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Subscribe now “Grouping + AI” for Triage One area I’m quite excited to see AI revolutionize is “grouping + triage” workflows. Many of them AI based. They each have some of the largest cloud businesses in the world in AWS, Azure and Google Cloud respectively. Follow along to stay up to date!
Subscribe now Azure Report - Cloud Infra Looks Good! For software, all eyes were on Azure - which grew 31% YoY (ahead of expectations closer to 29%). Azure doesn’t disclose exact Azure quarterly revenue (they disclose growth rate in absolute terms and in constant currency), but there are good estimations.
net retention and CAC payback). It’s worth pointing out that Azure is a bit above the long term trendline, while AWS is still below (but accelerating up). Net Revenue Retention High net revenue retention is the fourth aspect of a successful quarter, and one of my favorite metrics to evaluate in private SaaS companies.
With a PLG-heavy background, first working at Microsoft Azure and again with Atlassian, the PLG pioneers, he gives insights into leveraging PLG for the growth of your organization. It’s an end-user-focused growth model where your product drives acquisition, activation, expansion, and retention. Leverage AI to assist sales.
If it wasn’t clear before, AI is the single biggest revenue driver in cloud. Microsoft’s Azure is winning share directly from Amazon. ” Much of the AI spend is at the enterprise, where a 50% reduction in customer support cost or a 75% increase in engineering capacity filters billions to the bottom line.
Enterprise software businesses strive for 90-95% gross retention (generally the percent of revenue that sticks with you vs churns altogether), with net expansion in the 120%+ range (the aggregate change in expansion - contraction - churned revenue). Namely, retention!! For “fake” ARR, retention can vary wildly.
AI companies] have a real use case for the cloud which is somewhat different than what we see from some other companies. Today, our largest R2 customer is another AI company using us for exactly the purpose of being a neutral place to store their training data.
Subscribe now Cloud Giants Report Q3 ‘23 Not a great signal for software this week from the Cloud Giants (AWS, Azure and Google Cloud)…After Q2 (3 months ago), the tone from the Cloud Giants around optimizations was largely: optimizations have started to ease, and net new workloads have picked up. Staggering scale already.
” Microsoft on Azure : “And I think last quarter, we said one, we are going to continue to have these cycles where people will build new workloads. So what you're seeing is much more of that continuous cycles by customers, both when it comes to AI or whether it comes to the traditional workloads.”
net retention and CAC payback). Who are the real AI winners. It looks at the YoY dollar change in quarterly revenue from the hyperscalers (just looking at Azure / AWS because the data goes back further) going back a few years. Is Software Rebounding? The first few months of this year felt like a lot of churning in the market.
Cloud Giants Report Q2 We also got the Q2 quarters from AWS / Azure / GCP this week! Our expectation, obviously again, is that we are going to significantly increase our investments in AI infrastructure next year, and we'll give further guidance as appropriate.”
This can lead to an airpocket of valuation as companies transition to a different primary valuation metric Outside of the hypserscalers (Azure, AWS, GCP) who have uniquely benefited from AI revenue (mainly selling compute), everyone else has largely struggled. Coming in to Q1 there was broader optimism. Q4’s were generally good!
Hyperscaler Preview Next week Amazon, Microsoft and Google report earnings and we’ll see Q3 data for AWS, Azure and Google Cloud. These are thought to be the early AI winners, largely due to all of the compute they’re selling to power GenAI applications.
Subscribe now Foundation Models Are to AI what S3 was to the Public Cloud Many people look at 2006 as the birth of the public cloud - the year Amazon launched AWS. Microsoft launched Azure in 2010, and Google launched GCP to the public in 2011 (they launched a preview of Google App Engine in 2008, but made it publicly available in 2011).
Expansion revenue is still declining (we see this in falling net retention rates), but gross retention remains strong. Usage on Snowflake is driven by queries run on Snowflake Azure: Neutral Tone With Strength in AI Overall I’d characterize Azure’s quarter as a net positive.
When I think about the monetization of AI (and which “layers” monetize first) I’ve always thought it would follow the below order, with each layer lagging the one that comes before it. Model providers (OpenAI, Anthropic, etc as companies start building out AI). 2024 will be the year of AI applications!
