How we grew our SaaS to 10k MRR using social listening

When we were growing Swipekit, one thing became obvious pretty fast.

People were already asking for tools like ours in public.

Not always by name, of course. Most of the time they were asking broader questions.

Things like:

• what’s a good Facebook Ad Library saver?
• how do you keep competitor ads organized?
• is there a tool better than screenshotting ads into Notion?
• how do agencies store ad inspiration for clients?
• what’s a good Magicbrief alternative?

Those are the kind of posts that matter. Someone is already problem aware. Sometimes they are even solution aware. They are actively looking for a product like Swipekit.

That is where social listening came in.

Instead of waiting for SEO to kick in, or hoping people would stumble onto our site, we used Mentionkit - a social listening tool, to monitor those conversations across Reddit, X and LinkedIn, then jump in when it actually made sense. Mentionkit is built for that exact workflow: track keywords, review mentions in one feed, draft replies faster, and mark work as handled so your team has a proper record.

Why social listening worked for Swipekit

Swipekit is not a casual consumer app. It is a pretty specific product for marketers, agencies and brands that want to save ads from places like the Facebook Ad Library, TikTok and LinkedIn, organize them into boards, track competitor brands, and use AI scripts to turn reference ads into concepts, copy and storyboards.

That kind of product benefits a lot from being mentioned in context.

If someone is in a Reddit thread asking how to save ads properly, how to keep a swipefile organized, or how to track competitor creatives without manually checking ad libraries all day, that is not cold outreach. That is not interruption marketing. That is just showing up where the question already exists.

That was the big mindset shift for us.

Instead of thinking “how do we push Swipekit harder?”, we started thinking “where are people already describing the exact pain that Swipekit solves?”

How we set Mentionkit up for Swipekit

The nice part about Mentionkit is that it does not just throw you into an empty dashboard. You can enter your landing page and it analyzes it to suggest keywords and targeting angles. For a SaaS product, that is a much better starting point than opening Reddit manually and guessing what to search for.

For Swipekit, we broke our tracking into 3 buckets.

1. Brand keywords

These were the obvious ones:

• Swipekit
• Swipekit alternative
• is Swipekit good

Brand terms are important because they catch direct interest, support questions, and comparisons. If someone already knows your name, you want to know about it quickly.

2. Competitor keywords

This is where things got more interesting.

We tracked competitor and adjacent-tool phrases, because people rarely search for your product first. They search for the tool they already know, or they ask for an alternative.

So for Swipekit, that meant terms around competitor ad tools, swipefile tools, and ad library workflow tools.

These mentions converted surprisingly well because the user was already in buying mode. They were not casually browsing. They were actively looking to switch, compare, or find something cheaper or easier.

3. Problem-aware keywords

This bucket was the highest leverage one.

We tracked phrases tied to the pain itself:

• save Facebook ads
• ad library downloader
• organize ad inspiration
• competitor ad tracking
• save TikTok ads
• swipe file for ads
• ad creative research tool

These are the mentions that do not look branded on the surface, but they are often the best ones. The person might not know Swipekit exists yet, but they are clearly describing a workflow problem that Swipekit solves.

How we actually worked the mentions

This is the part people usually overcomplicate.

Our process was pretty simple.

Every day, we checked Mentionkit for fresh mentions. We mostly focused on the high-intent ones first. Mentionkit’s workflow is built around reviewing mentions in one place, drafting replies, and tracking who handled what, which made it easy to stay consistent without turning this into a full-time job.

Then for each mention, we asked:

• Is this actually relevant to Swipekit?
• Can we add something useful to the conversation?
• Would mentioning our product feel natural here?

If the answer was no, we skipped it.

That last part matters a lot.

Social listening is not about barging into every thread and dropping your link like a maniac. If you do that, people will smell it instantly.

What worked for us was the opposite.

We tried to leave comments that could stand on their own even if Swipekit was removed from the reply.

For example, if someone asked how agencies keep track of good ads, we would first explain a practical workflow:

save the ad, save the landing page, keep the copy, store it in one place, tag it by angle or format, and make it easy to share with the team.

Only then would we mention that this is basically what we built Swipekit for.

That style of comment performs better because it feels like a real answer from someone who has done the work.

How Mentionkit helped us write better replies

One of the harder parts of social listening is not finding the mentions.

It is replying without sounding fake.

Mentionkit leans into that by giving you AI reply drafts that are meant to sound natural, not robotic. We did use that, but not as a copy-paste machine. We used it as a first draft. Then I edited it so it sounded like me.

Usually the best comments had 3 parts:

1. acknowledge the actual problem
2. give a quick practical opinion
3. mention Swipekit only if it fit naturally

That kept our replies authentic.

And over time, that compounds.

A good Reddit comment does not just help on the day you post it. It can keep showing up in Google, in Reddit search, and in AI-generated answers later on. Mentionkit itself leans into this idea too: showing up early in relevant threads can increase your brand mentions in places that LLM tools and buyers already use.

Why this helped us get to 10k MRR

Getting to 10k MRR did not come from one viral post.

It came from stacking lots of small, relevant interactions.

• A thread here.
• A helpful comment there.
• Competitor comparison post.
• Me answering the workflow question honestly.

A marketer discovering Swipekit because they were already looking for a better way to save and organize ads.

That is why I like social listening so much for SaaS.

It does not rely on perfect timing like social posting, nor does it rely on paid ads. And it nicely compliments SEO and AIO

You are basically inserting yourself into demand that already exists.

For Swipekit, Mentionkit made that process way more systematic.

Instead of manually checking Reddit and X, we had one place to monitor buyer-intent conversations, one place to work through mentions, one place to draft replies, and one place to keep a paper trail of what had been handled.

Mentionkit also includes email alerts, client-ready reporting, API access, and onboarding that helps generate keyword strategy from your site, which makes the whole thing much easier to operationalize as a repeatable channel. (mentionkit.com)

Final thoughts

If you are trying to grow a SaaS, especially in a category where people ask for recommendations in public, social listening is one of the most underrated channels around.

It worked for Swipekit because the market was already talking. We just needed a better way to hear those conversations and respond in a way that felt useful.

That is really the whole playbook.

Track your brand. Track your competitors. Track the problems you solve. Reply like a human.

???

Profit!

And that’s how we used Mentionkit to help grow Swipekit to 10k MRR.

And honestly, it is still one of the simplest growth loops we have.