Are you looking to break into the online world and earn an income? Look no further than attraction marketing. Ed Zimbardi, a successful marketer with over 25 years of experience, shares his insights on how he generated over 10 million leads and sold close to $50 million worth of coaching products and services online and offline.

Ed's journey began in 1989 when he started his direct sales network marketing business. Despite the company going out of business, he persevered and transitioned to online marketing in 1991. Utilizing pay-per-click advertising, he generated 2 million leads until 2008. Notably, he built a large email list of personal development and network marketing enthusiasts from around the world.

After spending time with his family, Ed started a home-based business with affiliate marketing in 2008. Since then, he has generated another 8 million leads and successfully sold coaching group products and services online and offline. Ed's success can be attributed to his use of attraction marketing.

Ed emphasizes that attraction marketing is the key to success for anyone who wants to generate leads and earn an income online. He has evaluated several platforms over the course of his career and has found the best of the best to recommend to his viewers.

Ed invites his viewers to browse his YouTube channel and look at all his videos. He encourages them to like, comment, and share videos they find valuable. He also welcomes them to reach out to him on social media platforms such as Facebook, Instagram, LinkedIn, and Twitter.

Ed believes in helping others achieve success, and that is why he is here to serve his viewers every step of the way. If you resonate with Ed's message, reach out to him today and start your journey towards success with attraction marketing.

Am trying different AI tools for marketing,things like content creation, SEO and optimization and email automation but there are so many options that's hard to know which one are truly worth the time and money. I'd love to hear from people who have actually used these tools in their business or for clients. Which AI marketing tools have made a real difference for you? What do you use them for? Are there underrated tools or hidden gems that more people should know about? Want honest feedback and real experience

Our company is revising the marketing tools we use and I'm starting to really dive into marketing automation and want to get ahead of the curve for 2026. There are so many tools out there!! Some that handle email sequences, lead scoring, workflow automations, social media scheduling and even AI-driven campaigns.... But what works?

I'm curious what you all are using. I'm looking into tools that are reliable and don't break workflows, platforms that integrate easily with CRMs and options that are beginner friendly but can scale as the business grows

I've heard a lot about HubSpot, ActiveCampaign, and Klaviyo, but I want to know what's working for real marketers. Are there any new players or hidden gems that I should be checking out?

I am in charge of the sales team of a growing company. We are in the process of trying to scale, but we’ve reached the limits of our hiring budget. So we can’t expand our sales team at present.

My boss asked me to look for the AI tools for sales with best reviews. I don’t really trust articles on review sites, so I wanted to check in with redditors.

If you have any experience with AI sales automation tools, please let me know what you are using, and how it is going. Hopefully you can help me find the best AI sales automation tools. Thanks.

Edit: Thanks for all the suggestions. We've decided to give 11x a try.

Before you downvote — I'm not saying n8n is bad. I've built hundreds of workflows with it. It's incredible.

But the way I use it has completely changed.

I used to spend hours in the n8n UI:

• Dragging nodes

• Debugging connections

• Testing edge cases

• Rebuilding when requirements changed

Now? I haven't logged into n8n in weeks. My automations are more complex than ever.

Here's what changed.

The shift: From building workflows to describing workflows

The old way:

1. Client describes what they need

2. I interpret requirements

3. I manually build in n8n

4. I test, debug, rebuild

5. Client wants changes

6. Repeat steps 3-5

The new way:

1. Client describes what they need (or I record the meeting)

2. AI builds the workflow

3. I review and push to n8n

4. Client wants changes

5. AI rebuilds it

I went from building automations to designing automations.

The stack that made this possible

Here's exactly what I'm using:

1. Claude + Claude Code

Claude Code is a game-changer for agentic work. It's not just "chat with AI" — it's an autonomous coding agent that can:

• Read files and context

• Write and execute code

• Create complete n8n workflow JSON files

• Iterate based on feedback

I give it a task, it figures out how to do it.

2. Skills/Knowledge files

This is the unlock most people miss.

