How to Use AI Tools for Sales Prospecting

Every B2B sales tool today: "We're powered by AI!" Ughh. Are you? I talk to dozens of founders every month. Most have been burned by buying "AI sales tech" That was just a basic GPT wrapper. With good marketing. 🙈 ❌ THE PROBLEM TODAY: So many "AI" sales vendors today demo well. But their actually product? It's not really AI. It's an API call. To ChatGPT... The red flags you should look for: 🚩 Template based responses 🚩 Minimal error checking 🚩 Basic API calls We've tested so many of these tools ourselves. And guess what? They failed to verify basic company data. They misunderstood qualification tasks. They sent emails with wrong context. That's because they're treating "AI" like... A fancy version of mail merge. SO... What should you look for? 2️⃣ What AI Sales infrastructure SHOULD look like Your AI sales stack needs these core components: Multi-Source Verification: - Cross-reference data across 3+ sources - Source tracking for every data point - Real-time accuracy validation - Automated fact-checking Context Management: - Industry-specific knowledge bases - Historical interaction memory - Company relationship graphs NOW... Here's where I'd focus your AI sales agents first 👇 Start with research heavy tasks. Things like: Lead Research: - Identifying expansion opportunities  - Analyzing technographic data - Mapping org structures - Finding trigger events Prospect Qualification: - Technology stack analysis - Company size verification - Recent company changes - Budget signals BEFORE YOU BUY... Look at THESE metrics 📈 "What are your accuracy rates?" Ask them for: - Research verification percentage - Data freshness metrics - Error correction stats - Learning curve data "What are your performance metrics?" - Error reduction over time - Processing speed at scale - Consistency across tasks - Adaptation to feedback THEN... Here's how I'd do a roll out 1️⃣ MONTH ONE - Audit manual research tasks - Document qualification criteria - Map current research workflow - Identify verification sources 2️⃣ MONTH TWO - Test AI on small lead segment - Measure accuracy vs humans - Document error patterns - Refine verification process 3️⃣ MONTH THREE - Scale successful processes - Build feedback loops - Train team on collaboration - Measure productivity gains -- P.S. Always ask AI vendors: "Show me your error rate metrics" If they can't, you know what you're dealing with. Have more questions? Hit me up in the comments or DM me!

I tested 117 AI tools for B2B sales this quarter. Here's what happened: • 54% reduction in admin tasks • 3.2x faster lead qualification • Closing calls prepped in minutes, not hours Most sales teams are using AI wrongly, focusing only on content generation. Here are the 5 AI tools actually moving the needle: 1) Meeting Intelligence: • Descript transcribes every customer call • AI identifies buying signals I'd missed • Auto-creates follow-up tasks based on commitments 2) Research Automation: • Perplexity AI builds prospect briefs in 90 seconds • Surfaces trigger events I'd never find manually • Helps me personalize at scale (not mail-merge "personalization") 3) Cold Outreach Enhancement: • Using Claude to analyze response rates across 2,400 emails • Discovered 3 messaging patterns that doubled replies • Now every campaign starts with AI-driven message testing 4) Pipeline Analysis: • ClickUp + AI identifies deals most likely to slip • Suggests specific actions based on similar won deals • Helped rescue $418K in at-risk opportunities last month 5) Proposal Creation: • Jasper builds customized proposals based on call transcripts • Speaks the buyer's exact language back to them • Cut proposal time from 2 hours to 23 minutes The real opportunity isn't replacing salespeople. It's augmenting their capabilities to focus on the human elements that AI can't replicate: building trust, handling objections, and creating genuine relationships. Is your team leveraging AI in your sales process? If so, what's working? #B2BSales #AITools #SalesProductivity #Sales #Revenue

Do you want to be in the driver's seat of your sales success, harnessing the power of AI while staying true to the human touch that closes deals? A great seller adapts and assimilates new tools to better create relationships. From the days of cold calling with nothing but a list and a phone, to the complex, data-driven strategies we use today, one thing remains constant: the need to connect with people on a personal level. Recently, I’ve been leveraging AI-driven outreach in a way that’s revolutionized my approach to sales. But here’s the thing—I’m not just blasting out AI-generated emails and crossing my fingers. I’m using AI as a powerful tool to enhance my work, not replace the human touch that’s always been at the heart of successful selling. When I’m engaging a new organization, AI helps me pull insights from a company’s website, executive LinkedIn profiles, and public reports, surfacing key themes that align with what my team can offer. It’s like having a super-smart assistant who can read everything on the internet in seconds and summarize it for me. In one case, I used AI to help draft emails to multiple stakeholders within a company. It crafted personalized messages that referenced specific goals and challenges mentioned on their website, which I polished with my own flair. Out of 121 organizations, I received 47 responses from C-Level and VP-level executives, all of which turned into conversations and pipeline. That’s a 39% meeting success rate—a figure that was almost unimaginable before integrating AI into my strategy. But here’s the catch—AI can give you the data, the structure, and even the words, but it can’t give you the soul. Sales is, and always will be, about human connection. The risk with AI is that it can make things too polished, too perfect, too robotic. If you rely solely on AI-generated content, you risk losing the very thing that makes sales work: authenticity. Technology can make us smarter, faster, and more efficient, but it’s our humanity that makes us successful. And that’s something no AI can replicate. 🛠️ Try AI-Driven Outreach: Start using AI tools to draft your next round of prospecting emails. Experiment with how AI can help you personalize and optimize your outreach. 🖋️ Add Your Human Touch: Before hitting send, take a moment to personalize the message. Add a relevant anecdote, tweak the tone, and make sure it sounds like you. 🤝 Focus on Building Relationships: Keep your end goal in mind—building strong, long-term relationships. Let AI do the heavy lifting, but always be the one steering the conversation. Ready to combine AI efficiency with your unique human touch? Start today, and see how it transforms your sales game. #SalesSuccess #AI #SalesTips #Authenticity #ModernSelling #CustomerRelationships #SalesStrategy #DigitalTransformation #AIinSales

