Generating 100,000s of conversions monthly via SEO & AI search (AEO) for B2B SaaS companies like @meetgranola, @Instantlyai, @Composio & others.

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Just asked Tom, CMO at @incident_io (Series B), what it's actually been like to work with us on SEO and AEO. The results: in the first four months organic meetings booked grew 22%, their AI share of voice is up 62% and top 3 Google rankings are up 97%. Tom runs a lean marketing team, so he needed a partner that could own the work and keep adapting as AI search changed. As he put it himself: "it's not as easy as publishing more content...if you want to just go buy a tool like AirOps and churn out a bunch stuff, great, go for it...Liam and team will help you understand the strategy inside of it, not just the tactical execution." Here's what that strategy looked like: (1) Turned "we're probably behind" into a competitive map We tracked incident against competitors across ChatGPT, Perplexity and Google's AI answers. This exposed the exact buyer questions they were losing and where the most valuable gaps were Without reliable and significant measurement you do not have an AEO strategy, it’s just SEO with a fancy name. (2) Covered the whole buying decision We prioritised MOFU and BOFU content such as competitor comparisons, category alternatives, migration guides and buyer guides to capture as much commercial intent as possible and create the positive brand associations we wanted embedded inside AI answers. (3) Engineered every page for two retrieval systems We used CITABLE, our framework for Google and LLM retrieval. Everything managed by our editorial team end-to-end to ensure content was on-brand, relevant and differentiated. (4) Built off-page consensus for brand authority Models look beyond a company's claims when deciding what to trust. We found the conversations shaping category consensus on platforms like Reddit and made sure incident was included. The impact: - Increased organic meetings by 22% - Increased Google top 3 keywords by 97% - Average Google position moved from page 2 to page 1 // About Discovered Labs: we're a team of AI/ML engineers and marketers that help generate 10,000s of conversions every month from organic search through end-to-end SEO/AEO services, working with companies like Granola, Composio, Instantly, incident and others. If you'd like to learn more about our work, click here: discoveredlabs.com If you have any Qs about what's working in AI search right now, feel free to connect & send a DM
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Liam retweeted
credit to discovered labs and their team for doing incredible work in the space! respect!
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Big milestone for us as an ai-native services company: we've shipped our own company harness called Pascal Like pretty much everyone in our bubble of the internet, we've tried to lean into AI as much as possible First, it started with Claude and ChatGPT via the web interface, throwing .md files into projects and using structured prompts Then it was running Claude Code and Codex locally, creating agents that used several skills and rules to run entire workflows Then it was...chaos The early gains were insane and so worth it. But you reach a certain point where the chaos outweighs the benefits When everyone is using Claude/Codex in single-player mode, some team members are AI wizards while others are not, and everyone has their own flavour of how skills work, it creates a lot of divergence and chaos Struggles with adoption, standardisation, data validation and observability quickly become bottlenecks For us to scale as a company we can't rely on heroics where one individual can create high-quality work with AI but others suffer, and we don't want to simplify things so much where we're working with basic markdown files that create no edges We've graduated most of our core workflows into a proprietary cloud platform, effectively working just as typical software does, but every team member still has access to our agents and company MCP so they can run workflows locally Now we have observability so we know when an agent does something wrong, we're constantly building custom evals to standardise quality, we've got data validation in place, we've built a context layer across the entire company, and we can use whatever models we want incl. OSS models to avoid dependence on frontier models It's been insanely difficult to get to this point, it requires a complete rethink of how companies & people have worked since mass-adoption of the internet around 30 years ago. Everything - people, systems, org structure, standards, culture - needs to be thought about differently if you want to scale this across an org of dozens of people (and just to be clear: these workflows are responsible for generating tens of millions ($$) in revenue, so there's a lot of complexity involved) Very proud of the team on this one. All done while being bootstrapped, and unlike many other things in business, working from a blank playbook with little-to-no historical precedent
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They ripped our case study lol. Even uses our OCEC framework
