Dan Balcauski

Why some SaaS companies 🚩 struggle to grow on cloud marketplaces? These 5 root causes may not be what you expect. 1️⃣ Strategic Cloud GTM Misalignment The most critical blocker isn’t technical—it’s strategic. Many companies treat cloud marketplaces as "just another channel," but success demands a fundamental GTM shift. Winning in cloud marketplaces requires embracing a partner-led, customer-centric, consumption-focused model where you align with the cloud provider’s priorities—not the other way around. You’re entering ecosystems of Amazon Web Services (AWS), Microsoft Azure, or Google Cloud as their partner, not the reverse. 2️⃣ Cloud & Customer Centricity Gap The "build it and they will come" approach fails spectacularly on marketplaces. Successful ISVs deeply embed themselves in the cloud ecosystem by: Mapping their solution to the cloud provider’s growth areas and strategic initiatives. Understanding how and why customers discover, evaluate, and buy solutions in cloud marketplaces and on each cloud platform. Aligning GTM motions with the cloud provider’s sales cycles and engagement models. 3️⃣ Immature Co-Sell Many SaaS companies struggle with co-sell readiness, held back by ingrained direct sales cultures, concern of conflict (channel/competition) and lack of Cloud GTM understanding. Incentives: Sales teams aren’t motivated (or de-motivated) to collaborate with cloud reps or sell through marketplaces. Value Proposition: SaaS companies fail to articulate how their solution complements the cloud provider’s offerings and drives customer value. Program Knowledge: ISVs often miss out on cloud program benefits because they don’t meet requirements or focus enough on eligibility. 4️⃣ Lack of Alignment and Internal Resistance The most insidious obstacle often comes from within: Siloed Departments: Sales, marketing, product, and finance don’t collaborate effectively, hindering a unified marketplace strategy. Leadership Gaps: Executives may not fully grasp the strategic importance of cloud marketplaces, leading to misaligned priorities or underinvestment. Not leveraging marketplace data and insights and not integrating MP into your sales and company operations 5️⃣ Cloud-Native Product Reality Success on cloud marketplaces goes beyond GTM strategy—your product must also be ready... Ideally its architecture should leverage cloud-native services to enhance consumption and scalability. 📈 What This Means The gap between leaders and laggards in cloud marketplaces is widening. Those who treat Cloud GTM as a transformation, not just another sales/partner channel, are experiencing rapid growth. Others risk being left behind in what’s quickly becoming the largest software distribution channel. 💡 What’s the biggest obstacle you’ve encountered? _________ PS. Accelerate your #growth on #cloud marketplaces with Cloud GTM Leader Course. Last chance to join Cohort 9 starting Jan 14th (tomorrow) - https://lnkd.in/ejc7S4Pb

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In the last month, we've all heard this Service-as-a-Software narrative that AI will enable applications to sell an outcome or a full task, rather than a seat as in vertical SaaS. This could then increase annual contract values from 3 or 4-figures to 6 or 7-figures. After all, that is the cost of labor previously delivering the service, right? Service-as-a-Software expands the $650B Software Market into the $10T Services markets. We've heard this seductive VC narrative from Mamoon Hamid at Kleiner Perkins; Sarah Tavel at Benchmark and Pat Grady at Sequoia Capital. Smart investors, no doubt. But what if this thinking ignores the competitive element? Since when is pricing a function of the work you replace, rather than the next application who is seeking to replace you? I suspect customers will see massive savings in cost / task, but competition will render value capture difficult for these first movers. With dozens of AI SDRs, AI Coding Agents, and AI Work Assistants and discerning IT procurement departments, how will these price assumptions sustain? The answer, I think, lies in dusting off Hamilton Helmer's 7 Powers, specifically 3 of them: 1) Network Effects (on users or data) 2) High Switching Costs (system of record) 3) Counter-Positioning (inimitable pricing or delivery mechanism) This is what we are looking for at Optimist Ventures. Would love others' thoughts on this.