AWS (Amazon), Azure (Microsoft), and Google Cloud (Google) all reported this week. Azure reported on Tuesday and gave us that glimmer of hope. Azure : Coming into the quarter, a growth rate that would have satisfied the market would have been ~29%. Azure came in at 31% (constant currency). Follow along to stay up to date!
So far - you’re either tied to AI tailwinds, or it’s rough out there. And in the public universe, it’s really only been the hyperscalers who’ve benefited from AI. We’ll see if anything improved in the month of April, or if it was another challenged month.
AI = Data + Compute I’ll continue beating this drum, but we got two great quotes from Azure and AWS this week. Satya at Microsoft said “Every AI app starts with data and having a comprehensive data and analytics platform is more important than ever.” Subscribe now Busy week! AWS reports next week.
The good news is gross retention (ie churn) stayed constant. If next quarter we get similar commentary that Azure gave us this quarter (“still a couple quarters away” without any specific guidance), then we may see market loose a little patience. And everyone hoping for AI acceleration will need to wait.
Why retention isn’t just a CS metricand how to build a sales team that cares about it. The revenue leader needs to have an overwhelming amount of focus on retention. Rudimentary AI to, to then be able to extend it extensibility that you can bring to other apps. Appreciate y’all hanging out with us for the next hour.
While we aren’t going 100% usage-based overnight, if you look at some of the mega-trends in software—things like automation, AI, and APIs—the value of a product normally doesn’t scale with more folks logging in. And of the IPOs over the last three years, seven of the nine that had the best net dollar retention all have a usage-based model.
We have companies like BuzzFeed and C3 making loose announcements about how they will incorporate generative AI into their business, sending their stocks up 50-100%+. In the short term, enjoy the ride as the chase continues 😊 Kind of related to all of this - we now have seen the Q4’s from AWS, Azure and Google Cloud.
Equipped with such knowledge, you can onboard them more effectively and drive engagement to increase adoption and retention. It enables you to collect user feedback and track their in-app behavior to gain granular insights into their needs and preferences. Dedicated NPS analytics , including qualitative response tagging NPS dashboard.
Appcues enhances user onboarding, adoption , and retention with targeted walkthroughs, in-app messaging, and feature adoption tools. Key examples are Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform, which provide scalable resources like virtual servers and storage. What are the benefits of the SaaS model?
Qualaroo helps you collect customer feedback and measure customer satisfaction with AI-powered sentiment analysis. Integration: This user feedback software offers integration capabilities with popular services like Slack, Azure DevOps, and Zendesk. AI-powered Tools: It leverages AI-powered tools to help you effectively manage feedback.
Running your own server to handle your customer's valuable data requires a huge investment to match the same level of security and reliability that comes baked into services like Amazon AWS and Microsoft Azure cloud. AI Integrations. Double down on retention. As such, many SaaS businesses are opting for the latter. Offer tiers.
Either way, a decrease in attrition could be achieved using digital retention methods and an improved customer interaction site. Besides, their data professionals could develop comprehensive data strategies, deploy sophisticated analytics, and use AI to acquire deeper insights.
Azure has been gaining on them rapidly and is growing a double that rate. What we’ve built is this core AI machine learning engine that takes literally millions and millions of unique sources so that we can deliver 95% accuracy to our clients. If you look at the IAS vendors, they passed $130 billion revenue milestone this year.
The ultimate failure of Siri to dominate the AI personal assistant game might come to be seen as its biggest miss of the decade. The wave of SaaS companies that built themselves on the likes of AWS and Azure have reinforced the pre-eminence of cloud computing.
This will be a really strong indicator of retention and recruiting. Five people in the digital team were looking at blockchain projects and three people on that digital team were looking for long term AI transformation. Aaron Levie: Everybody had their digital team. So, that’s effectively what we’re working on.
AI Commentary Some interesting AI commentary / stats I wanted to highlight from a couple earnings calls this week Microsoft on AI “We're excited that only 2.5 years in, our AI business is on track to surpass $10 billion of annual revenue run rate in Q2.
From AI-driven applications to automation that slashes tedious tasks, SaaS solutions are becoming smarter and more efficient by the day. Well, AI and machine learning (ML) are making it a reality. In 2025, AI is supercharging SaaS applications, making them more intuitive, predictive, and flat-out smarter. Lets break it down. (A)
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