Granola, a $1.5B company, increased monthly new users from AI search by 4,600% in JUST 7 months. here’s the genius AEO workflow behind it: 1. They started with buyer decisions, not keywords -> Granola mapped the questions people ask before choosing an AI meeting tool -> Then they turned those same decisions into both Google keywords and AI prompts so they could measure where the brand actually showed up 2. Every lost prompt got diagnosed before anything was created -> If Granola wasn’t showing up, they first asked why -> Was the right page missing? -> Did the page already exist but fail to answer the question properly? -> Was there a crawl/indexing problem? -> Or was AI getting the answer from third-party sources that barely mentioned Granola? 3 They separated “missing page” from “weak page” -> This sounds obvious, but it changes the entire content strategy -> If a relevant page already existed, they improved that page instead of publishing another article targeting the same question -> New pages were only created when there was actually a gap 4. They stopped treating every technical SEO issue like it mattered equally -> Crawlability, indexing and performance problems were prioritized based on whether they affected pages tied to real buyer demand -> A technical issue on a page connected to an important buying question came before cleaning up random site-wide warnings 5. They studied the exact third-party sources AI was already trusting -> For prompts Granola lost, they looked at the Reddit threads, review sites, articles, directories and other pages showing up instead -> The question wasn’t just “how do we get more backlinks?” -> It was “which sources are shaping this specific recommendation, and why are competitors represented there better than us?” 6. They used a simple framework for every important source: -> OWN: pages Granola controls directly -> CLAIM: profiles and listings they can take ownership of -> EARN: editorial mentions, reviews and community discussions they have to deserve -> CONTEST: outdated or incorrect information they need corrected -> Different source = different action 7. Reddit became part of the search strategy -> Instead of posting everywhere, they focused on communities much closer to the product and buyer -> The same buyer questions being tracked in AI search were used to decide which conversations were actually worth joining 8 They measured Google and AI separately -> A page could rank better on Google and still barely move in ChatGPT -> AI mentions could rise while organic traffic stayed flat -> So Granola tracked both systems independently instead of assuming SEO performance meant AEO performance 9. Then they reran the same questions and scaled what actually moved users -> measure the gap -> diagnose why it exists -> make one specific change -> rerun the prompts -> track whether visibility and activated users moved -> double down on what worked the result: -> monthly new active users from AI search increased 4,600% -> non-branded AI citation rate increased 558% -> non-branded mention rate increased 739% -> organic sessions increased 134% Granola didn’t win AI search by JUST publishing more blogs & content like every other company instead they built a system for figuring out exactly what they were missing, choosing the right fix, and measuring whether it actually brought in users. then after that just iterating and doubling down on what worked AI search is now one of their biggest acquisition channels. and it should be one of yours too! if you want us to run an audit for your company and make you rank #1 in AI search, reply “audit”
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in celebration of one of our client case studies being ripped on X, here is a completely different client who's currently getting almost 300k signups per month from organic you can copy the case study but not the alpha god bless
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in celebration of one of our client case studies being ripped on X, here is a completely different client who's currently getting almost 300k signups per month from organic you can copy the case study but not the alpha god bless
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. @mal_shaik what's going on here? directly ripped from our website, no credit
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What do managers look like in the AI era? There seems to be a barbell Extremely ai-pilled vs. barely uses AI When all of the ICs are ai-native and every company is now becoming a product company, i struggle to see how you can solve a company's hardest problems w/o also being a heavy user and strong systems thinker
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Brothers, sisters, nobody cares about the vibecoded tool or app you've built It's the equivalent of showing a pivot table in Excel Much more interested in: - what problem you solved - how you implemented guardrails, data validation, evals - what metric you improved Building tools & apps isn't hard - showing a vibecoded tool w/o reasoning through the above 3 things is an anti signal
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Looking for a S-tier thumbnail designer You'll take a rough, half-baked brief like "create some thumbnails for this video" and come back with elite thumbnails Ideally you can create 3x variants for 1 video, each testing a different concept, so we can A/B/C test Please DM me with your rates & proof of past work Thank you 🙏
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Do a kickflip!
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An agency partner we work with was obviously using AI to email us, painful experience
Please I am begging you, stop sending me Slacks that are obviously written by Claude code. It feels like you haven’t put any effort into reading my message, even if you have. At least put in the effort to make it look like it's not written by AI lol
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One of our biggest B2B SaaS clients gets 30,000 signups per WEEK, with a large chunk of those coming via people building inside claude code and codex Users are prompting "help me build X" inside their agent and the agent is making a purchase decision on their behalf Barely anybody is optimising for this, different ball game than just posting blog content and hoping it ranks
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Maybe i'm the crazy one but seen a huge increase in candidates applying for FULL-TIME roles at our co and they think it's ok to run other clients/projects in parallel at the same time Is this normal?