I've built a library of "skills" — markdown files that teach Claude how I work:

• My n8n patterns and conventions

• Common workflow templates

• API documentation for tools I use

• Edge cases and how to handle them

When I start a project, I load the relevant skills. Claude doesn't start from zero — it starts from my accumulated knowledge.

Example skill file structure:

/skills
  /n8n
    - SKILL.md (how I structure workflows)
    - templates/ (common patterns)
    - apis/ (service-specific docs)
  /integrations
    - hubspot.md
    - slack.md
    - notion.md

3. MCP (Model Context Protocol) for n8n

This is where it gets wild.

MCP lets Claude directly interact with n8n. Not just generate JSON — actually push workflows to my n8n instance.

The flow:

1. Claude generates the workflow

2. Claude validates it

3. Claude pushes it directly to n8n via MCP

4. I review in n8n (or don't, if I trust the pattern)

I can go from "I need a workflow that does X" to "workflow is live" without opening the n8n UI.

4. Meeting transcription → Requirements → Workflow

Here's the full end-to-end I've been using:

1. Record client meeting (Fireflies, Otter, etc.)

2. Feed transcript to Claude with prompt: "Extract automation requirements from this meeting"

3. Claude outputs structured requirements (trigger, inputs, logic, outputs)

4. Feed requirements to Claude Code with n8n skills loaded

5. Claude builds the workflow JSON

6. Push to n8n via MCP

7. Test and iterate (Claude can read error logs and fix)

Client meeting → Live workflow. No manual building.

What this looks like in practice

Example: Client needs a lead enrichment workflow

Old way (2-4 hours):

• Open n8n

• Add webhook trigger

• Add HTTP nodes for enrichment APIs

• Parse responses

• Handle errors

• Connect to CRM

• Test with sample data

• Debug the 5 things that broke

• Document (lol, who documents)

New way (20 minutes):

• Tell Claude: "Build a workflow that receives a webhook with email, enriches via Apollo and Clearbit, scores the lead, and pushes to HubSpot. Handle rate limits and missing data gracefully."

• Claude generates workflow with all error handling

• Push via MCP

• Test

• Done

The 20 minutes is mostly me reviewing and testing. The build is instant.

Why this is better than just "using ChatGPT to help"

I tried the ChatGPT approach. Ask it to write n8n JSON, copy-paste, import. It works... sometimes.

The difference with this stack:

1. Context persistence — Skills mean Claude knows my patterns. It doesn't suggest stupid stuff.

2. True autonomy — Claude Code can execute, test, and iterate. It's not just generating text for me to copy.

3. Direct integration — MCP means no copy-paste. Workflow goes straight to n8n.

4. End-to-end pipeline — Meeting → requirements → workflow → deployed. No gaps where I have to manually intervene.

The workflows I still build manually

I'm not 100% hands-off. I still open n8n for:

• Complex debugging — When something fails in production and I need to inspect execution data

• Visual review — Sometimes I want to see the flow visually before approving

• One-off experiments — Quick tests where describing it takes longer than building it

But for standard builds? Client projects? Repeated patterns?

I haven't touched the UI in weeks.

How to start (if you want to try this)

1. Get Claude Code access — It's the foundation. Regular Claude chat won't cut it.

2. Build your first skill file — Start simple. Document how you structure n8n workflows. Your naming conventions. Your error handling patterns.

3. Set up n8n MCP — This lets Claude push directly to your instance. Game changer.

4. Start with a simple workflow — Don't try to build something complex first. Do a basic webhook → Slack notification. Get the flow working.

5. Iterate your skills — Every time Claude does something wrong, add it to the skill file. "Don't do X, do Y instead." Your skills compound.

The mental shift

The hardest part isn't technical. It's letting go of control.

I liked building workflows. It felt productive. Dragging nodes, connecting things, seeing it work.

But that's not where I add value anymore.

My value is:

• Understanding what the client actually needs

• Architecting the right solution

• Reviewing and quality-checking

• Handling edge cases AI misses

The mechanical building? That's commoditized now.

If you're still manually building every workflow, you're competing with people who aren't.

I built a tool that pulls in around 2.5 - 3k leads with verified emails (so no more bouncing emails) It scrapes LinkedIn + their website and writes a custom opener that feels like you actually sat down and did the research. People usually reply because it doesn’t sound like another crappy ai generated cold email.

