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Zombie GTM User Base Discovery
Zombie GTM User Base Discovery
Prompting as Programming in 2026
Prompting as Programming in 2026
AI made paid signals obsolete. Signals are no longer a product. They are a prompt away. Read on how to get your signals at no cost.
AI made paid signals obsolete. Signals are no longer a product. They are a prompt away. Read on how to get your signals at no cost.
Vector search understands meaning, phrase match nails exactness. Together, they’re absurdly good at finding almost anything. Step up your Clay game and save hundreds of dollars.
Vector search understands meaning, phrase match nails exactness. Together, they’re absurdly good at finding almost anything. Step up your Clay game and save hundreds of dollars.
GTM engineers are today’s alchemists, chasing digital gold in a world without a Periodic Table. Clay recipes are traded in private channels, sold as training, and hyped on LinkedIn.
GTM engineers are today’s alchemists, chasing digital gold in a world without a Periodic Table. Clay recipes are traded in private channels, sold as training, and hyped on LinkedIn.
Why are GTM pros still burning thousands monthly on ZoomInfo’s buggy, outdated data and fighting Apollo’s bounce-rate nightmares that deliver more frustration than leads? It’s like using Grammarly’s relic in the GPT5 era.
Why are GTM pros still burning thousands monthly on ZoomInfo’s buggy, outdated data and fighting Apollo’s bounce-rate nightmares that deliver more frustration than leads? It’s like using Grammarly’s relic in the GPT5 era.Or they’re just wary of the GTM grind, battling Clay’s credit-guzzling limits,
Last week we wrote about small, obscure TAMs that can still be very profitable. This week, client conversations pushed it even further: micro TAMs, markets where the total number of target accounts is under 100.
Last week we wrote about small, obscure TAMs that can still be very profitable. This week, client conversations pushed it even further: micro TAMs, markets where the total number of target accounts is under 100.
Obscure verticals once un-targetable are now your GTM playground. Most GTM agencies skip small TAM projects as locating the right companies is the toughest hurdle. But that is changing.
Obscure verticals once un-targetable are now your GTM playground. Most GTM agencies skip small TAM projects as locating the right companies is the toughest hurdle. But that is changing.How would you reliably source: • Guided big game hunting outfitters in the US • Remote security monitoring and alar
Most GTM teams don't even know they're prospecting with blinders on, missing two-thirds of the market in plain sight.
Most GTM teams don't even know they're prospecting with blinders on, missing two-thirds of the market in plain sight.
🚀 Meet Disco Gen, a Second-Generation AI Research Agent for GTM. Create new columns with any prompt for each company in search results 👇
🚀 Meet Disco Gen, a Second-Generation AI Research Agent for GTM. Create new columns with any prompt for each company in search results 👇
💰 Usage-based pricing sounds sexy… and just as risky, but what’s the alternative?
💰 Usage-based pricing sounds sexy… and just as risky, but what’s the alternative?
Targeting Local Businesses with Serper and Google Maps: GTM Gold Standard or Missed Opportunity? What If I Could Get You 50% More Coverage?👇
Targeting Local Businesses with Serper and Google Maps: GTM Gold Standard or Missed Opportunity? What If I Could Get You 50% More Coverage?👇
3 common problems that make GTM engineers race to spin up new Clay automations or 8n8 workflows 👇
3 common problems that make GTM engineers race to spin up new Clay automations or 8n8 workflows 👇
Scraping Google Maps is a demo trap. Let’s talk dentists in the US. 🦷 Want to find dentists who carry Invisalign? Sounds simple 👇
Scraping Google Maps is a demo trap. Let’s talk dentists in the US. 🦷 Want to find dentists who carry Invisalign? Sounds simple 👇
Recover Lost Precision in Account Discovery: Infuse Context Engineering Rigor into ICP Prompts 👇
Recover Lost Precision in Account Discovery: Infuse Context Engineering Rigor into ICP Prompts 👇
How ColdIQ Doubled an Enterprise Client's Target Account List in 30 Hours Using DiscoLike
Enterprise SaaS company discovers 2,000+ hidden high-value accounts and 15,000 new contacts previously invisible to traditional data providers like Apollo, ZoomInfo, and Cognism.
Everyone knows Apollo and Clay's company accounts are just indexing LinkedIn’s company directory. But can you do better? How about 6x better? 👇
Everyone knows Apollo and Clay's company accounts are just indexing LinkedIn’s company directory. But can you do better? How about 6x better? 👇
🤔 Got this hard TAM question from a prospect (and former Keyplay user) today:
🤔 Got this hard TAM question from a prospect (and former Keyplay user) today:
GTM Engineers 🚀 Want to level up like Data Engineers? Here’s the simple blueprint for a Target Accounts Audit 👇
Any time you are working with data it’s a good idea to validate two key things, Accuracy and Coverage.
💎 Lookalikes are all the rage, but useless for finding midsize SaaS gems. Feeling stuck? You need tech & precision. See how 👇
💎 Lookalikes are all the rage, but useless for finding midsize SaaS gems. Feeling stuck? You need tech & precision. See how 👇
The New AI Cold War. Your intent signals are not 🚫 working. Welcome to the new GTM arms race: AI research bots 🆚 Human buyers. 👇
👻 AI-side search agents silently harvest, evaluate, and screen. Traffic to your site? Untraceable, proxied through AI calls. Why visit 20 review sites and 10 vendor sites… when GPT or Grok does it instantly?