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Liam retweeted
AdvisoryAI's demos and closed won revenue are up 100% YoY from SEO/AEO. We've been working with them over the last several months. I caught up with Ben who runs marketing at AdvisoryAI, a pre-Series A startup building AI tools for financial advisers. One of my fav pieces of feedback from Ben: "Other agencies inside our shared Slack channel mentioned they want their communication standard to be at the same level as Discovered Labs" When we took over from their previous SEO agency, a site move had seemingly cost them nearly all their organic traffic. They ranked for very few keywords and the majority of clicks came from people already searching for AdvisoryAI by name. Here's what we changed: (1) Fixed the foundation before anything else The site had real technical issues. We ran a site audit and shipped the fixes within a day or two which almost immediately had an impact. (2) Used proprietary AI visibility measurement to build the content roadmap Everyone's using AI visibility tracker atm (or trying to vibecode one over a weekend). The problem is that many of them rely on flawed measurement methods. With our approach, we were able to get hyper-targeted on the topics we went after, helping them increase share of voice by 244% for a key topic cluster in one month. Every piece of content managed E2E by our team of editors, structured using our CITABLE framework to ensure the best chance of performing across Google and LLMs. (3) Used Reddit to influence the sources AI draws from Most people judge Reddit's value by the citations visible inside ChatGPT. We intercepted ChatGPT's retrieval traffic and found Reddit occupied roughly 27% of its search slots, despite only appearing in a small % of visible citations. So we focused on the Reddit threads already shaping the commercial prompts that mattered to AdvisoryAI, with one of our placements becoming the most-cited Reddit source LLMs are drawing from. (4) Used data to find and go after competitor gaps By July, AdvisoryAI had overtaken one of their main competitors. We were able to do this by drilling down into the specific topic clusters and model-level performance, identifying where competitors were weak, and putting together a dedicated strategy for displacing them. Ben's own words: "You guys are able to take what everybody else refers to as a black box, which is LLM search results, and make it a white box." Now, we're about to go even deeper with original thought leadership so we can create distance :) // About Discovered Labs: we're a team of AI/ML engineers and marketers that help generate 10,000s of conversions every month from organic search through end-to-end SEO/AEO services, working with companies like Granola, Composio, Instantly and others. If you have any Qs about what's working in AI search right now, feel free to connect & send a DM!
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Just asked Tom, CMO at @incident_io (Series B), what it's actually been like to work with us on SEO and AEO. The results: in the first four months organic meetings booked grew 22%, their AI share of voice is up 62% and top 3 Google rankings are up 97%. Tom runs a lean marketing team, so he needed a partner that could own the work and keep adapting as AI search changed. As he put it himself: "it's not as easy as publishing more content...if you want to just go buy a tool like AirOps and churn out a bunch stuff, great, go for it...Liam and team will help you understand the strategy inside of it, not just the tactical execution." Here's what that strategy looked like: (1) Turned "we're probably behind" into a competitive map We tracked incident against competitors across ChatGPT, Perplexity and Google's AI answers. This exposed the exact buyer questions they were losing and where the most valuable gaps were Without reliable and significant measurement you do not have an AEO strategy, it’s just SEO with a fancy name. (2) Covered the whole buying decision We prioritised MOFU and BOFU content such as competitor comparisons, category alternatives, migration guides and buyer guides to capture as much commercial intent as possible and create the positive brand associations we wanted embedded inside AI answers. (3) Engineered every page for two retrieval systems We used CITABLE, our framework for Google and LLM retrieval. Everything managed by our editorial team end-to-end to ensure content was on-brand, relevant and differentiated. (4) Built off-page consensus for brand authority Models look beyond a company's claims when deciding what to trust. We found the conversations shaping category consensus on platforms like Reddit and made sure incident was included. The impact: - Increased organic meetings by 22% - Increased Google top 3 keywords by 97% - Average Google position moved from page 2 to page 1 // About Discovered Labs: we're a team of AI/ML engineers and marketers that help generate 10,000s of conversions every month from organic search through end-to-end SEO/AEO services, working with companies like Granola, Composio, Instantly, incident and others. If you'd like to learn more about our work, click here: discoveredlabs.com If you have any Qs about what's working in AI search right now, feel free to connect & send a DM