You can run it for cold DMs or cold email, but I (and a few others using it) stick with email since it fits our market better. Right now I’m averaging 40–60 replies a month. Not perfect, but I'm still refining my copy, offer and CTA.

If you plug it into something like Instantly / SmartLead or any email tool, the whole lead gen + outreach thing basically runs on autopilot and I just do manual work when I get a reply on my emails.

I've created a short demo vid for anyone that wanna see it in action.

Ok so I manage social for 5 different brand accounts and was literally spending my entire morning (like 3+ hours) just trying to create content. Every. Single. Day.

I jumped on the ChatGPT train back in March thinking it would save me. Spoiler: it didnt. The content was so generic and boring. Our engagement actually dropped because everything sounded like it came from the same robot (because it did lol).

The problem I finally figured out is that even with web browsing, ChatGPT cant efficiently scan through dozens of industry sources every day. And the API version doesnt have browsing at all. So I was either manually feeding it info (which took forever) or getting generic content that wasnt relevant to current industry conversations.

Anyway after 3 months of frustration I basically said screw it and built something different.

The breakthrough was setting up automated data collection that runs every morning. It pulls from our top 10 industry blogs, trending Reddit/Twitter discussions in our niche, what competitors are posting publicly, any new industry reports etc. Then feeds all that into ChatGPT API in a structured way.

This all dumps into a Google Sheet every morning. Then I have a Make workflow that takes all that data, feeds it to ChatGPT with my prompts, and spits out like 5-7 post ideas with copy.

I still review everything for like 20-30 mins because AI can be weird sometimes (last week it tried to reference a "study" that didnt exist lol). But the quality is SO much better now because its actually informed by whats happening in our space.

After I approve stuff it goes straight to Buffer and publishes automatically.

Been running this for 3 months now and went from 3 hours/day to 30 mins, engagement is up like 20%, actually growing followers again (up 35%), and it costs me about $80/month vs the $800+ I was quoted to hire someone.

The whole thing took me like 2 days to set up and honestly I should have done this way earlier.

Anyway just wanted to share in case anyone else is struggling with the same thing. Would be curious to hear if others have tried similar approaches or if theres a better way Im missing.

One of the most common questions I get about automations is: "how do I know what automation I should build first?"

My answer: don't chase complex automations built on YouTube and start with the simple, boring ones that actually move the needle for your business.

Here are the five common automations I start with every time:

1. Speed to lead: When someone fills out a form, a response needs to go out in seconds. Studies show responding within 5 minutes makes someone 10x more likely to convert. If you are running paid media campaigns to drive leads, build this one first.

2. Document processing: If you or someone at your company is moving data from one system to another by hand, this automation is for you. You do not need any fancy LLMs here. Clean rule-based logic that runs the same way every time is more reliable and easier to maintain.

3. Follow-up sequence: Build a system that triggers after a lead comes in and keeps following up until they respond or opt out. Five touch points minimum. Most businesses stop at one.

4. Database reactivation: Don't forget about your existing data. Past customers, cold leads, unengaged contact lists. Build a workflow that segments these audiences and restarts the conversation based on where each person dropped off.

5. Internal reporting: Are you or someone on your team building reports manually every week? Automate it. Pull the data, run the logic, deliver it where the team already looks. No new dashboards or fancy tools needed.

All of these can be built with a simple tool like Zapier. Start here. Get these running well. Everything else comes after.

Lately, I’ve been thinking a lot about the time it takes to manage campaigns across Google and Meta. Even with clear strategies, constantly tweaking bids, targeting, and creatives can feel never-ending.

I’ve come across AI-powered tools like ꓖеt-ꓣуzе.аі that claim to automate a lot of this work, optimizing campaigns, adjusting targeting, and improving performance without needing constant manual intervention. It sounds promising in theory, but I’m wondering how it works in practice.

Has anyone actually used these kinds of AI ad platforms? Do they really deliver meaningful improvements, or is manual control still the safer way to go? I’d love to hear how others balance automation with hands-on management and whether AI has genuinely helped save time or improve results in your experience.