🔓 Unlock Precision Targeting with Website Signals. Here is how: Target by👇
🔓 Unlock Precision Targeting with Website Signals. Here is how: Target by👇
Unlock Growth & Business Function Targeting: Exclusive GTM Data
Growth intent data is a powerful option in GTM engineering. Two common sources are LinkedIn employee counts and job postings counts.
💡 What if you could target any vendor’s customers… …without paying 4 different providers to cobble it together?
🤹 Why juggle HG Insights, BuiltWith, Store Leads, and Apify and others to piece together technographic data when you can get it all in one place with DiscoLike?
🤔 Why do AI prompts inside GTM automations break or yield unpredictable results? Here’s a GTM Engineer Cue Card to navigate the randomness👇
⚙️ Generative models are amazing, but their answers vary. The reason is the decoding step.
Why Your Clay or N8N Automation Flow Is Sabotaging You (And How to Fix It)
There's a surge of love among GTM engineers for automation sequences, and understandably so: build a list, scrape website text, and use GenAI prompts to validate account fit. But despite the apparent simplicity and power, there's a sabotage happening right from step one.
Why Generative Models Struggle with Negation
Generative models, like large language models, generate human-like text by predicting words based on patterns in datasets but struggle with negations, such as "not" in "I do not like apples." Training data favor affirmative statements, leaving fewer negated examples, so models poorly grasp how "not"
Seeing some panic in SEO/SEM circles over Google's Mode announcement. So, what now?
The answer isn’t complicated. We just need to peek under the hood of how LLMs actually work.
Understanding The Similarity Gap
The similarity gap, defined as the maximum gap in cosine similarity between a webpage and its nearest similar page, offers a lens to evaluate a website's uniqueness in the digital landscape. Cosine similarity measures how closely two pages align based on their content, typically represented as embed
20-50 Companies Max: The Uncomfortable Truth About AI-Generated Target Account Lists
The market is buzzing with a flood of GTM agents that automatically identify target accounts. New AI solutions promise you can simply ask for a list of lookalike companies. Some even predict the GTM engineer job will disappear soon. If you just want a list of 50 companies from the Fortune 5000 list,
From Nuclear Promises to AI Fallout: Are We Repeating the Same Mistakes?
Nuclear technology was once celebrated as the future of cheap, clean energy, “too cheap to meter.” Yet, it was pushed forward without enough safeguards. Toxic waste, for which we still have not found a permanent solution, and accidents like Chernobyl shattered public confidence. Even lower CO2 emiss
The Hidden Cost of AI-Generated Code: A Silicon Valley Reality Check
The tech world is buzzing about AI coding assistants saving hours of developer time, but let's pause and ask the uncomfortable question: Are we just shifting the complexity from writing code to making our clients become unwitting debuggers of mysterious AI-generated solutions?
Operators Are Standing By… But They Can’t Count!
You just upgraded your OpenAI account for the month to give Operator a shot and tasked it with cleaning up your CRM. Step one, an easy task to warm up: deduplicate and check if existing customers are already in the system. Surprisingly, you still find a few duplicates here and there, and some client
Innovation Selling: The Last Frontier AI Can't Conquer in B2B Sales
The evolution of B2B sales has taken another dramatic turn. We've moved from feature selling of the 1980s, through solution selling of the 1990s, and past the challenger/insight selling of the 2010s. Today, we're witnessing the rise of innovation-driven sales – and it's not just another methodology
The Hype Cycle: Rideshare Dreams and AI Realities
The allure of instant creativity and wealth fueled by AI is undeniable, but are the current models sustainable? This post dives into the hidden costs of large generative AI models, from soaring hosting prices to immense energy consumption. It advocates for a more sensible approach, championing small
LinkedIn Scraping: A Minefield for Rising GTM Companies Bound to Trip Many
In the fast-paced world of Go-to-Market (GTM) strategies, the allure of LinkedIn scraping can be hard to resist. For rising companies looking to accelerate product development, purchasing scraped LinkedIn data might seem like a quick fix. However, this shortcut is riddled with hidden risks that coul
Demystifying Target Account Modeling: How to Do It in 2 Easy Steps
Target Account Modeling can feel overwhelming, often appearing like an entirely new product rather than a simple feature. However, the key to success lies in breaking it down into manageable steps. By focusing on customer segmentation and embedding-based search, you can unlock the full potential of
From Keywords to Context: Embracing the Future of Search with LLM Embeddings
For over two decades, digital content and search strategies have been dominated by a focus on keywords. This keyword-centric approach, once revolutionary, now reveals its limitations in the era of large language models (LLMs). As search technology evolves, the shift from keywords to context, driven
Platform Partnerships: A Smarter Path to the SaaS Future
The SaaS industry has long been captivated by a winner-takes-all mindset. From the dominance of MS Office to today’s competitive landscape, companies have poured resources into replicating each other’s functionalities. This relentless duplication drives up prices for customers, diverts attention fro
Still going on fishing expeditions? Try TAM as an Account List instead.
We believe that sales and marketing should be about market penetration, not volume. By using precision company data and purpose-built LLMs, we’re enabling businesses to identify their TAM as a complete list of all Target Accounts.