It can be easy for SaaS companies to lose momentum if they haven’t quite found the perfect product-market fit. How can you get back on track? Kazuki Ohta, CEO & Founder at Treasure Data, shares his company’s story of how pivoting at the right time saved their business and accelerated their growth to $100 million ARR.
The Platform: $0 – $5 Million ARR
When it launched in 2011, Treasure Data’s positioning was a Hadoop-based big data warehouse in the cloud. The Treasure Data platform instantly analyzed large amounts of data, which meant that companies didn’t need to hire lots of computer scientists or put up a considerable upfront investment for data projects.
In the first two years, Treasure Data grew to $5 million ARR, but most of that money came from $3.6 million and $1.2 million deals led by the founders. The reality was that they were heavily relying on the enterprise deals closed by the leadership team.
At $5 million ARR, the positioning shifted to a “big data-as-a-service” platform. The product grew more mature, with three main functions: data collection, data warehouse, and data analysis.
They reached $10 million ARR by year three, which was exciting, but what was missing was a true sense of product-market fit. As Ohta says, “Around 2014 in Q4, we were about to cross a $2.5 million revenue quarter…In reality, though, we were still the founder-led sales company.”
The Graveyard: $10 Million ARR
Even after that exciting third year of growth, leadership at Treasure Data began noticing the lack of product-market fit. A few telling signs started to reveal themselves:
- Sales, Marketing & Accounts Struggled. No matter what VP of Sales they hired, sales consistently failed to meet their quota. Similarly, marketing couldn’t generate the pipeline, and only a single AE managed to hit their target, even then, with the help of the founders.
- Commoditization From AWS & Google Cloud. Competition in the market rose sharply. “The biggest threat we had at the time was Amazon, Google, and Microsoft trying to commoditize everything from the infrastructure layer.”
- SaaS KPIs Suddenly Taking a Turn for the Worse. The ASP was shrinking, so sales were having difficulty overcoming the objection of comparing prices to competitors. As a result, the logo churn went up, the NRR stopped increasing, and the deal rate decreased as the sales cycle got longer.
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Treasure Data took a step back as they tried to figure out how to shift into a better product-market fit, and they determined they could go for one of two directions:
- Build more stack, move to the application layer, and focus on solving an end-to-end problem.
- Fight large competitors like Amazon and Google with performance-per-price through raising a large amount of money.
Each route is valid (for example, Snowflake took the second route), but Treasure Data decided to pursue an end-to-end application route. Of course, there are pros and cons to shifting to an end-to-end application model over a platform. Still, Treasure Data took the plunge and pivoted to an end-to-end app, so they could more consistently capture the market with predictable use cases.
The App: $20 Million to $100 Million ARR
Once the Treasure Data team decided to transition their business, they examined their customer base more closely. They realized that 90% of their clients analyzed customer data, and 90% of use cases came from marketing teams. So they began building marketing applications on top of their big data platform, emerging in a different category, Customer Data Platform (CDP).
The transition was not easy, and there were struggles along the way. Many original team members who believed in the original mission left. The platform innovations slowed temporarily, which drove churn higher. Every piece of marketing collateral had to be rewritten, and the needed AE background shifted from an engineering focus to a marketing and business focus.
Yet, it was all worth it in the end. ARR jumped from $25 million to $100 million within three years. In addition, the SaaS metrics dramatically improved, including increased growth rate, faster pipeline velocity, shorter sales cycle length, and higher gross margin.
Ohta ends with some helpful advice for SaaS leaders: “Treasure Data is now landing by solving specific problems with an app, by using the underlying platform to expand the use cases in your customer base.” He recommends solving specific problems to win more customers and then evaluating new ways to expand revenue with your underlying tech.
- Businesses always fund the project for solving specific problems with an app.
- The underlying Treasure Data platform allows customers to expand into more use cases. The investor likes the platform story, but that is not always how customers will buy.
- On top of the platform, always seek additional apps to expand your TAM.
- If you foresee things going wrong, trust your intuition. Speak with helpful advisors, start proving small, and turn it around.