Sales reps and recruiters are notoriously slow to adopt new tech 🐢 Especially the more seasoned ones who have been top producers in lieu of technology, rather than because of it. So how can sales & recruiting leaders tell their teams they need to be at the forefront of #AI adoption, when they haven't needed it in the past to do their jobs at a high level? It starts with leadership embracing it themselves. Here's how we're doing this at Staffing Engine: -Every morning, I log into ZoomInfo. Their AI CoPilot has surfaced accounts that tell me where to focus my time based on website visits, market signals, news, and other relevant info -When we are reaching out to these accounts, we use Lavender 💜🔮 www.ora.im to help us write & score initial email outreach -As outbound calls, discoveries, demos, and other meetings take place, they are recorded with Chorus by ZoomInfo. As we are fully remote, this gives me an opportunity to review calls and provide our team coaching -Throughout my week, I'm constantly using Grw AI (this is quickly becoming one of my favorites). Grw allows us to role-play calls with Voice AI, provides me an opportunity to provide my team coaching based on internal feedback loops, and provides impressive generative outputs for every stage of our sales cycle -We use OpenAI and other LLMs constantly to help generate content, images, and ideas that save time throughout our day-to-day Here's the thing. As leaders, it's not enough to tell our teams to "go use AI". We need to be doing it ourselves, finding examples, and sharing them with our teams so they become believers as well 🚀 #sales #recruiting #techadoption #leadership

Sales discovery in emerging markets is hard 😅 You spend half your first call just figuring out if they know their pain is solvable. So I'm gunna share the 5 best AI-research agents I've seen sellers create to do that research AHEAD of their first call. 1. “Has this company already built an internal workaround?” 🧠 Detect when a team is already solving the problem—but with duct tape. 🤖 The agent scans eng blogs, docs, and repos for signs of internal tooling that mirrors your product’s core value. 🔍 Example: If you sell a data quality platform, and a prospect has open-sourced their own dbt tests, they’re not just aware of the problem—they're actively burning time solving it themselves. 2. “Is there an internal team with a title or function that suggests they're ready for this?” 🧠 Emerging categories don’t have formal owners yet, but adjacent roles can signal a company is thinking in your direction. 🤖 The agent scans LinkedIn and job boards for emerging titles (e.g. "AI Ops") or descriptions that imply ownership of your problem. 🔍 Example: If you sell internal tooling for ML model review, spotting a new “AI Governance” hire may mean they’re preparing for procurement—even if they haven’t started vendor research yet. 3. “Has the company recently invested in an adjacent tool or initiative?” 🧠 Some software only makes sense after another building block is in place. 🤖 The agent analyzes integration directories, changelogs, or even recent launch posts that signals technical maturity. 🔍 Example: If you sell an LLM observability tool, prospects who recently launched a chatbot using LangChain or fine-tuned a model on Vertex AI are much more likely to be ready. 4. “Does their current stack create pain your product solves uniquely well?” 🧠 Some stacks are practically billboards for your solution’s value. 🤖 The agent scans technical docs, SDKs, open job listings, and blog content for specific integrations, tooling choices, or architecture that create known friction your product is designed to alleviate. 🔍 Example: If your tool speeds up CI/CD times for monorepos, prospects using Bazel + GitHub Actions are living in pain—they just haven’t met you yet. 5. “Is the company entering a phase where old tools break down?” 🧠 Change triggers purchases. This agent identifies companies hitting inflection points that force re-evaluation. 🤖 The agent looks for signs of rapid growth, org shifts, market expansion, or new compliance pressures—any of which might expose the limits of legacy tools or manual processes. 🔍 Example: If you sell a documentation automation platform, a recent launch into an enterprise market or new regulatory region (e.g. GDPR, HIPAA) could make your value proposition much more urgent. All can be built in Koala if you want to apply to every lead, combine with CRM data, and rank with product and web signals. If you're not ready for all that, ChatGPT can help in the meantime!

I recently joined Companyon Ventures's roundtable to share some GTM Engineering & AI workflows with Clay. Here's 4 simple ways to enable your sales team with relevant messaging using AI: 1. Classifying companies based on industry or by custom characteristics 2. Use tech stack to inform the right sales play. In this case, aligning the right product based on a company's cloud infrastructure: Multi region cloud --> position "Multi-region redundancy" Hybrid cloud --> position "Hybrid cloud offering" Previous data leak --> position "Ransomware protection service" To find this data - I used API Ninjas to pull in the DNS Entries + IP Addresses for analysis. 3. Surface & summarize relevant news articles. 4. Generate an easy to digest research report that provides recommendations on what case studies or sales play to deploy. To me, this is just scratching the surface of what's possible. Each company has a unique ICP data set that helps them to: 1. Prioritize the right accounts 2. Find the right people 3. Inform the 'hypothesis' and relevant message 4. Reach out at the right time What do you think about this workflow? #gtmengineering #b2bsales #ai #saas