Thoughtful Friday #14: Hypergrowing Communities & Stories - Deconstructing Airbyte, Dbt, Levels
I’m Sven, and this is Thoughtful Friday. The email that helps you understand and shape the one thing that will power the future: data. I’m also writing a book about the data mesh part of that.
Let’s dive in!
Time to Read: 8 minutes
Airbyte, Levels and DbtLabs mastered two skills, community growing & movement creation
Both skills go hand in hand but can be used in separate
In the data space, both seem to become essential
Movements/market visions exist on top of company/product visions
Product vision = how does the product fit into the movement
I just read an engaging message inside the airbyte Slack channel which promptly reminded me that I had this draft sitting around. It was a simple bot highlighting the biggest community contributors to the open-source side of Airbyte.
Airbyte does two things well, they have both, hyper-grown their community and managed to spread their story. This pic puts it still quite nice.
The numbers still check out, Airbyte has 8k community members, vs. Meltanos 3k. Although compared to Dbtlabs they are still small. Dbt has a Slack community of over 31k members.
The story of Airbyte inspired me to do a deeper dive into community & story building because these two ideas seem to be related in the data space. I’ve picked three exemplary companies which IMHO perform these tasks extremely well:
Airbyte, dbt, and Levels. All of these companies seem to hyper-grow communities. All of them are very different in nature.
- Airbyte is an aggressive young data start-up, founded in 2021, now with 150M in funding and a valuation of 1,5 billion a year later.
- DbtLabs, built around the data tool coming out of a self-funded business (Fishtown Analytics) and slowly but steadily growing a huge community, now valued at 4,2 billion.
- Levels, a health care start-up giving people real-time feedback on how food affects their health, is now valued at 300 million.
Unfortunately, nobody at these companies wanted to hand over their key to success, so we’ll have to take a few guesses instead ;)
I’ll discuss a few topics which stand out at these companies. And one thing, in particular, does seem to be common across all of them:
Key Point: A strong market vision seems to use to unite the community. At Airbyte it's the “modern data integration story”, at dbt it has a distinct name “analytics engineering” and at Levels, there was a pivotal strategic shift towards “creating a movement” with serious investments.
Let us first take a look at Levels’ strong story!
Crafting a Movement
Levels is crafting a movement around metabolic health. They are doing so by investing heavily into two things:
2. Influencers in the space
According to The Generalist, the Levels blog gets 160k pageviews a month (in one particular month to be precise), and the list of influencers in the space is exhaustive.
“In speaking about Levels ability to execute on its goals, a16z General Partner, and former President of PayPal, Jeff Jordan, recalled how Corcos had explicitly outlined a plan to win over the space's most powerful influencers. When Jordan caught up with the Levels CEO a few months later, Corcos told him, "We're running out of influencers. We've got them all."”
Straight from The Generalist - Levels a Cultural Anomaly.
The same “creating a movement” spirit is present in Airbyte to a lesser degree and inside the dbt community. In Airbyte, the story goes something like this…
“ Every data team needs dozens of tools and lots of custom coding to serve as their “data stack”, whereas Airbyte with its open approach leverages community-created code that everyone can use. Go from “lots of custom coding” to “zero custom coding” with Airbyte. “
It’s the story they explored when they pivoted from their previous business idea, and it’s the story they have been telling every since, focusing on and highlighting the “number of connectors” almost every day.
Note: Airbyte has a fun animation on their homepage showcasing this exact story.
For dbt, it is the “analytics engineering” movement and the simple story that SQL is the best lingua franca of data. They are taking the community idea very seriously. They are giving up a major portion of the space on their main page to highlight it:
While Levels pushes for credibility through influencers, Airbyte focuses on the “number of connectors” and their quality of them to make their point. DbtLabs took a long time to support their story which they did through consistency over time. All strategies seem to work for delivering credibility.
Key Point: A strong distinguishing story, that is credible, for instance by being supported by the industry leaders is common across all of our exemplary companies. This isn’t just a “product vision”, it’s a true movement meant to shape the whole market. The product vision is just “how we fit into this grande theme”.
Since content is so essential across all three of these examples, let’s see what kinds of content these companies leverage to tell their story.
Creating Compelling Content
Being the most unusual in our set, we start with Levels. Levels utilize a bunch of forms of content:
Their blog Levels Health
A podcast “A Whole New Level” already featuring 132 episodes as of today
The usual social network magic with Tweets and Instagram stories and YouTube.
If we turn to DbtLabs, on top of these channels, they utilize a newsletter “The Analytics Engineering Roundup” running since 2015, that’s been specifically rebranded to focus on the “Analytics Engineering Story”. They also offer in-depth “on-demand” learning teaching an array of dbt-related skills inside specific free courses.
Airbyte offered “Weekly Bytes” as their newsletter although they rebranded it to “Monthly Bytes”. In it, they strengthen their story by offering both product news as well as stories about the modern data stack.
Key Point: All three companies use their content to back up their “movement story”, not just their product story. They are doing it consistently over time for years. They do so via podcasts, videos, blogs, newsletters, and learning courses - all focused on enhancing their distinguishing “movement story”.
But content isn’t enough right? Content is there to tell the story and make me feel part of something, but it’s not enough to get me active, active as part of a community. Let’s see what more these companies do to get people to act.
Activating the Community
The data start-up Airbyte does a particularly great job at activating the community, they got a “Writers program”, and a “Maintainer Program” and they highlight the data champions (which is basically their testimonial/use case section). They host a bunch of events, including very active events like conferences, meetups, connector creation hackathons, and many more.
A pic of the current “community frame” from Airbyte’s website.
The company shared a bit of their key to success for the slack community. They managed to build a hugely active Slack community by focusing on the response time to questions from actual users, because they rightly realized, for building communities, is not about the customers, it is about the end-users (which rarely coincide in the B2B world where they operate). They even welcomed every new community member with a personalized message.
Dbtlabs does a lot of what Airbyte does and more. They also do live Q&As with experts, which is something lots of people are looking forward to because the guys at Dbtlabs truly are the experts in analytics engineering, after all, they’ve invented it.
Putting these Pieces Together
This is not a blueprint or an exhaustive analysis, it’s stuff I noticed, these companies have in common. Let’s summarize them:
All of these companies create a story that goes beyond the company itself, a movement.
They maintain both a movement story and a company vision telling us how they fit into the movement.
They make the story credible, e.g. by talking about it in interviews for years, or by aligning 100s of influencers.
They make the story appealing and visible by creating content and content for years, consistently.
They create a passive community through this content and explicit community channels.
They then take the “passive” community and turn it into an active community.
Then they do some mystery magic to create a lasting business on top of that, but that part is still kind of missing… Yes this is still work in progress…
Companies don’t need to tell stories or create communities to be successful in general. But I’ve come to the conclusion that in the data space, creating or participating in a great story is indeed crucial. And since open source is all around the data space, community-building skills or companies are becoming ever more important. You might just need one of these two skills, you might use them in combination or separately, either way, I feel these skills and these three companies offer a lot to learn for the data space.
How do you feel about that?
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