Seldom does a startup become an overnight sensation. Expecting the same from yours may lead to failure and disappointment. Instead, try growing your business iteratively. Consistent effort, with an eye on the big picture, is what leads to success.
At least that’s the advice from Ali Baghshomali, the founder and CEO of Mentat Analytics, who’s built a sustainable business from diversified income streams. According to Trillium Financial, “Diversification of revenues provides financial stability for your company, reduces business risk, and makes your business infinitely more marketable when it comes time to sell.”1
After only one year in business, Mentat Analytics already generates six figures in revenue helping startups exploit their data stacks. Many companies struggle to set up, maintain, and manage their data tools – and that’s where Mentat comes in.
Start Small, Even if You Have Big Dreams
Ali Baghshomali has been working in the tech industry for ten years. He launched his first startup right out of college. It was a mobile navigation app for areas like festivals and college campuses, places most apps hadn’t mapped.
Despite occasional download spikes during events like the Electric Daisy Carnival in Las Vegas, the app stagnated and eventually folded. Ali says, “I failed miserably with that startup, but I learned a lot from it. Instead of trying my hand at another startup, I went to work as a data scientist at Buzzfeed.”
Ali then worked at Bird, the electric scooter company, as an early employee but was laid off during the pandemic. He made the most of this involuntary career change by working on various projects, from contracting to volunteering. Then, a little over a year ago, Ali decided he wanted to embark on his next startup.
His dream was to launch an online data school, focusing specifically on teaching data skills to people who aren’t on the data team. Many data courses cater to people who want to become data analysts, scientists, or engineers – but none towards other departments, like product teams.
“During my career, I worked with many different teams who’d benefit from data skills. Data skills are universal. Unlike engineering or sales skills, for example, every department can benefit from having basic data skills to work more efficiently, understand their product, and know their customer,” Ali says.
But couldn’t afford the time to build his data school immediately. Instead, he consulted for various companies on data analytics, a journey that eventually became the foundation of Mentat Analytics.
Helping Startups Build Their Data Stack
What’s the difference between an engineering stack and a data stack? Ali explains that the engineering stack is used to build the tech product, while the data stack is used to understand how the business and the product are performing.
In other words, the data team is the eyes and ears of the company. If you don’t have accurate data, you don’t know how many people are using your product, how they’re using it, or which features are performing poorly.
Ali says, “Generally, I found that a startup almost always has a software engineer on their founding team who helps create their engineering stack. But they rarely hire a data engineer to build their data stack until they reach a point when data is critical to the business’s goals.”
As a result, the data stack gets built by someone who doesn’t necessarily know how to do it, since it’s not part of their job description or skills. Mentat Analytics, however, fills the role of a data lead without hiring a full-time person.
The Ups and Downs of Specialization
Ali started consulting for one client, a former coworker. He then invested about $300 to open a company bank account and officially incorporate Mentat Analytics. To find more clients, he looked into partnerships with existing data tool vendors.
Many software companies have solutions partners. It’s in their interest that customers use their tools correctly, and they often refer customers to vetted partners. Analytics tools need precise implementation to get good results, Ali says.
Ali reached out to Mixpanel, a product analytics company whose customers often need help implementing its data tools. He says, “I completed Mixpanel’s certification program because I figured the official badge on my site would appeal to more customers. I did well on their program, and Mixpanel liked my data background. So, they started sending clients my way as one of their trusted partners.”
Ali’s partnership with Mixpanel produced a steady flow of customers. So, the founder narrowed his services to match his Mixpanel specialization. These services included working with companies to implement Mixpanel from scratch, improve their existing setup, and train their employees to ensure autonomy.
Ali says, “I think the only way I can compete with bigger firms is if I provide a very good service. I can only do that if I have some level of specialization. I know Mixpanel inside and out, so I can put my service up against any of the big agencies.”
