 3. Organic overview - sessions, conversions, top landing pages, demographics. The single view for what is working I built this because this is how I drive our SEO and AEO forward it gives me the insights I need to allocate budget and prioritize what content to work on next I decided to give it away because most companies have no idea AI search is already sending them traffic like this post and comment "AEOdashboard" and I'll send it over

80,045 views

last week a forward deployed engineer built an AI agent that extracts linkedin post engagers and finds their emails for cold outbound tons of people asked for this so over the weekend this FDE built an app where you drop in a post URL, it extracts the engagers profiles, and gives you email leads if their are emails available if you want free credits comment "engager" and I'll send you some

last week a forward deployed engineer built an AI agent that extracts linkedin post engagers and finds their emails for cold outbound tons of people asked for this so over the weekend this FDE built an app where you drop in a post URL, it extracts the engagers profiles, and gives you email leads if their are emails available if you want free credits comment "engager" and I'll send you some

10,814 views

ai script ai avatar product video background avatar foreground tiktok cloud 100 accounts 3M views a month signups you want this form below

ai script ai avatar product video background avatar foreground tiktok cloud 100 accounts 3M views a month signups you want this form below

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new live class for you how to build facebook ads AI agent you'll learn strategy - andromeda killed interest targeting — the creative + landing page *are* the targeting signal now, so the play is volume of distinct personas/angles rather than audience selection - loop is: publish many → let meta prospect → trim losers → promote winners into a winners campaign → remix winners back into testing - structure: testing campaign with multiple adsets, 5 ads per adset fighting for budget; winners graduate to a separate campaign, watched for fatigue - winners campaign can optimize on a deeper event than the testing campaign (signup for testing, demo/payment for winners) - agent entropy is the failure mode — left alone it regenerates the same creative; new dna comes from competitor ad libraries and viralio-scraped trending short-form tracking - gtm as the single tag + custom datalayer events for conversion actions - start upfunnel, work down as conversion volume allows — you can't train on payment events without enough volume - cap it at ~5 conversion events; more is noise - server-side capi for real-time lead scoring: enrich on submit (similarweb traffic via apify, headcount, crm, google review velocity, zip), agent scores 1–10, only 6+ fires back. solves lead quality without waiting out a 4-week sales cycle. build the scoring model off the shape of existing closed-won customers - delayed closed-won-based conversion feedback (hubspot deep funnel) works for some people but the learning cycle is too slow infrastructure - fb marketing api for **writes only** — creative upload and account management. never for analysis; hammering it risks a tos-based account ban, plus truncation/pagination/hallucination problems - analysis comes from the warehouse: airbyte → clickhouse, agent queries that. supabase/postgres won't hold up — 100m rows is minutes vs milliseconds - access via developer app + system user token (doesn't expire), not a public app submission - fb mcp exists but exposes only a handful of endpoints and breaks at scale; there's a new cli, untested - agent = software + thinking loop + live data stream; deploy to railway or similar creative - reddit scrape (xai api) for pain points and desired outcomes → source language for hooks and scripts - statics: kie ai → nano banana, fed competitor ad library refs + brand style guide - video: heygen public ugc avatars + elevenlabs voices (better than heygen native), seedance for more expensive/higher-fidelity once a format wins - cheap models for testing, expensive models for scaling proven winners numbers / positioning - financial advisor client: $100 → $53 cpl over four weeks - minimums: ~$30/day local, ~$100/day national, two-week read - diy timeline: ~2 weeks to something usable, 4–6 weeks to enterprise-ready — the pain is the pipeline/warehouse, not the agent - ad platforms' own automation has misaligned incentives (they want spend, you want cheap cpa)

Cody Schneider

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