How to mine Reddit for Meta ad gold (no budget needed)

Speaker 1: Most creative teams don't have the time or the money to conduct extensive market research or do some huge intensive focus group analysis. It costs a shit ton of money and it takes a really long time, which is why I love this little workflow that I'm going to show you today that the DTC marketing expert Brennan Tobin came up with for mining Reddit to find winning ad angles. And the best part is, guys, that this is basically free. All you need is an LLM like ChatGPT or Claude and Reddit, and you're good to go.

Speaker 1: Brennan Tobin shared these techniques with us in Motion's latest report on how the best teams in DTC are using AI in their ad workflows. Brennan is the founder of Odd Duck Marketing Group. At his agency, Brennan helps brands scale on TikTok Shop. You should give him a follow as he shares super useful stuff all the time, just like this workflow.

Speaker 1: So to make this video easier to follow along, I'm going to create a fake brand called Daily Defense, which is an immune supplement brand, and I'm going to come up with new ad angles using this workflow. Follow along and pause the video if you'd like so that you can type in what makes sense for your brand that you're working on, and we can come up with some new ad angles together by the end of this video.

Speaker 1: All right, so step one, according to Brennan, is to start with the problem and not the product, which sounds simple, but we need to frame this as a human problem that our product solves, which in this case for my fake brand is about getting sick. So for Daily Defense, I'm not going to look up stuff about immune supplements. I'm searching for pain points without brand names. So pause the video and think about it for a second to see what kind of pain points without brand names you need to be searching up.

Speaker 1: All right, I'm going to go ahead and open up Reddit, and I'm going to go over to this feature called Answers, and I'm going to open up a few different tabs and type in problem phrases like "always getting sick," "tired of being sick," "kids bringing home germs." The idea here is really to develop an understanding of how people describe their struggles and what outcomes they are hoping for.

Speaker 1: All right, let's take a look at the outputs here. And we can see first that it's giving us the subreddit communities and the answers that it's going to be pulling from, which could be helpful for future browsing, you know, if we want to do follow-up questions that I want to ask later. And then just below that, you'll see, okay, we have common reasons for frequent illness, and these hyperlinked parts below in the outputs are really actual quotes from Reddit threads, which is where we want to double-click into to get more context.

Speaker 1: Step two is we need to dive into real conversations from Reddit Answers with some quality follow-up questions. So from here, I'm going to just scroll down to the bottom of the page, and I'll type in a follow-up question. I'm going to start broad. So, "how to stop getting sick all the time." And then look at that. We've got an entire section on supplements and vitamins. And if we click into these, I can get real language that people use. These are not AI summaries. They're actual verbatim quotes. And that part is crucial because here is where it gets systematic.

Speaker 1: Step three is to start adding these emotions and angles into a database based on these quotes I'm grabbing. So for this Reddit thread, the person was asking the biohacker community or subreddit, and they were saying, what to do in order to prevent a cold or get over one quickly. They're training for a 5K and they're stressed about coming down with a cold, and they're having anxiety about missing out and feel like it's inevitably just going to ruin their plans.

Speaker 1: So I'm going to open up just a blank document. You can open up a notepad and create a table with three rows. One for the quotes you're gathering, one for the emotions, and the last one for the creative hooks. So this is basically what my table looks like. I'm going to gather as many quotes as I can.

Speaker 1: The next step is to open up an LLM, so Claude or ChatGPT. You're going to feed it a prompt. Second part of that is we're going to come back to the table we just created. But first, go ahead and pause the video so you can copy and paste and then fill in this prompt that I have in the YouTube description and put it into the LLM.

Speaker 1: So I use Claude extended thinking and research mode. Here's what my prompt looked like for Daily Defense.

Speaker 1: Now, once you've got your market and customer overview plugged into the LLM, you're also going to then put in that database, that unfinished database, and you're going to ask it to fill in the blanks on the emotions and creative angles. And that's kind of the second part of this whole step. And we're going to see if it can add more quotes maybe as well from its own research.

Speaker 1: Okay, look at that. We've got a completed research report and a nice-looking database that's getting started. So we'll review this research report first because this is important. It's got amazing market research. And look at this. All the stuff I've got customer archetypes, competitive white space, recurring positive and negative themes with verbatim quotes, and some gap opportunities that my fake brand could take advantage of. This is kind of nuts, guys. Like, this is reporting that would take somebody like a week to put together, and we just did it in five minutes.

Speaker 1: All right, let's move on to step five. Step five is to take out that report and get all the information that we have now and then put it into our database. Here's the exact prompt that Brennan uses, and then I've got my own little addition that you can put in as well.

Speaker 1: And voila. Look at that. This is so damn impressive. It's short, natural, and true to the customer's voice. There's no jargon. It feels like we could turn these into ads very quickly.

Speaker 1: Okay, the last step that Brennan recommends is to use all this stuff that we've developed so far and feed it into some custom GPTs or Claude agents that can take this database, all this research, and put it and create it into a brief. You can brief your UGC creator, you can brief your designers, your video editors, and there you go. You've just mined Reddit and developed nine new ad clusters based on real consumer quotes. You've identified the driving emotions behind them and turned all of that into creative hooks that are ready for briefing and testing.

Speaker 1: Let me know in the comments if there are other creative strategy workflows that you want help with, and we can show you maybe some AI tools to help you improve that process.