Soon, the demand for Ali’s services was so high that he decided it was time to hire his first employees, funded by the company’s revenue. But was this hyper specialization with Mixpanel also posing a risk to his business?
Ali says, “Even though Mixpanel helped get Mentat Analytics off the ground, if I wanted to expand, I needed to build my business without focusing on one tool, vendor, or service. Any negative developments at Mixpanel would create a single point of failure for Mentat Analytics. Finding the right line between narrowing down your niche and keeping it lucrative enough is challenging.”
Specialization also made it difficult to hire new employees. Not just because he’s on a bootstrapper’s budget, but because it’s hard to find people with the right skills. When Ali adds a new member to the team, he spends a lot of time teaching them the ropes, throttling growth. Ali keeps a constant eye on forums and asks for recommendations to find others who know the tool as well as he does.
Now, Mentat Analytics has four part-time employees, each specializing in a different data analytics service. Ali has also expanded into providing data services for early-stage startups (which make up a quarter of Mentat’s revenue). A common one is the building of a “Modern Data Stack”, an approach that involves building the stack around a data warehouse. Or, sometimes, startups simply need an audit of their existing data team and stack which can uncover many opportunities for improvement. Mentat Analytics now offers on-demand analytics and data science for startups.
Building Complementary Arms of the Business
Alongside his work on Mentat Analytics, Ali also pursued his passion project: the online data school. He says, “What was meant to be a stop-gap between projects, became huge. But ever since I hired my first employees for Mentat Analytics, I was able to launch my data school, Product Analytics Academy, on June 1st, 2022.” The service offers self-paced data courses for product managers, teaching them the data skills they need to tackle the most common problems in their roles.
While Product Analytics Academy is run under the same corporation (Mentat Analytics LLC), Ali treats it as a separate business with a dedicated website, branding, and strategies. Mentat is the consulting side of the corporation. It provides a steady income but can’t easily grow to ten times its size like a SaaS startup.
While it got off the ground fast, Mentat Analytics requires a lot of time from its founder to expand its capacity. The data school, on the other hand, generates less income but can scale faster, without needing to adapt the product.
“My approach to the company has been to have multiple arms of the business that all complement one another and tackle different problems in the world of product data. Each sub-business supports the other,” Ali says. For example, Mentat Analytics’ clients are the perfect target audience for the data courses.
And as the class sizes increase, Mentat Analytics meets more people who need hands-on consulting. The founder also has plans to build a third arm of the business focused on providing tools for common data engineering tasks, like importing and exporting data.
Does Funding Suit The Way You Want to Run Your Startup?
When creating his startup plan, one of the constraints Ali imposed on himself was to build the business without funding. He says, “I laid out a set of self-constraints and worked my way back, brainstorming what was doable within those boundaries. One of them was that I didn’t want the business to interfere with my flexibility, allowing me to spend as much or as little time on it as I wanted.
“I also wanted to ramp the business up or down based on needs. And I didn’t want to raise funding. Not because the money wouldn’t have been helpful, but because I’m not a fan of how investors affect your business. I’ve seen the downside of funding at companies I worked at before. I saw how it could push a business in a direction the founder doesn’t necessarily want to take.”
Ali says that investors wouldn’t be interested in his business currently because they would want much faster growth. But growth isn’t everything. He wants to maintain the ability to experiment and slowly increase his company numbers.
Mentat Analytics also donates five percent of its revenue to a charity or nonprofit. Ali says, “Once a project is done, I’ll share a list of good causes with my client and have them choose where they want a portion of the overall project revenue donated to. I send the money to charity and share the receipt with the client. They love it. And I just don’t think I could do something like that if I got investors on board.”
Being bootstrapped, Ali does not have the funds to hire full-time employees to work on all three subsidiaries simultaneously. Instead, he’s chosen to diversify his services and pool his resources. It might mean slower growth, but at least he’s in the driving seat.
Sources:
1 Trillium Financial: https://trilliumfinancial.com/newsletters/diversify/
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