When I first started cold email for my AI automation agency, I was hardly getting any replies. The emails sounded “fine” in my head, but looking back, I was doing it completely wrong. After running outreach consistently and testing loads of different approaches, I noticed that replies started coming in the moment i started using micro offers. Once I started making it about them and leading with value, everything improved: more replies, better conversations, more booked calls. So I put together a quick breakdown of what micro offers are and how I use them to consistently get a 10-16% reply rate on my cold email campaigns. You can access it here, hope it helps 👍

I know a lot of you in here use Apollo to build lead lists for either your own business or your clients. But one thing I don't think people realise is just how powerful Apollo's filters actually are. Most people use a few basic filters, pull a big list of leads, and call it a day. The problem is that your filters determine who ends up on your list, and if you get them wrong, you're going to spend time reaching out to people who were never a great fit in the first place. Once I started getting more intentional with the filters I used, my lists became smaller but way more relevant, which made everything else easier. Better personalisation, better replies, and better qualified calls. So I put together a free Apollo filter guide breaking down the main filters I use and how I think about building lead lists inside Apollo. You can access it here, hope it helps 👍

Does anyone here find cold email hard and if so what part?

10 months ago when it came to doing cold email for my ai agency, I'd spend ages setting up domains, writing emails, building lists, and then wonder why the campaign wasn't performing. The problem was that I had no real plan. I was just launching campaigns and hoping everything would work itself out. After a lot of trial and error, I realised that the best campaigns are usually won before the first email is even sent. Once I started planning things properly, who I was targeting, what problem I was solving, and how I was positioning the offer, everything became much more consistent. The emails were more relevant, the replies improved, and the calls became easier because the foundations were already there. So I put together a quick guide breaking down the 3 stages I go through before launching any cold email campaign now so it's easier for you to build high converting cold email campaigns. You can access it here, hope it helps 👍

When I first started cold email for my AI automation agency, I thought personalisation just meant mentioning something from their LinkedIn or website. But after a while I realised everyone else was doing the exact same thing. If you’re automating outreach with AI, chances are hundreds of other people are pulling the exact same LinkedIn data and using the exact same type of openers. So even though the email looks “personalised”, the prospect has probably already seen something similar 10 times before. What actually started getting me replies was finding information people weren’t expecting me to know. So I put together a quick guide breaking down how I approach research and personalisation now so your emails stop sounding like every other AI-generated cold email in their inbox. You can access it here, hope it helps 👍