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The acquisition game is very different from 10 years ago now that 70% of SaaS acquisitions are led by private equity investors or PE-owned strategic buyers. Most SaaS founders aren't thinking about the new realities of eventually selling their SaaS companies. It's very different than the old days of "sell it for big multiples to a strategic buyer, cash out, and see ya later." Here are 5 questions for founders to consider the new realities of a potential PE-backed exit: 1) Is my company built to keep growing efficiently after I sell it? - Your SaaS metrics need to be healthy. Growing steadily with efficient CAC and solid revenue retention - You need a business that runs without you, the founder. - And you will still be responsible for fixing the problems in your business. 2) Would I invest in the new company with my hard-earned equity or cash? PE buyers don't cash you out of 100% of your equity, just a partial "first bite of the apple" prize. They buy a minority or majority of your company, so you become the major private investor in the acquiring business. This is not an earn-out. You now own shares in a new company that you don't control. You must be confident enough in the new owners, operators, culture, and vision to invest 20-60% of your hard-earned equity in this new venture. 2) Why will this acquisition work to build and sell a much bigger company? Most old-style mergers and acquisitions didn't work for either side. In this new world, founders need to find the right owner/partner with the right strategy and team to ensure their hard-earned equity pays off on their "2nd bite of the apple" when it is sold again. Founders should also do deep due diligence on their acquiring PE investors, not just pitch themselves for "sale" to any takers. 3) Do I trust the new owners and operators to do the right things? Most founders don't stay on as CEOs when they sell to PE buyers. Someone else owns your business (PEs), and they have CEOs who will run the business their way. 90% of founder-CEOs who sell to PE end up as board members with the ability to make suggestions to the new leaders. That's it. You must trust the people and their approach to your business and your precious equity. 4) How will things change now that I'm not the CEO? Maybe you continue running the business as a CEO with new owners for a while, but eventually, you won't be there. Now what? How do you spend your time now that you're only an involved board member? This is very jarring for most former CEOs, so it's worth considering before selling. 5) How will things change now that I have money? The biggest reason to sell a major part of your healthy SaaS business is to take some chips off the table and win a major cash prize. You invested 5-15 years in this business and probably some of your own cash. Now what? Will your life change a little or a lot? It's a whole new world for successful SaaS founders when they sell to PE buyers. #practicalfounders

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AI could kill ARR as we know it. And, in doing so, it could kill SaaS metrics as we know them ⤵ Annual recurring revenue (ARR) is the building block of SaaS metrics. And it's the basis of SaaS valuation multiples. It's (usually) high margin, predictable and growing. Which means SaaS companies are (usually) on track to become highly profitable at scale. AI throws this off. What's not classic ARR: - Charging per successful AI resolution (Intercom, Zendesk) - Charging per credit used (Clay) - Charging per task completed (11x) - Charging per photo edited (Imagen) - Charging per demand package generated by AI (EvenUp) - Charging per conversation (Salesforce) We're moving away from charging for *access* to software and to a model of charging for the *work delivered* by AI & software. This might mean greater volatility. Variable margin profiles. Seasonal revenue. Project-based, non-recurring use cases 🤯 Welcome to the new "ARR": annual *re-occurring* revenue. Some implications of this shift: 1️⃣ Spending much more time unpacking the components of revenue. 2️⃣ Moving away from ARR multiple valuations to looking at last 12 month revenue (or, even better, last 12 month margin $). 3️⃣ Looking much more closely at revenue concentration -- I suspect there will be a far wider variance between the smallest & largest accounts. 4️⃣ Measuring newer things like "time to ramp" and "share of wallet" as predictors of future success. --- I unpacked this shift with CJ Gustafson in his Run the Numbers podcast (check the comments). And shoutout to Dave Kellogg for a great keynote on this topic 🙏 🎁 For more insights on SaaS growth & pricing, check out Growth Unhinged — my free weekly newsletter: https://lnkd.in/exTbjKaM #ai #saas #finance

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Tech CEOs, is your team struggling with execution speed? Time to unblock your flywheel. Better handovers and faster throughput. Comment "flywheel" below OR direct message me for a quick tool to map things out.