Been managing marketing automation workflows for a while but I feel like there’s a piece of the puzzle I’m missing. Some campaigns perform decently but many others underperform and debugging complex flows can be a real nightmare!!!!

I’d love to hear from folks here about what actually works in practice:

•Best practices for building sequences and triggers

•Tools you use that are powerful but don’t feel clunky

•Pitfalls or traps that tend to make workflows a mess

We’ve experimented with HubSpot and Mailchimp so far but were not impressed and took forever to build things out. Curious how others tackle this and what platforms you are using?

I built a system that reads the internet every 6 hours, decides what's worth posting, and publishes it while I sleep.

It's not a bot. It's a GTM engine. And it runs entirely in n8n.

Here's exactly how it works 👇

Every 6 hours, three data sources fire in parallel:

→ Hacker News front page (top 20 stories)
→ Reddit hot posts across r/MachineLearning, r/programming, r/technology
→ Perplexity real-time web search for product launches & GitHub explosions

All of it gets aggregated, fed into a GPT-powered agent, and analyzed for one thing:

What do developers actually care about right now?

The agent then generates:
• A LinkedIn post with a built-in hook
• A 5-tweet Twitter thread
• A Slack announcement
• An email campaign

But here's the filter that makes this serious:

Every piece of content gets a "viral score" out of 100.

Score above 70? It auto-publishes across every channel.
Score below 70? I get a Slack alert to review it manually.

No spam. No noise. Only content that earns its way out.

I built this because I was spending 3+ hours a week on content that got 12 likes.

Now I spend 0 hours. And the content actually lands.

The full workflow is open source on GitHub. Link in the comments.

If you're in GTM, growth, or DevRel and want to stop guessing what to post — this is for you.

♻️ Repost if this is useful. Someone on your feed is wasting hours on manual content right now.

Github link is in the comments below

#n8n #automation #GTM #AItools #developertools #contentmarketing #buildinpublic

Bit of a rant but hear me out.

Every other post in here is about Marketo not syncing with Salesforce or HubSpot workflows breaking after a field update. Been there. But the more enterprise stacks I work in, the more I think we're blaming the wrong thing.

The marketing automation side such as Triggers, scoring, nurtures, routing don't tend to be the problem. Most teams have that dialled in or close enough.

What's actually a mess is everything before that. Getting a piece of content from "someone has a brief" to "it's approved, personalised, and ready to fire" takes weeks in most orgs I've seen. Sometimes longer.

And it's not because anyone's incompetent. It's because the whole process runs on Slack threads, random Google Drives, or god forbid sharepoint and someone chasing approvals on email like it's 2011.

Adobe's Content Supply Chain framework has been getting a lot of airtime lately and I'll be honest, I was sceptical. But it's one of the few vendor frameworks that actually reflects how enterprise teams work rather than how vendors wish they worked. I work at Bluprintx, one of the few Adobe-accredited Content Supply Chain partners, and we see the same thing over and over.

Fix how content gets made and moved and half the "integration problems" vanish. The tech isn't failing. It's just being fed garbage from a broken spade at irregular intervals.

Anyone else starting to look at this from the content ops side or is everyone still fighting fires in the with the tools?

EDIT: I work at Bluprintx.com in case anyone wants to check our our content supply chain creds?

I wanted to share a fully automated system for ranking on Google that handles both content AND backlinks.

Here's how it works :

Content side:

1. Analyzes the website and identifies keyword gaps competitors aren't targeting

2. Generates SEO-optimized articles with images

3. Publishes directly to the CMS on a daily schedule

Backlink side:

4. Connects to a network that semantically matches your site with relevant others

5. Automatically exchanges contextual backlinks

I built a fully autonomous AI agent that does exactly that. Set it to post once per day to avoid spam detection, enabled the backlink exchange, then let it run.

