SaaS Winners and Losers, AI Pricing & Efficient Growth
My "SaaS Perspectives" Interview w/ Bowery Capital
I recently sat down with Patrick McGovern at Bowery Capital to chat all things SaaS, the impact of AI, and what that means for building a valuable business.
As always would love to hear your thoughts!
This was originally published on the Bowery Capital Blog.
SaaS companies have underperformed broader technology stocks (and especially AI-related companies) in 2024. What is going on in SaaS right now?
Simply put, 2024 is highlighting that there will be relative winners and losers in SaaS. We’re in the heat of Q2 results, but here’s how I would synthesize Q1: Companies like Workday and ServiceNow (the bellwethers of SaaS) reported longer lead times, deal scrutiny, and shrinking deal sizes. Bespoke put out a great tweet that CRM missed consensus revenue estimates for the first time since February 2006 (73 quarters). On the opposite side, we saw the hyperscalers report their first revenue growth acceleration in a long time, but still with more muted growth performance from the big usage-based names (SNOW, DDOG, CFLT, MDB)... showcased by MDB falling 24% the day after it reported earnings. While that sounds bad, there are clearly relative winners as well. And I see two main ones: 1) Anyone focused on selling picks and shovels for AI seems to be winners (mainly hyperscalers) and 2) cyber security… with the added qualification that you must be a best-in-class platform to be winning share.
I think it's safe to say we are in a moderately growing IT spending environment… some would say a “tight” environment but I have seen low-single-digit growth across a number of surveys. Is this slower than prior years? Yes. Is this closer to “normal” growth rates? I would also guess yes plus or minus some margin of error. In this type of environment, CIOs and CFOs are going to prioritize projects within their budgets - not expand their budgets to fit their priorities. In fact, this is a normal dynamic for any vendor / customer relationship - software just isn’t used to it. AI is clearly a priority across all organizations and it is one of the few projects that are likely mandated and pushed by the board and CEO level. These will obviously take priority in the CIO budget and the question is this incremental spend or taking share? The MS CIO survey said it was 50/50, but maybe recent results are suggesting it’s more shifting than incremental.
I would expect cyber security to remain a top spending priority for at least the next few years given the increase in quantity and sophistication of threat actors (also boosted by AI), increased regulations and disclosure requirements, and the growing perception of the downside of breaches (operationally and from being made public). The cyber security market seems to be a few years behind software in terms of moving towards platforms and CFO deal scrutiny given the added technology complexity, but it does seem like buyers are becoming more discerning here and will likely trend in that direction in the future.
How do you think about AI companies and their attempts to price their products in terms of efficiency gains (i.e., we will save you the work of three people)? This can lead to ACVs way beyond what many of these software companies previously commanded.
I’m in the camp that AI will have massive societal impacts long-term, but how that plays out near-term in terms of economics beneficiaries and timing remains highly uncertain. There’s a few obvious use cases with various levels of complexity, timing, and potential ROI.
The easiest and most-common is giving your employees a “copilot” to become more efficient. Microsoft Office is obviously one of the more common options given the ubiquity of the office platform. The return on Office Copilot still seems uncertain, however, the ROI seems much clearer if you’re on the coding side but only for coding problems that are easy to solve and don’t require novel solutions. As part of that, I would include enabling sales and marketing as well. Using AI to enhance marketing ROI seems like an obvious use case. Using GenAI to enhance outbound sales seems like another.
I would say the 2nd layer is automating repeatable, low-value operational tasks which are currently completed using employees or BPOs. Many investors have been labeling this group the “process layer”, which helps clarify it as a system that automates a specific process, not a general use robot designed to replace a human 1:1. It’s hard to measure how many processes (and therefore man-hours) could be replaced using this methodology, but there seems to be clear use cases in customer success and document processing with usage beginning to creep into traditionally more “white collar” corporate jobs such as legal and finance.
The 3rd layer is the most valuable, but the most nascent and hardest to implement — thus the most uncertain ROI. This is using AI to independently drive results and generate new insights. Many of the most beneficial use cases require allowing AI to not only access a significant portion of your data estate but also allowing AI to automatically and independently edit the data and systems without human intervention. If you ask any C-suite executive now, few are comfortable giving the necessary access to their data estate to fully unlock the potential here.
