Andy Cloke Shares How He  Grew Data Fetcher - a No-Code Tool for Airtable - to  $8600  MRR
Andy Cloke Is the founder of Data Fetcher - a tool to import data from anywhere into Airtable with no-code.

Tell us about your product and what inspired you to start it?

I was trying to build an IPO alerts newsletter and manage the content from Airtable. I found an API with data about IPOs but there weren't any simple ways to connect to this in Airtable.
A couple of months later I was browsing Product Hunt and saw a successful Google Sheets extension called 'API Connector', which let you connect to any API within sheets. I remembered my Airtable pain point with the IPOs use case and decided to build an equivalent extension for Airtable.
It was great timing - Airtable were just opening up their extension marketplace to any third-party developer. So Data Fetcher was one of the first extensions on there, and I've been riding the no-code/ Airtable wave ever since.

How long did it take you to acquire your first 50 customers, and what was your growth strategy?

It took about six months to reach the first 50 customers. Initially, I launched on forums, Product Hunt, Reddit etc. which got a handful of users.
Being early to a marketplace like Airtable means you get a handful of new users each day, even without doing any marketing. I think a big factor in converting these people was choosing a freemium pricing model. Some people would try Data Fetcher out on the free plan for months, then finally convert when they had a concrete use case.
A few months in, I realised Data Fetcher wasn't going to grow properly unless I found a more scalable marketing channel. As for many bootstrapped products, this turned out to be SEO. Specifically, I would take common Data Fetcher use cases and create YouTube videos & written tutorials.
Today, 30%-40% of my customers come through our YouTube videos or blog posts, and this % has steadily increased. The interesting thing is the number of views on the videos/ blog posts is tiny (e.g. <1000 total views for most videos), but the intent is super high, so the conversion rate is high.

Which technology stack are you using and what challenges and limitations does it pose?

The backend is written in Node.js, TypeScript, PostgresQL, GraphQL and hosted on Heroku. The frontend is React.js, TypeScript and Airtable's Blocks SDK.
I chose this stack because I was already familiar with it, which is the approach I'd advise anyone to take.
There haven't been any serious limitations, but there have certainly been some Heroku growing pains, now that Data Fetcher users are doing 10,000s of runs (an import/export) per day. I've had to upgrade Heroku servers/ database in a hurry and add lots of monitoring to try and see this coming.
The backend relies on Airtable's REST API. It's solid enough but has some quirks I've had to build around. e.g. it uses names for tables rather than ids, which means when a user changes a table name their scheduled runs start failing. So gracious error handling and alerting the user has been very important.

What are some of the most essential tools that you use for your business?

  • Airtable, obviously - I use the kanban view for my product backlog and content marketing pipeline.
  • Sendgrid. I love their dynamic templates feature for sending transactional emails
  • Mailerlite for email newsletters
  • PgMustard for understanding slow database queries

What have been some of the biggest insights you've gained since starting your entrepreneurial journey?

The big one was doing more user testing. i.e. give someone a task to do in your app and watch them do it. It sounds obvious, but there's a lot of advice that says 'Don't talk about your product, just talk about people's problems', and I'd kind of taken that too far and was just speaking to users at quite an abstract level. Once I started doing more nitty-gritty testing of the actual extension, the UX improved immeasurably.
The next thing is that it's often better to focus on keeping customers than trying to find new customers. This means doing boring stuff like fixing edge case bugs, improving error messages and writing help docs. The combined effect of making dozens of minor improvements to your product means your bucket becomes less leaky - customers stick around longer.
The last thing is that it's easy to procrastinate on a big feature because it seems intimidating, even though it's actually very achievable. This has happened a few times, e.g. with my recent webhooks feature. The best strategy I've found to avoid this is to do a quick technical spike (investigation) of big features that are commonly requested, so you can properly estimate them.
Books: Range by David Epstein, Lost and Founder by Rand Fishkin Podcasts: Startup to Last, Nathan Latka, Cartoon Avatars

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