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AdvisoryAI's demos and closed won revenue are up 100% YoY from SEO/AEO. We've been working with them over the last several months. I caught up with Ben who runs marketing at AdvisoryAI, a pre-Series A startup building AI tools for financial advisers. One of my fav pieces of feedback from Ben: "Other agencies inside our shared Slack channel mentioned they want their communication standard to be at the same level as Discovered Labs" When we took over from their previous SEO agency, a site move had seemingly cost them nearly all their organic traffic. They ranked for very few keywords and the majority of clicks came from people already searching for AdvisoryAI by name. Here's what we changed: (1) Fixed the foundation before anything else The site had real technical issues. We ran a site audit and shipped the fixes within a day or two which almost immediately had an impact. (2) Used proprietary AI visibility measurement to build the content roadmap Everyone's using AI visibility tracker atm (or trying to vibecode one over a weekend). The problem is that many of them rely on flawed measurement methods. With our approach, we were able to get hyper-targeted on the topics we went after, helping them increase share of voice by 244% for a key topic cluster in one month. Every piece of content managed E2E by our team of editors, structured using our CITABLE framework to ensure the best chance of performing across Google and LLMs. (3) Used Reddit to influence the sources AI draws from Most people judge Reddit's value by the citations visible inside ChatGPT. We intercepted ChatGPT's retrieval traffic and found Reddit occupied roughly 27% of its search slots, despite only appearing in a small % of visible citations. So we focused on the Reddit threads already shaping the commercial prompts that mattered to AdvisoryAI, with one of our placements becoming the most-cited Reddit source LLMs are drawing from. (4) Used data to find and go after competitor gaps By July, AdvisoryAI had overtaken one of their main competitors. We were able to do this by drilling down into the specific topic clusters and model-level performance, identifying where competitors were weak, and putting together a dedicated strategy for displacing them. Ben's own words: "You guys are able to take what everybody else refers to as a black box, which is LLM search results, and make it a white box." Now, we're about to go even deeper with original thought leadership so we can create distance :) // About Discovered Labs: we're a team of AI/ML engineers and marketers that help generate 10,000s of conversions every month from organic search through end-to-end SEO/AEO services, working with companies like Granola, Composio, Instantly and others. If you have any Qs about what's working in AI search right now, feel free to connect & send a DM!
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Looking to hire our first in-house marketer: content lead You'll take what's already working across our primary channels and help us do a better job through systems and impeccable taste Any referrals appreciated, just shoot me a DM, will share JD to those who ask
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Liam retweeted
Just asked Tom, CMO at @incident_io (Series B), what it's actually been like to work with us on SEO and AEO. The results: in the first four months organic meetings booked grew 22%, their AI share of voice is up 62% and top 3 Google rankings are up 97%. Tom runs a lean marketing team, so he needed a partner that could own the work and keep adapting as AI search changed. As he put it himself: "it's not as easy as publishing more content...if you want to just go buy a tool like AirOps and churn out a bunch stuff, great, go for it...Liam and team will help you understand the strategy inside of it, not just the tactical execution." Here's what that strategy looked like: (1) Turned "we're probably behind" into a competitive map We tracked incident against competitors across ChatGPT, Perplexity and Google's AI answers. This exposed the exact buyer questions they were losing and where the most valuable gaps were Without reliable and significant measurement you do not have an AEO strategy, it’s just SEO with a fancy name. (2) Covered the whole buying decision We prioritised MOFU and BOFU content such as competitor comparisons, category alternatives, migration guides and buyer guides to capture as much commercial intent as possible and create the positive brand associations we wanted embedded inside AI answers. (3) Engineered every page for two retrieval systems We used CITABLE, our framework for Google and LLM retrieval. Everything managed by our editorial team end-to-end to ensure content was on-brand, relevant and differentiated. (4) Built off-page consensus for brand authority Models look beyond a company's claims when deciding what to trust. We found the conversations shaping category consensus on platforms like Reddit and made sure incident was included. The impact: - Increased organic meetings by 22% - Increased Google top 3 keywords by 97% - Average Google position moved from page 2 to page 1 // About Discovered Labs: we're a team of AI/ML engineers and marketers that help generate 10,000s of conversions every month from organic search through end-to-end SEO/AEO services, working with companies like Granola, Composio, Instantly, incident and others. If you'd like to learn more about our work, click here: discoveredlabs.com If you have any Qs about what's working in AI search right now, feel free to connect & send a DM
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this dude will make $1M just by capitalising on competitiveness someone's paid $10k to be top
I love how people start randomly claiming ranks on outbid.lol just for the getting the nice number 🫶🏼
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