Dynatrace targets the 1,500 biggest enterprise companies after IPO boost

After seeing its shares pop 49 percent on its stock market debut, the SaaS vendor is targeting the biggest enterprise customers with its AI-powered platform

€ Dynatrace

Dynatrace is riding the wave of a successful first day of trading after its initial public offering (IPO) last week, with plans to invest this cash injection in repaying debt, growing its sales and marketing functions and expanding its AI-powered monitoring platform into new areas.

Originally founded in Austria, the Massachusetts-based application performance management (APM) software vendor floated on 1 August, with shares jumping 49 percent on debut, helping the firm — which is majority owned by the private equity firm Thoma Bravo, for now — to raise $570 million. This valued the company at $6.7 billion. For context, rival vendor New Relic has a market cap of $5.1 billion at the time of writing.

Dynatrace has spent the past few years under CEO John Van Siclen, and upon the recommendation of cofounder and CTO Bernd Greifeneder, moving the company to being a software-as-a-service (SaaS) provider, and this is reflected in the numbers. Subscription revenue for 2019 was $349.8 million, which represents 81 percent of total revenue, up from 57 percent in 2017.

The vendor has since expanded beyond just monitoring the health of applications to more business insights, with its SaaS platform utilising "artificial intelligence at its core and advanced automation to provide answers, not just data, about the performance of applications, the underlying hybrid cloud infrastructure, and the experience of our customers’ users," according to its S-1 filing.

That being said, the vendor also outlined the risk factors in that same S-1 filing: "Market adoption of software intelligence solutions for application performance monitoring, digital experience monitoring, infrastructure monitoring, and AIOps is relatively new and may not grow as we expect, which may harm our business and prospects."

The company’s total revenue for 2019 was $431 million, but it shifted from a $9.2 million profit in 2018 to a $116.2 million loss in 2019 as the company migrated to the cloud and upped its go-to-market efforts.

"This is truly only a milestone and we only see more of a responsibility to continue reinventing ourselves, innovating and creating value for customers," Bernd Greifeneder told Computerworld.

Market opportunity

Dynatrace pegs its annual addressable market at $18 billion, according to the vendor's S-1. "We calculated this figure using the largest 15,000 global enterprises with greater than $750 million in annual revenue, as identified by S&P Capital IQ in February 2019," it details. "We then banded these companies by revenue scale, and multiplied the total number of companies in each band by our calculated annualised booking per customer for companies in each respective band. The calculated annualised bookings per customer applied for each band is calculated using internal company data of actual customer spend."

Dynatrace had 1,364 customers at the time of the IPO, but will continue to target "the largest 15,000 global enterprise accounts," according to the document.

The risk factors section of its S-1 added: "Expansion in our addressable market depends on a number of factors, including the continued and growing reliance of enterprises on software applications to manage and drive critical business functions and customer interactions, increased use of microservices and containers, as well as the continued proliferation of mobile applications, large data sets, cloud computing and the internet of things."

Analyst firm Gartner predicts that global IT operations software spending will grow to $37.5 billion in 2023 and that enterprises will quadruple their APM use to reach 20 percent of all business applications by 2021.

What next?

Now with a capital infusion of $570 million the vendor will seek to write down some of its debt. However, Mike Maciag, CMO at Dynatrace told Computerworld that the firm will also focus on expanding its platform, continue to invest in development, build its sales and marketing reach, and retire debt.

He added that this week's IPO is "really a culmination of what we have been doing for the past five years and the change in the market we have seen. Five years ago we saw the enterprise cloud coming and the implications would be profound," he said, "so we took the bold decision to reinvent our product from tools, to an all-in-one platform that goes beyond APM," with AI-driven insights on top.


Dynatrace identifies AppDynamics — which was acquired for $3.7 billion by Cisco just days before its own planned IPO back in 2017 — Broadcom and New Relic as rival vendors, as well as infrastructure monitoring specialists like Datadog and Nagios, digital experience management vendors Akamai and Catchpoint and the big cloud providers Amazon Web Services, Azure and Google Cloud Platform.

AppDynamics in particular continues to invest in AI and machine learning to expand its APM tools into a “central nervous system of IT”, as the vendor puts it. This signals a broader market shift towards AI-powered monitoring platforms, which Dynatrace markets as its 'software intelligence platform'.

Read next: AppDynamics turns to automation and AI to expand APM offering

All of these vendors are locked in a battle for AI and machine learning talent as they vie to bring customers the most 'intelligent' analytics platform.

Dynatrace, naturally, claims that its approach to AI is unique amongst its competitors however. 

As Bernd Greifeneder explained in a press release earlier this year: “Four years ago, we pioneered, and continually improve, a unique, deterministic approach to AI that enabled customers to simplify enterprise cloud environments and focus more time on innovation. Because Dynatrace auto-discovers and maps dependencies across the enterprise cloud and analyzes all transactions, our Davis AI engine can truly causate, and drive to the precise root cause of issues versus simple guesses based on correlation.

"This concept just got even better through semantically enriching external data and mapping it to our real-time topological models. In addition, unlike other solutions, it doesn’t require learning periods, making it effective for highly dynamic clouds."

Copyright © 2019 IDG Communications, Inc.

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