Webinar Recap: Winning GTM Plays in the Age of AI with Mica Oliveira & José Velez
Steal the playbook top teams are using to fill their sales pipeline
José (Founder, Reach) and Mica (Co-founder, Amplemarket) broke down the exact system they use to engineer demand using AI search + signal-based outbound. Not theory, high-intent pipeline plays that turn on in under 5 minutes, no integrations, no IT tickets.
The main theme stayed clear throughout: marketing teams need to help Large Language Models (LLMs) understand, retrieve, and accurately recommend their brand. Everything below is structured around that.
Top Takeaways
AI Search is the next major GTM channel.
LLMs are influencing buying decisions before AND after a prospect lands on your site. ColdIQ added $506K ARR in 4 months from SEO + AEO. Indie Campers 13x revenue from AI search in 8 months. Carro closed multiple 7-figure deals sourced through ChatGPT.
How AI engines decide who to recommend.
Different reasoning, different signals than Google. Citations cluster around source convergence — listicles, review sites, niche publishers, and community threads where buyers actually hang out.
Engineer the recommendation, don't hope for it.
A clear blueprint with the right artifacts and buyer-journey research. The formats AI pulls from (passages, structured data, FAQ schema, comparison tables) ensure LLMs can read and cite your content.
Convert visibility to pipeline.
AI Search → Visit → Retargeting → Demo. Inbound-led outbound plays the moment a high-intent visitor lands. Visitor identification, Clay-powered enrichment, Amplemarket signals.
Measure what predicts revenue.
Leading indicators of AI search success that correlate with pipeline — not raw referral traffic. ROI model comparing AISO to SEO, paid, outbound, and content.
Best Practices and Key Learnings
Why AI search is becoming the next major GTM channel
LLMs are reshaping how people discover, evaluate, and buy products and services.
Search is evolving, not dying. AI is now 56% the size of search; search-related sessions of AI + Search up +26% YoY.
48% of prompts to LLMs are new intents (asking, expressing, doing) work that never happened on Google.
AI search has gone from a trend to a real pipeline channel: ColdIQ $506K ARR in 4 months, Indie Campers 13x AI-search revenue in 8 months, Carro closed Tucker Carlson + Revolut through ChatGPT.
How AI systems interpret and recommend solutions
The core differences between how Google ranks and how LLMs reason.
LLMs build answers through comparisons, integrations, pricing checks, compliance filters, and ICP-specific needs, not single keyword matches.
When a buyer asks an AI tool for recommendations, the LLM generates sub-queries to validate fit. Your content needs to answer those sub-queries directly.
Source convergence matters more than any single page. The model trusts when it sees the same claim across listicles + review sites + niche publishers + Reddit.
How to engineer a plan that gets AI to cite you
A clear blueprint that compounds monthly.
The 5G framework: Get Findable (sitemap/robots/indexing) → Get Scannable (schema, page experience) → Get Visible (keyword + prompt research, on-page SEO, earned mentions) → Get Scalable (programmatic SEO) → Get Measurable (analytics, scorecards).
Write pages for passage retrieval: short, declarative, self-contained paragraphs that LLMs can extract and cite. Each paragraph as a standalone answer.
Map content to the reasoning journey: audit core pages around buyer dealbreakers (integrations, pricing, compliance, company fit). Add comparison, alternatives, and "who it's for" content.
Turn AI visibility into traffic, leads, and pipeline
Go from recommendation to revenue.
AI Search → Visit → Retargeting → Demo flow. Identify the prospect on the site, enrich, drop them into the right sequence the same day.
Inbound-led outbound: Amplemarket signal-based plays that trigger off a real buying signal (job posting, funding announcement, tech-stack change), not a static list.
Buyer intent personalization: dynamic site content based on the prospect's ICP, with retargeting ads that follow the prompt cohort they arrived from.
GTM workflows that convert
Real examples of the signal-based plays that activate high-intent buyers.
Website visitor identification with Clay + RB2B + Reach attribution.
Retargeting based on prompt cohort (visitors from "best X" prompts get different retargeting than visitors from "X vs Y" prompts).
Amplemarket automations that activate the moment a high-intent thread lands — without IT, without integrations, without 6-month builds.
Measure what matters
Leading indicators of AI search success that actually correlate with revenue.
Track: AI share of voice by prompt cohort, citation share by source type, brand search volume, "How did you hear about us?" attribution.
Ignore: raw referral traffic from AI engines (will always look small), absolute citation counts (your competitor moved too), single-prompt wins.
ROI model: AISO vs SEO vs paid vs outbound vs content — head-to-head on pipeline generated per dollar.
Full transcript
How Reach helps teams act on these insights
The same five-pillar system runs across every Reach customer. Different categories, different starting points, same compound curve. Reach's platform pairs research, scorecards and action plans with senior strategists who execute the work — so AI search visibility translates to pipeline within months, not years.