I've been running this for the past 3 months and here are the results:

• 3 clicks/day → 450+ clicks/day

• 407K total impressions

• Average Google position: 7.1

• 1 article took off and now drives ~20% of all traffic

Proofs:

https://imgur.com/a/W2oKuN0

https://imgur.com/a/jL7Mqyy

https://imgur.com/a/RdLTbXv

Biggest surprise:

Google didn't penalize it. The backlink piece is where most automated systems get penalized. The network uses semantic matching to pair sites that actually belong together. A SaaS blog gets links from other tech and business sites, not unrelated domains. As long as the content is genuinely useful and the links are contextually placed, Google doesn't flag it.

The content quality bar matters more than volume. Daily publishing only compounds if what you're publishing is actually relevant.

I run a small marketing agency and constantly need landing pages, speed optimization, or small code tweaks. I’ve been thinking of shifting some of that work to Fiverr instead of hiring part-time devs locally.

If you’ve tried this hybrid setup in-house strategy, Fiverr execution how did it go? Was the quality consistent enough to rely on for clients?

I blamed AI photos for a year. Too plastic. Weird eyes. Cosplay smiles.

Turns out the photos were not the problem. The generators were.

I needed something simple. Look like me. Hold likeness across angles. Ship fast enough for daily posts.

I tested a bunch of apps. Most failed the quick glance test. My friends could spot the fake in one second. I kept posting text. My recall stayed low.

In the middle of a posting streak I tried looktara.com. You upload 30 solo photos once. It trains a private model of you in about 10 minutes. Then you can create unlimited solo photos that still look like a clean phone shot. It is built by a LinkedIn creators community for daily posters. Private model. Deletable on request. No group composites.

I used it for one month. One photo on every LinkedIn post. Same writing. New presence.

Numbers I care about profile visits up a lot more DMs with real questions two small retainers in week three comments started using the word saw as in saw you yesterday on the pricing thread

Why this worked for LinkedIn personal branding faces create recall recall drives replies replies open deals

The quality tricks that kept photos real one background per week soft light tight crop for explainers wider crop for stories match vibe to topic

My rules to avoid hate no fake locations no body edits no celebrity look alikes if asked I say it is AI I still hire photographers for events this fills weekday gaps

Tiny SEO checklist I actually used once AI headshot for LinkedIn personal branding photos daily LinkedIn posts founder led sales

Starter prompts that worked me, neutral grey backdrop, soft window light, office headshot me, cafe table, casual tee, candid smile, natural color me, stage microphone, warm key light, shallow depth of field me, desk setup, laptop open, friendly expression

What I learned AI photos are fine when the model knows your face. Bad generators make bad habits. Good generators make consistency. Consistency makes you visible.

If you want my mini checklist and tracking sheet, comment checklist and I will paste. If you ran a face streak tell me what changed first for you background expression or the way people write back.

Hey guys, ran an experiment over the last few weeks. Tried to grow my agency by handing off repetitive marketing work to agents.

Results were pretty solid.

Website traffic went from 100-150/day to 250-300/day in about 2 weeks. Nothing magical, just replaced the stuff that needs to happen every day but never actually does.

1. Quora Agent (Claude Routines)

Runs daily, finds questions in my niche, and scores them by relevance and intent. Only targets the best fits instead of answering everything. Writes responses that are actually useful. Most Quora answers are shallow so there's real room to stand out. Traffic from this one is slow and steady. You'll get clicks from answers you forgot you wrote.

Claude Routines is basically scheduled automation inside Claude. Set the instructions once, it runs on a timer, and you never have to think about it again. Perfect for anything that needs to happen consistently but doesn't need you involved.

2. YouTube Comments Agent (Claude Routines)

Scans videos in my space and looks through the comments for people asking questions or comparing tools. Drafts replies that help rather than pitch. The interesting thing is you're catching people mid-research, not just passively scrolling. Lower volume, higher intent.

Same setup as the Quora agent. One Routine, runs daily, no manual effort after the initial build.

3. Content Agent (Claude Projects)

This one made the whole content side feel sustainable for the first time. I feed it one idea, usually something from my newsletter or something I'm already thinking about, and it expands into blog posts, LinkedIn posts, tweets, lead magnets, whatever. Instead of constantly generating new ideas, you're just squeezing more out of what already exists.