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If you're looking to hire a GTM Engineer in-house, full-time, here's where I would look for one: CONTEXT First, if you don't know what a GTM Engineer is, check out this post: https://lnkd.in/gCgNZD-B It's not ops or growth or sales development. It's a new role that is emerging. Someone who is helping create efficiencies through the go-to-market motion and generating pipeline automatically (in many cases). So, they need to have some technical chops (like ops) and have sales accumen (like sales development) but also ship things like growth. I'm not saying this person replaces all of those departments (obviously). Instead, it's an additional headcount. Why now? Well, because teams are leaner. Budgets are tighter. Efficiency matters. And AI has created an enormous opportunity/lever for early adopters. HOW DO I HIRE ONE OF THESE (FEW) UNICORNS? First of all, I don't think Clay is the only tool that GTM Engineers should know. But, anyone who is great at GTM Engineering *very likely* is a master in Clay already. So, the first place I'd look is in the Clay Slack community. You could also probably find someone junior here: https://lnkd.in/gMZAUrCs and use them as a contractor, then hire full-time if it's a mutual fit. Finally, Cargo has a Slack community called "GTM Engineer" which has really high-quality builders in it. I'd go hang out there for a week or two and see who is shipping dope stuff. PS - If the person is not using AI every day, I would not hire them. (You are going to get sick of me talking about my bullishness about AI in 2025... get use to it, or unfollow me)

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Some things are best understood by actually seeing it. 👀 Especially our custom object lifecycle (aka funnel ) reporting. We get a lot of folks coming to us who are interested in getting this unified reporting model. So I thought it would be best to just show off what the data looks like. Don't get it twisted - you still need a great foundation to support a lot of the data  and process for getting a correct view and accurate reporting. We help with all of that too. You gotta do the basics first but then you will be ready to report like this. Props to Alison Rouse  for developing this amazing solution and Christie Montague Fusco for the visuals 💥 #revenuwgrowtharchitecture #gtmops #revops #funnel #lifecycle #analytics

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Lately I’ve talked to several RevOps leaders about their trickiest data gaps. This isn’t about rep outreach. This is about understanding a market to determine TAM, ICP, segmentation and territory design—big strategic choices that massively influence next year’s financial plan. And there are SO MANY gaps. The gaps aren’t simple. The basics like phone numbers and simple firmographics are covered. It’s really about where data bleeds into information. Here are some types of gaps I’m seeing: * Industry-specific technographics. I’ve been talking with a customer in healthcare. Healthcare tech stacks are complex and fragmented. There are specialized data providers but they’re struggling to keep up. * Domain-specific taxonomies. One customer targets professional services providers for SMBs. Understanding the types of backoffice services those companies offer and which they prioritize is just as important as company size. There’s no good source for data like this and any scraped data needs to be heavily processed to fit into a meaningful taxonomy. * “Hard” firmographics. One customer recently did a market-sizing exercise that relied on the physical locations of each prospect. Another customer needs to understand the total number of front-line employees. Some providers claim to have this data, but it’s spotty at best. I think of these as “hard” firmographics. The hard numbers do exist, but they’re very hard to source. * “Soft” firmographics. I talked with a company in the food service space. The concept of a “well-established” restaurant is important to them. Another customer cares a lot about finding companies with “road warrior” employees. These criteria are tricky to precisely define but, much like the famous supreme court ruling on obscenity, you usually know it when you see it. * Classifications. This really isn’t about data, more like synthesis. Most companies need to put prospects into buckets—anything from use cases to personas to a set of defined market segments. Having to rely on reps to do this assessment means we can’t use these classifications to make strategic resource allocations. So we’re back in planning season. Yet again trying to compile data points from bulk enrichment providers, combine that with spotty data captured by reps, sprinkle in some self-reported customer data from apps and lead forms and then somehow—somehow—turn this shaky foundation into the hard commitment of a financial plan. It’s a difficult, high-risk job and RevOps is usually at the very center. I know because I’ve been there. I wish I could end with pithy advice about how to fill these kinds of gaps, but I’m afraid it’s not that easy. I’d love to hear from anyone that’s got a complicated strategic data gap. We might be able to help. But if nothing else, I’d love to talk shop, share what I’ve seen and learn how you’re tackling the problem.

