Ending its first year as a publicly traded company, Confluent appears to be firing on all cylinders as the vendor delivered a strong set of fourth quarter results and beat analyst expectations.
Confluent's solid cloud numbers and the growth in the number of large contracts suggest that the vendor's ‘data in motion' offering is resonating with buyers.
Spun out of LinkedIn in 2014, Confluent is built upon Apache Kafka and allows companies to take advantage of real-time streaming data. As CEO Jay Kreps explained to diginomica last year, the digital enterprise can't rely on historical, stagnant data and needs to utilize data streams in real-time.
And this message is delivering results. Revenue in the fourth quarter totaled $119.9 million, representing growth of 71% year-over-year, a further acceleration from Confluent's 67% growth last quarter.
Furthermore, revenue from Confluent Cloud in the fourth quarter grew 211% year-over-year, significantly outpacing the growth of its overall business. Confluent Cloud now represents 28% of total revenue, up from 26% last quarter and 15% one year ago.
Kreps told analysts that Confluent Cloud is now "the most significant focus" of the company's go-to-market engine. Kreps added:
A fundamental driver of this growth is the rise of data in motion as a foundational underpinning for a company's success in digital transformation.
Tech disruptors are building around real time data streams to deliver rich digital customer experiences and are setting the standard for customer expectations.
Mainstream enterprises are quickly realizing that their ability to harness data in motion is key to their survival as this is at the heart of the customer experiences and operational capabilities they need to compete in the modern digital world.
Customer success as a foundation
Kreps used the analyst call this week to provide some interesting detail on Confluent's go-to-market strategy, which I think is worth highlighting. He noted how the data infrastructure world is currently transitioning to a consumption oriented model, similar to that of software-as-a-service.
Kreps added that this is crucial for Confluents' customer journey and for the company's future success. It all starts with enterprise developers, where he said:
Adoption of data in motion often starts with developers in the early phases of product experimentation. At this stage, being low friction and building developer love are the keys to success. A product needs to be available for instant usage, with all the needed features and the least amount of hassle. Stopping to try to plan out the structure of a large deal or negotiate pricing at this early stage would serve little purpose and slow down the development cycle.
And then as technical projects move towards production, new needs arise. Kreps added:
Are the security, availability, connectivity and compliance needs met? Is there a predictable pricing that is economically attractive? In this phase, it's important to provide the customer with the qualifications and assurance they need to depend on the service as a mission critical part of their infrastructure stack. Succeeding in this phase involves satisfying multiple economic and technical stakeholders.
This phase is then followed by customers transitioning to multiple projects, which begin to merge. Kreps said:
It goes from being an ingredient in one project to a layer connecting many such projects. There's a natural network effect for data in motion that helps drive this expansion and the progression between these stages.
These streams go between applications. Our customers add streams to the platform, unlocking value for that use case, but also attracting other applications that need to tap into these streams. Hence the virtuous cycle of adoption is the applications bring incremental data streams with them, which in turn attract new applications that need that data, which in turn bring new streams of data, and so on.
This journey is truly unique to data in motion because of the natural virtuous cycle and network effect that comes from the sharing of data in Confluent.
Why is this important? Well, Confluent is bringing together a variety of tactics suited to each of the different stages - which suggests it has a firm understanding of what customer success really means. And it is creating a funnel that leads to larger deals being down the line. Kreps said:
Self-service signup and adoption as well as open source downloads help developers get started in a low friction way without requiring any contact with sales. This is often done with free credits or in a pay-as-you-go model that lets them start quickly and with low risk.
In 2021, the traction of our self-service cloud adoption helped us grow our customer base 65% year-over-year to approximately 3,470 customers. Our sales team engages early in the customer lifecycle to help customers that are progressing towards production to ensure their needs are met. Our customer success focus starts on day one.
As a customer's project becomes part of production operations, they would likely move to a committed contract, which they would lock in in exchange for discounts. The best proxy for customers in this stage is the count of customers $100k or greater, which grew 43% year-over-year to 734 customers.
Our team then engages to help the spread to additional use cases and teams to ensure that data in the platform is widely available, and that there's top level buy-in for the larger architectural role that Confluent can play in the organization.
In fact, Confluent's later stage customer base is growing and the company now has 88 customers paying over $1 million (a 57% increase year over year). Kreps added:
We believe this customer growth go-to-market model is a significant competitive advantage.
I wanted to go over this customer growth go-to-market model in some depth because it continues to be an area of ongoing effort and investment for Confluent, and we think it will be a critical moat.
We continue to work to develop easier, low friction adoption at the beginning of the journey, easier, more transactional project level sales for the middle, and best-in-class enterprise sales and customer success capabilities at the end, each supported by the right product capabilities for that phase.