How each of these flush out in terms of economics and pricing remain uncertain with the big platforms being the only clear beneficiaries so far. While platforms can command an AI premium, many verticals will need to incorporate AI functionality just as table stakes. There will undoubtedly be some large companies in the 2nd layer especially those architected to be AI native and can scale to be a broader platform. Unlocking the 3rd layer would likely allow companies to capture incremental economics but data governance and security concerns as well as broad integration requirements still suggest this bucket is well off in the future. Like many nascent industries the net benefit to customers will likely outweigh the net ROI of the vendors until mass adoption is reached which makes choosing the winners as investors very cloudy.
From your perspective, what are the most significant challenges facing Enterprise SaaS companies in achieving scalable growth? What strategies do you believe are most effective for SaaS companies looking to expand into new markets or verticals?
Durable growth has been the topic du jour lately with the discussion of growth vs. profitability a close second. Both of these have replaced the growth at all costs mindset we saw during the COVID / ZIRP period. I think it is important to frame this question in the framework of growth and ROI. I think what has really changed and what has historically been missing from SaaS companies is a focus on profitable growth. Normally how investors express this sentiment is saying they want you to be profitable. This high level view is fine when the situation is dire and the operating executives and investors don’t have a better methodology. But the reality is that you need to be efficient, and preferably ruthlessly efficient, in each of your growth curves.
What does this mean? When you develop a new product you need to invest significant R&D expense upfront to build the product from scratch and this might continue for a few years as you add major new features and especially if you’re building a new category. Eventually (this might be 3 years or this might be 10) you should end up with a product which is competitive and stable with only incremental fixes and additions needed going forward. Maybe this means 100 engineers were needed to go from 0-9, but only 10 are needed to go from 9-10. Realizing where you are at in the product cycle will guide you on how and when to shift resources to the next growth priority.
A similar exercise also needs to be continuously happening in your GTM motion. At its most basic level, there are account executives who are closing deals and then support teams helping and enabling them (there are also ops and partner teams which we will leave out of this for now). Account executives are well known to operate on a power law and also take time to ramp up to full productivity. These tend to be more significant variables as you get into larger, enterprise contracts. There are a few primary metrics you want to track to assess GTM efficiency including average productivity, ACV/OTE, and support ratios. You should also do this by customer segment, region, and any other way you can think of, to make sure different splits are comparable. If they are not - it is time to look at pruning low performers and ensuring support ratios match those observed in your most profitable segments. At a higher level, you can also look at “Cost-to-Book” which was pioneered by John Cummings at Salesforce which is simply S&M / new ACV.
So how do you operate within this efficiency framework that I am describing? First of all, you need to have a strategy and a plan to execute your strategy. There are many ways to win as a software company - the most important part is to build a strategy which is expected to win in your respective competitive environment. Second, you need to match your internal investments to that strategy and its expected outcome. A lot of the issues we are seeing now is an outgrowth of a mismatch between investment/spend with growth prospects, as well as a mismatch between how the allocation of that spend has been apportioned towards maintenance vs. growth in the organization. Another part of this efficiency framework is assigning risk levels to outcomes and understanding which are higher-risk bets vs. more sure things and to make sure the potential outcomes are compensating you for the risk you are taking. Companies need to answer those questions for themselves on a case by case basis and the answer will differ depending on many circumstances, but this framework can help answer the questions of product line vs. platform vs. new market, etc. (i.e., should you be hiring incremental AEs to add capacity to a current geo/segment line vs. launching a 5-year R&D effort to build a whole new product).
You have written some great stuff on your blog where you take a “DCF for Dummies” approach to help the tech crowd better understand the drivers of company valuation - what is your prediction on multiples and interest rates over the back half of 2024 and into 2025?
If I could predict interest rates and multiples I would be in a different business. But seriously, as an investor-facing operator, it is part of my job to keep a tight pulse on interest rates, industry multiples, and other market drivers and also help my boss/CFO and the broader executive team and company understand those.