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One challenge folks will hit when moving to durable messaging is that although it can enable complex retry strategies, it does not mean that your operation *should* be retried. A failure during a web request may just result in an error to the end user, but the story is more complicated in a message handler when we don't have that direct connection to the end user anymore. Internal business logic and external services may not be able to handle this scenario. The realities of async messaging means we need to understand: - What happens if (when) this message fails? - What happens if (when) this message is handled more than once? - What happens if (when) this message is retried far in the future? Each of these isn't just a technical consideration - it's a business one as well.

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I interviewed over 200 GTM leaders before we even wrote the first line of code for WINN.AI. One thing came up in nearly every conversation: It has to be seamless. Not just easy to use. Not just good product design. It has to be completely non-interruptive. 100% integrated into a sales rep’s workflow. That’s the only way AI can really work in real-time. Any additional information during a sales call can be distracting. And with platform fatigue, getting reps to do anything outside their existing workflow is nearly impossible- especially if it takes away from selling time. This was a huge challenge for us. We had to make WINN minimalistic - minimum information, minimum clicks, minimum cognitive load. That’s why integrating with Slack was a no-brainer. Now, revenue teams can get their call summaries and notes right in Slack. No extra clicks, no new tabs, no logins. You finish a call You get a summary in Slack. You click to update the CRM, straight from Slack. It’s that easy. It’s that seamless.

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A GTM engineer who can “build anything” is worth $1M. A GTM engineer who can figure out “what to build” is worth 100X that. In business, the GPS creates more value than the engine.

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7. That's the median employee headcount for SaaS companies under $1m in ARR. Nearly half of those positions are in engineering. I'm often asked about headcount planning and it's so helpful to provide data to drive decisions. The High Alpha SaaS Benchmark Survey is live and it's full of data like this. Download the report now. (Link in the comments)

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SaaS Buying Behavior Has Shifted: What Software Founders Need to Know The landscape for software purchasing has changed dramatically since 2021. Companies are no longer buying software for every need—instead, they’re categorizing products as either "nice-to-have" or "must-have." Here's what that means: Scrutiny is Higher Than Ever: Every purchase is heavily examined, with CFOs, head of sales, and RevOps teams now playing key roles in the decision-making process. Must-Have or Bust: If your SaaS product isn’t essential, you’re at risk. Companies demand solutions that solve critical problems. The game has changed. Has your SaaS strategy?

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ServiceTitan, the "operating system for the trades," has filed for its IPO. Here's what you need to know about this vertical SaaS pioneer: 🔑 Key Figures: ARR: $685M (+25% y/y) GTV: $62B (+23% y/y) Net Dollar Retention: 110%+ Customers: ~8,000 (+18% y/y) 💡 What They Do ServiceTitan provides an end-to-end SaaS platform for home and commercial service pros (plumbers, electricians, HVAC specialists). They're the "center of gravity" in vertical SaaS tech stacks, offering: -Automated scheduling -Integrated payments -CRM capabilities 🚀 7 Key Themes 1. Vertical SaaS Pioneer: Tailored solution creating deep customer lock-in 2. Founders' Deep Customer Ties: Intimate understanding of industry pain points 3. Stacking Niches: Expanding TAM through strategic acquisitions 4. Mid-Market & Enterprise Focus: Avoiding "down-market" trades businesses 5. Add-On Products Driving Growth: Pro Products and FinTech Payment add-ons 6. Economic Resilience: 75%+ of trades jobs are non-discretionary 7. Tech Lifeline for Aging Workforce: Attracting tech-savvy workers, boosting efficiency 💭 My Take ServiceTitan has the hallmarks of a vertical SaaS leader in a massive, underserved market. Their success post-IPO will hinge on TAM expansion, margin improvement, and continued product innovation. As a fan of vertical SaaS, I'm rooting for ServiceTitan to pave the way for other VSaaS pioneers helping small businesses thrive. What's not to like about that? What's your take on their IPO? Full S1 breakdown: https://lnkd.in/eYyavKE5 #ServiceTitan #VerticalSaaS #TechIPO #TradesTech