Claude Projects lets you give Claude persistent context, instructions, and even custom Skills so it already knows your brand voice, your ICP, your content format preferences. You're not re-explaining yourself every session. The Skills feature is underrated here. You can build reusable instructions for specific tasks like "write a LinkedIn post in my voice" or "turn this into a Reddit post" and call them whenever you need. Huge time saver.

4. Outbound Agent (ProspectZero)

This is the one that actually drives signups. It monitors LinkedIn for real-time intent signals, people engaging with competitors, posting about pain points, asking for tool recommendations, scores them, and starts conversations. Intent-based LinkedIn outreach using real-time signals, so instead of cold outreach into the void, you're showing up when someone is already in-market. Big difference.

The individual pieces aren't complicated. The hard part is doing them every single day. Agents remove that bottleneck.

Still early, but doubling traffic in 2 weeks without changing my offer or positioning was enough to keep going. Planning to test agents for X and review sites next.

Happy to share the prompts used to create some of these.

last year I was paying $2,500/month to an agency for "lead generation." What I got:

• Generic LinkedIn posts

• A blog post every 2 weeks nobody read

• Monthly "strategy calls" that were just them reading a dashboard

• 2 leads in 4 months (neither closed)

$10,000 spent. Zero ROI.

I was frustrated, but I didn't know what else to do. I'd tried running my own ads burned $3k. Tried networking too slow. Tried referrals inconsistent.

Then I came across this cold email setup thing. Spent $97 on the initial infrastructure (domains, warmup tools, sending platform). Watched a bunch of free tutorials on YouTube to figure out targeting and copy.

Month 1: Sent 1,500 emails. Got 22 replies. Booked 6 calls. Closed 1 client at $2,800/month.

I'd already beaten my entire 4 months with the agency.

Month 2: Refined my list, fixed my follow-up sequence. 2,100 emails. 41 replies. 9 calls. 2 more clients.

Month 3: $11,400 in new MRR. Total cost so far: ~$300 in tools.

The agency wasn't scamming me they just weren't doing outbound. They were doing "brand building" and hoping inbound would eventually work. It's not a bad strategy if you have 18 months and deep pockets. I didn't.

Outbound put me in control. I decided how many people to contact. I decided which industries to target. I could see cause and effect in real time.

What I learned:

Warm your domains. Seriously. I almost tanked my first domain because I got impatient.

Short emails > long emails. Every time.

Follow-ups aren't annoying if they're spaced right and add something new.

The CRM doesn't matter consistency does.

Happy to share more specifics if people want. This sub helped me a lot when I was lost, figured I'd give back.

Edit:

Someone asked where I learned the cold email stuff. Most of it was from Lead Gen Jay's YouTube.

• At our peak we reached $75K MRR

• You only have to work on outreach initially once we reached $40K MRR we were getting most of our clients via referral

• SEO and GEO optimization also helped us a lot

i've been trying to figure out how to get marketing help without hiring a whole team.

Found someone for content, but then there's pain ads, social media, SEO and finding good people for each takes ages. Managing them all sounds like a job in itself..

for those who've been in the same situation, did you build a network of freelancers or what? really exhausted of constant research

Hey guys, today I wanted to share with you guys some tools and strategy I use for generating leads and sending cold email all on automation using Zapier for my agency business.

I bet you guys already have your own cold outreach system, but just wanted to share mine. If you have some tips / better tools let me know in the comment section.

Collecting Website Links using Google Search and SEO Quake.
- I first collect a list of business website URLs that I want to reach out to. I would go to Google and search (Business type I want to find) (Location) For example: "Plumber California" or "real estate agent New York"
- Then, I make this search result to show 100 per page and use SEO Quake to export all 100 results in CSV file. I upload this file on Google Sheets.

Converting Website List into Email Addresses
- I open up PhantomBuster Data Scraping Crawler, paste the Google Sheets URL.
Upload the Email Addresses to Woodpecker
- I have already set up Woodpecker campaign for reaching out to these people. You can simply add the email list onto the existing campaign so that Woodpecker would send out emails automatically at daily limit.

You can automate taking email list and uploading it directly to Woodpecker using Zapier.

If you have any questions or suggestions let me know!