Jung what's your backstory?

I've been in the startup world for as long as I can remember. Both my father and grandfather built their businesses, and I grew up watching and learning from them.

My grandfather started a construction business from scratch after the Korean war, and my father built a freight forwarding company following the East Asian economic crisis. Seeing their journeys first-hand taught me a lot about the ups and downs of building something from the ground up. Under my father's vision, I was sent to different countries from a young age—New Zealand, Australia, and China—before settling in Hong Kong in 2012. There, I attended a local university, studying computer science, business, and politics. But university life wasn’t for me. I realized this right after my first class and decided to start working immediately.

My first job was as a mobile game translator, where I somehow convinced the CEO to let me distribute the game in South Korea. After a year in digital marketing, I returned to Korea for my national service, serving as a military police officer in the United States Army for two years. When I finished my service in 2015, I went straight back to Hong Kong and dived into startups as a developer. This was around the time AlphaGo was making waves, and neural networks and machine learning were taking off. My first product was an AI education platform (which failed), followed by an HR tech solution that automated first-round interviews using AI (white-labeled). Then came a retail AI product that extracted demographic data from in-store cameras, along with a few more machine-learning-related projects.

Then came 2018. Hong Kong was hit by city-wide riots, followed by COVID-19. Our target market—retail outlets—was decimated, and I had to pivot to survive. I took on whatever jobs I could find in one of the world’s most expensive cities—tutoring, food delivery, insurance sales—before eventually shifting into enterprise IT architecture consulting for corporations in Hong Kong.

Five years in survival mode taught me more about business and life than I could have ever imagined. After finally finding the right co-founders for my next venture, I dropped everything and returned to the startup world—this time with Klipy.

What does Klipy do and how did you come up with the idea?

Every time I help fix or implement a CRM in businesses, the recurring problem is: that nobody wants to handle the data entry.

At implementation, this led to rejection of the tool. For large companies, this leads to data quality issues impacting planning and operations. So we wanted to remove this issue for good using the new technology - generative AI. Starting as a Hubspot wrapper that auto-summarizes emails, we've now become a zero-admin CRM for service businesses.

The idea is simple - we want CRM to be used to understand and manage customer relationships, not 80% of the time spent on managing customer data.

How did you acquire your first 20 users, and what strategies worked?

We first started interviewing everyone we could find in our network - originally assuming that the tool would be helpful for enterprise/corporate salespeople. This didn't work out as it didn't fit into the purchasing process of corporates.

The next channel was cold emails - which also didn't help as we had not defined our ICP (Ideal Customer Profile) properly at that stage.

Our actual first acquisition came from the Product Hunt launch, which luckily led to our tool getting featured in Ben's Bites newsletter. Our first 20 paying customers were acquired from this newsletter, with most of them still staying with us now.

What metrics or feedback confirmed you’d achieved product-market fit?

Measurements we used:

• ICP - User Segment Fit: We had a hypothesis before the AppSumo promotion that our product was fit for 'digital agency / professional service business owners' which was later confirmed to be correct based on our user distribution.
• Feature utilization rate: Each product feature had utilization rate metrics that helped us prioritize feature upgrades.
• Public product roadmap: The public roadmap was crucial in prioritizing and also communicating our direction clearly to our potential users.

Which distribution channels have been most effective for your audience, and how did you find them?

For us, LinkedIn is currently the most effective channel - as our target market is still small and medium-sized digital and professional services agencies that normally use LinkedIn for their own acquisition strategy.

We tested Reddit, Twitter, Facebook, and TikTok but these channels are better at the mass distribution of consumer services but hard to qualify business leads, which means we can never optimize the approach. Even though both the amount and growth rate of impression and engagement were much lower on LinkedIn, the actual quality lead generated was the key metric we were looking for.

If you had to pick one distribution channel for Klipy, which would it be and why?

YouTube channel for Podcasts - It seems video is the most powerful content medium considering the volume of content everyone consumes on a daily basis. Even though I love reading, I still consume a massive amount of videos a day and having a reputable channel to share conversations & insights from other founders not only helps with marketing but also would help me grow as a human being.

Why do your users choose you over other CRM tools?

We solely focus on one theme - building a Sales CRM that functions as a personal assistant.

For clarification, we separate Sales CRM from other functionalities of the CRM domain - focused on record keeping of engagements, pipeline management and analytics. This helps us keep our focus on sales processes.

How do you see AI shaping the future of SaaS, and how will Klipy adapt?

The core of SaaS—or any IT system, really—won’t change. It’s still about saving and retrieving information. But the way users consume SaaS is going to change. Some thought leaders are now talking about "Service-as-a-Software" as a new paradigm, and I agree with this shift. People can now give instructions to computers and receive responses in natural language that they can easily understand. Plus, the combination of different models allows systems to self-plan, self-organize, and self-execute complex initiatives. Merging these two aspects creates an experience that’s very similar to working with a professional services firm.

The old SaaS model—simple data collection, retrieval, and display—will still survive. But the real innovation is moving towards automating entire services, not just individual processes. Luckily, Klipy started with a vision that aligns with this. We wanted to solve the “Hard Fact” problem of sales admin. We focused heavily on building lots of small AI agents that are specialized in performing individual tasks autonomously—for example, detecting purchase intention in emails, or picking up if any promises were made during a meeting.

As LLM costs continue to drop due to competition, delivering this kind of completely “off-the-shelf” automation—based on a deep understanding of a user’s processes—feels like the real differentiator. Especially now that the financial and time cost of developing software is rapidly decreasing too.

What is your plan for Klipy in the future?

We want to build a brand that focuses on removing data entry across all enterprise systems—we’ve seen too many people wasting far too much time on it. So our future plan is to continue relying on ARR, with the goal of building a HoldCo of agentic enterprise systems.

What do you think is the most overlooked aspect of building a successful SaaS business?

I can only advocate for B2B SaaS (as I've only done B2B SaaS my whole career) - I think it is extremely important to constantly attempt to measure and be able to know the dollar value of opportunity cost of not having the solution that the SaaS is providing. Most founders instead try to find a pricing that fits their cost.

Shapes the messaging, pricing, and feasibility of the solution around actual dollar value delivered makes everything very simple and agile for SaaS development - and also helps avoid the "hammer-and-nail-phenomenon" that every engineering project is prone to.

What specific tools, software, or resources have been essential in growing Klipy?

Cursor, Poe, n8n - the ultimate combination that allowed me to build and sell a whole CRM from scratch by myself. Thanks to these tools, we can definitely operate at a scale that was impossible before.

Who are some top experts or entrepreneurs to follow for business growth advice?

Adam Robinson seems to be a good one to follow.

What's your advice for founders on choosing the right channels to attract customers for their product?

I would recommend they use whatever channel they have the most pre-existing connections with the ICP. This helps increase reach to lookalikes in a short period of time, and if they can increase engagement with this segment, they can reach more similar profiles in the same channel.

In my opinion, early stage product is all about time ROI in the beginning to get idea validated and quickly deployed to start getting feedback to shape the product. And if there's one reliable channel established, expanding to other channels becomes much easier as the contents can be refurbished and original channel can be leveraged to kickstart the network in new channels.

What drives you to do what you do?

I love building new shiny things.

Any quotes you live by?

"Knowing is not enough; we must apply. Willing is not enough; we must do." - Bruce Lee

Your links + socials

Jung LinkedIn
Klipy website