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Looking for some help on a really important topic: Who has a ton of experience figuring out how to navigate enterprise security reviews, for $0-$1M ARR B2B startups? I am getting so many questions on: - Do we need to be SOC 2 compliant? Type 1 or Type 2? - How do we navigate the security review process? - What's optional, what's required? - How do we get the deal done without taking 6+ months in vendor review? - etc. Would love to host an event or roundtable on the topic. If you know anyone who: - Has done this before, ideally at multiple different companies - Ideally from "no plan" to "this works" to "this is fast & relatively easy" - Can explain the process end-to-end, options & trade-offs Please tag them here or DM me! I know there are a few people out there who know this well... please connect me!

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Don’t waste time and money on manually managing access reviews. Some of the biggest time wasters I see are: - Modifying access individually for each application after conducting reviews - Generating evidence for auditors post review - Need to coordinate with multiple stakeholders - Taking up tons of company resources and time - Overshoots deadlines - No/Limited visibility into who has access to what applications - No/Limited visibility into application usage information Does this sound like you? Check out Zluri’s case study on how to Improve your access review process. https://lnkd.in/gsR2Cuhu

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We analyzed hundreds of SaaS companies and the landscape of social proof to see how it has evolved and where it’s heading. We found 3 core eras and we’re now entering a 4th. 1. Era I: Analyst-led Back in the day, firms like Forrester and Gartner were the gold standard for advice. Their deep industry knowledge and extensive research were invaluable. But as the pay-to-play model crept in, their credibility took a hit. Only vendors who could afford to subscribe had access to their insights, which diluted the trust factor. 2. Era II: Platform Review-led Enter the era of platform review sites like G2 and Capterra. They shook things up with crowd-sourced reviews and ratings, much like Yelp but for software. This user-generated content, often incentivized by rewards, became a goldmine of information. Other review platforms emerged, and many were eventually acquired by larger firms. 3. Era III: Community-led (in this era) Then came the community-led era, which we’re still in. Professional networking sites like LinkedIn and online communities on Slack have become the new hubs for software recommendations. Influencers play a big role, offering genuine advice at first, but soon monetizing their opinions, which is eroding trust. Companies lean heavily on customer advocacy and influencer programs, but overusage and compensation blur the lines between genuine and incentivized endorsements. 4. Era IV: Authentic Word of Mouth (entering this era) Now, we’re in the era of authentic word-of-mouth. Organic feedback from peers is more valuable than ever. Platforms like Noble facilitate honest conversations between prospects and existing customers, making uncurated, genuine opinions the new norm. This approach emphasizes transparency and trust. This fourth era changes the game. Vendors confident in their product-market fit will embrace this approach, even at the risk of occasional negative feedback. Transparency builds trust, and unlike G2 reviews or paid influencer posts, this model of facilitating authentic word of month ensures people hear directly from customers in a trusted way. Read the full post in The GTM Newsletter in the comments. For more of what we are seeing across go-to-market and the insights of 350+ of the best operators in the game, join 52,000+ other revenue leaders who read The GTM Newsletter weekly below. ✍️

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Wondering how to merge PLG and SLG for maximum impact? Japna Sethi talks about how they made this work at companies like Dropbox, Productboard, and Calendly. She calls it "defining the API" between the two growth motions so the right PLG leads get passed on to your sales team and shares the details on the approaches at the companies she has worked. For the full episode: https://lnkd.in/d-2ZAvir

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