Hey everyone🙋‍♂️ I’m planning to seriously start building and selling AI chatbots to businesses (lead qualification, booking, customer support, follow-ups etc.), and I wanted to tap into the experience in this group before I go all-in. Right now, I’m trying to figure out the smartest way to approach this, so I’d really appreciate any advice on a few things: 1️⃣ Lead generation What’s actually worked best for you when getting your first clients? Cold outreach, warm intros, ads, local businesses, platforms like Upwork, or something else entirely? 2️⃣ Converting clients efficiently Once you’ve got a lead interested in AI/chatbots, what helped you close them? Demos, free trials, case studies, guarantees, pricing structure, etc. — what moved the needle for you? 3️⃣ Social media vs direct outreach Do you think it’s worth building a personal brand / posting on social media (TikTok, Twitter, LinkedIn) to attract clients long-term, or is it better to focus purely on direct sales at the beginning? 4️⃣ Challenges & wins For anyone already doing this: - What were the biggest challenges you ran into early on? - What were your first wins that gave you confidence this could work? I’m fully aware this space is noisy right now, which is why I want to learn from people who’ve already tested things in the real world rather than guessing. Appreciate any insights — even short replies help a lot 🙏 Thanks in advance.

Every agency owner I know struggles with the same problems: Ads drain your budget fast. Referrals are unpredictable. After 18 months of trial, error, and refinement, I discovered a system that consistently generates 30+ qualified meetings per month, using the exact strategies we actually implement every day. Here’s what it delivered in the past 6 months: ● AI SaaS agency: Booked 42 high-quality calls per month. ● B2B tech startup: Closed 4 enterprise deals worth $120k ARR in just 50 days. ● Digital marketing agency: Broke the inconsistent pipeline cycle and maintained 25+ active sales conversations every month. The best part? It outperformed ad campaigns by 5x ROI, without spending a single cent on paid ads. Picture this: every month, your calendar fills automatically with real decision-makers who are ready to talk. No hacks. No luck. No guessing. This is a repeatable, battle-tested system that works across agencies, SaaS, and SMBs. And here’s the kicker: I’m not selling anything. This isn’t a pitch. I’m just sharing what’s actually working right now in 2025. I’ll walk you through the precise setup, if you’re ready to see behind the curtain. Get this workflow for free — comment “TEMPLATE” and I’ll send it to you.

Hey guys, 2025 has been a wild year for me. Went from serving Fortune 500 clients, to that company liquidating, and then making $100K from a single client requesting n8n automation help. This client had posted about needing someone to teach them how to setup and evaluate an n8n automation for automating legal pleading responses. I attached the proposal I responded with and the first workflow. After meeting with him I built a 7 workflow Automation that: - Watches a google drive folder for new documents related to a case - uses OCR to extract text from the document - Reads all the case documents + the new doc - Extracts arguments + facts + case law - Forms an informed response using a case law research AI Agent - Drafts it with proper case law citation - Sends it to proper attorney to review Tech Stack - 1. n8n - for orchestration 2. OpenAI - AI Agent definition 3. AWS Textract - for OCR 4. AWS lambda + AWS S3 Bucket + Python - b/c n8n doesn't have great AWS Textract connectors 5. CourtListener + Google Scholar - Case Law research AI Agent 6. Google Drive - for triggering the workflow This workflow was about a $10K engagement and finished it in about a week. I closed a bunch of other work with him based on other projects he was working on that resulted in the rest of my income from him this year.

I've been helping dental practices automate patient communication, and the biggest bottleneck was initial outreach. Manually emailing 50+ clinics a day wasn't scalable, but mass email tools got me blocked or landed in spam. So I built this workflow in n8n that reads a Google Sheet of clinic contacts, personalizes each email based on their data, and sends them one by one with proper delays between each send. It feels human because it actually waits between emails like a person would. Here's the full breakdown: Manual Trigger Node This is just the start button. When I'm ready to run the campaign, I click execute and the whole thing kicks off. Nothing fancy here, just a clean way to control when emails go out. Google Sheets Connection Setup This node initializes the connection to my Google Sheet where all the clinic data lives. It's basically telling the workflow which spreadsheet to read from and which columns to pull. I keep Email, FirstName, Organization, Website, and Icebreaker columns in there. Google Sheets Reader This pulls all the rows from the sheet. Every clinic contact becomes a data point the workflow can use. It's connected to my actual Google account using OAuth so it has permission to read the data. Process Email Data This is where the magic happens. It loops through every row, grabs the relevant fields, checks if there's a valid email address, and packages everything into a clean data structure. It also counts how many total emails will be sent so I can track progress. If someone doesn't have an email or it's malformed, they get skipped automatically. Split Into Batches This node processes one contact at a time. Instead of blasting 100 emails at once, it queues them up and releases them one by one. This is critical for avoiding spam flags and staying within email provider limits. Send Email The actual email goes out here. I'm using a custom SMTP connection through my business email so it comes from a real domain. The subject line and body pull from the data fields, so each email is personalized with the recipient's name and clinic name. No generic mass email language.

https://youtu.be/UkE_CUmoy00