In 2020, Azul, the largest independent Java vendor, received a strategic growth equity investment from Vitruvian Partners – the catalyst for its corporate development strategy. Azul solves a variety of customer challenges, such as optimizing cloud costs, powering performance-driven applications, providing an alternative to Oracle Java licensing costs, and delivering security. Finding the right companies who can add value to its product portfolio is a major priority.
George Gould joined Azul in 2009 to help aid the company’s transition from a hardware and software vendor to a pure software company. Gould ran marketing, product management, and business development. In 2022, Gould transitioned to SVP of Corporate development to help find additional ways for the company to grow.
“As the predominant open source Java vendor, we’re always looking for ways to expand market share and complement our existing product lines, ” said Gould. “Acquisition of the right company is a viable strategy to achieve those goals. It’s all about strategy, structure, and fit”
The Azul team had a good understanding of their competitors but they needed to be able to map the bigger picture of technologies and companies available in the US middle market. Web search engines were insufficient to quickly identify companies of interest that fit Azul’s ideal company profile (ICP).
The problem: Azul needed a very specific search tool which allowed them to perform keyword searches such as “DevOps” “CI/CD ” and “Developer Productivity” and return a result set that could be further refined by Azul’s ICP (e.g. company size and funding level) into a readily consumable list of companies.
"To produce a manageable list of targeted companies that fit our ICP, we needed a tool that could combine key information from multiple sources, including LinkedIn for employee information and Crunchbase for funding data.”
Web searches were hit or miss and there was never a single profile that contained all the initial information Gould needed to understand a company’s relevance to Azul. Each search meant at least 2 more searches on LinkedIn and Crunchbase with data that was only partially reliable.
Azul needed a more streamlined process – a search engine that showed relevant results and included company profiles with basic information like sector, location, and size.
Grata is a deal sourcing platform that allows dealmakers to search 9 million companies by keyword. The value Azul found right away with Grata consolidation– a single view of a company that aggregates public data and blends it with Grata’s algorithm to allow dealmakers to filter quickly and accurately.
“It’s a great start to know immediately, company X is 800 people, which is currently outside our ICP. Or to see Company Y just got another round of funding, so they're on pre-IPO run. It’s critical that I can apply a quick filter on a large result set that initially returned hundreds of companies and reduce it down to a handful of companies of interest that I can save and perform deeper analysis.”
How valuable is that kind of time saved? For Azul, Grata replaced a full-time employee’s salary.
“When we first started the search process, I believed sourcing was going to be a very time-consuming process; one that would likely require a dedicated team member to filter 100s of companies through our ICP.”
With Grata, Gould did not need another sourcing resource. A process that Gould anticipated taking days could instead take hours with Grata’s Filters, Signals, and Similar Company Search.
Gould believes sourcing must be highly efficient to reduce the impact of vetting new opportunities across the different Azul teams.
“You need to be diligent in refining your targeted list, which requires continuous filtering and refinement at the top of your sourcing funnel. Vetting new companies impacts our greater organization from our executive team to our product managers. Sourcing efficiency is everything.”
“Before, I could spend a whole day filtering a list of 500 to 50. With Grata, I can start a search with 50 and quickly get it down to 5 companies. The difference is I'm not spending all of my time trying to find the basic information I need to know to deduce how good a fit a company may be for Azul. I can start with a very good list and then pinpoint exactly what we’re looking for.”
The data that Gould uses to evaluate ICP fit is very specific and meaningful. The ability to add and subtract quickly out of our tracker is a huge perk of Grata.
Two filters used most often by Gould are the “Ownership and Funding” and “Employee Count.” The Ownership and Funding filter allows Gould to quickly eliminate the late-stage funding and Pre-IPO companies with a few clicks rather than hours of searching Crunchbase. Knowing the estimated employee count is essential for Azul to estimate revenues and burn rates.
“Grata’s greatest value is the ability to filter down to something that's truly manageable that allows you to then go to the next step of technical due diligence.”
2022 is shaping up to be a very different market than 2021, a little reminiscent of 2009 where going public is very difficult for companies and even well-funded companies may not have the business models to secure their next round. This is impacting private companies acquisitions as well. Funding is not as rampant as it was in 2021. As such, Azul’s ICP is continuously evolving with market conditions to reflect the macroeconomic changes.
At the start of 2021, Azul’s goal was to track approximately 50 companies. With the changing economic conditions and ability to rapidly change Grata search criteria they are tracking over 100.
“For every company of interest that we’re tracking with the Grata tool, we’re constantly monitoring funding events and changes in headcounts to identify new opportunities and acquisition timing.”
Grata’s UI makes it easy to maintain lists. “On a regular basis I’m pruning our lists and replacing companies of interest with better prospects, but you can only do that with a tool that constantly gives the ability to refine your search criteria. Otherwise, you're just overwhelmed with data.”