I would also say that no matter what is going on with interest rates, market multiples, and the relative valuation of any specific company, the only way to increase the true value of your company is to build a plan for long-term FCF generation, have investors believe in and buy into your plan, and execute against it. Everything else is just noise. So within that framework we try to keep everyone updated on the latest in capital markets trends as in many cases that can drive real business impacts while still staying grounded that long term the dog wags the tail.
All that said, interest rates have a real (fundamental) and relative (valuation) impact - especially on high-growth, FCF burning software companies. When interest rates are low, this is generally considered to support the economy and improve executive confidence, which increases long-term investments with software being one of those investments. Many of the companies buying software today are themselves software companies which benefited from expanding budgets due to loose VC funding. This environment also seemed to create pull-forward demand which the industry is now realizing with hindsight and digesting. While difficult to see in real time, companies were also investing in talent while underwriting these temporarily favorable growth economics and likely doing so inefficiently due to easy access to capital. The industry is working through all these misallocations now, but I would generally expect future interest rate impacts on fundamentals to be much more muted with industry demand more driven by customer needs and ROI, and market share being captured by the companies with the best execution within their given verticals.
On the valuation side, changing interest rates impact valuations due to how a basic DCF formula is structured. All else equal, the higher your discount rate (which is in part based on treasury rates), the lower your valuation will be. If a large part of your company’s value is based on FCF well out in the future, then interest rates will have an outsize impact on your relative valuation. This turns into a fundamental impact when you are trying to raise money and/or IPO as your valuation will likely be pegged to an industry EV/Revenue multiple and adjusted for your relative growth rate (and more and more your relative economics). I wrote a post, Interest Rates and SaaS Multiples, that goes into more detail on the interplay of interest rates and valuation.
You write a lot about public scale B2B software companies - is there one you particularly admire at the moment in terms of how they run their business?
I try to be very explicit with never recommending companies as investments but instead try to understand how internal strategic decisions and external communications translate to fundamental performance and how I can learn from best-practices in the industry.
Within that framework, I like to look at Datadog a lot (I wrote $DDOG: Derisking the Growth Story highlighting what they do right). Datadog made a massive investment in their platform which was wildly unpopular with investors at that time, but has now translated to R&D agility, sustained NRR, and ultimately durable revenue growth (at least so far). They were also one of the first companies to benefit from the usage-based pricing strategy which paired well with the easy expansion capabilities built into your platform. In addition, they always have clear communications on what their product does, the pain point it solves, their product strategy and how these will combine to drive future growth. All of this has been in plain english (which tends to be lacking in a lot of tech) so it’s easy for investors to understand and ultimately underwrite in their valuation models.
I would also note this clear communication helps current employees understand the direction of the company and helps attract future employees who can understand the drivers of the company and get excited by its prospects.
In addition to your great newsletter, you also have a day job. As a growth stage finance professional - what are some of the biggest lessons you’ve taken away from the last 24 months?
I think the biggest thing I have learned is to always learn new lessons! I obviously spend a lot of my time observing other companies, investors, and operators and the blog has been a great way to not only meet these people, but also share my learnings. It also makes me better at my job which is helping map strategic decisions to our long term model and ultimately planning and preparing a successful exit for our investors and employees. While cliche, finding the right team can not be understated. The competition is tough, the job is tough. Finding a team that works hard and you enjoy being around and building things with is very important.
I’m also working on a new side project and it's my first time working with someone to own and build my own piece of software instead of just analyzing someone else's. It’s a competitive intelligence platform which aggregates news and delivers insights to investors, investor relations, strategy/corp dev, account executives, and competitive intelligence teams. I use it every day to keep track of industry news and competitive releases and now I am looking for some early adopters to help me grow! You can learn more about what I am working on at https://app.breakingsaas.news.
If you liked “SaaS Perspectives: Thomas Robb (Hard Mode by Breaking SaaS & SaaS News)” and want to read more content from the Bowery Capital Team, check out other relevant posts from the Bowery Capital Blog.