Jonathan Bikoff

Your POC process is probably why you're not closing enterprise deals.   After analyzing POC outcomes across our portfolio, the data is clear: Companies with structured and priced POCs close 3x more deals than those running free pilots.   Why charge? Price signals seriousness. Even nominal fees filter serious buyers from tire-kickers. Frame your pilots as fixed-fee engagements: Say "we structure this as a 4-week, fixed-fee engagement to quantify value and build your business case."   Be sure to clarify pricing expectations in the process: If your pilot costs $5K but commercial deals are $100K-$300K based on the value unlocked, state this explicitly to avoid anchoring.   Here are 5 best POC best practices we see:   1. Define success criteria, not scope Align on specific KPIs, business outcomes, and who signs off before writing a line of code.   2. Time-box ruthlessly with weekly checkpoints POCs should run 30-90 days max. Set weekly or bi-weekly checkpoints to maintain urgency.   3. Pre-commit the path to commercial discussions Before starting any pilot, confirm that hitting the success metrics will trigger stakeholder presentations and commercial negotiations.   4. Demand access to the full buying center Technical users alone can't close deals. Ensure you meet decision-makers and budget holders during the POC, not after.   5. Document like a contract Formalize scope, terms, and deliverables in the agreement. Include specific responsibilities for both sides, data access requirements, success metrics, timelines, and post-POC commitments.   --   POCs are where your enterprise motion gets built. Treat them that way.   I wrote a guide to AI pricing with Madhavan Ramanujam and Joshua Bloom that discusses these ideas in more detail. If you're curious to dive deeper, I'll leave that link below. Also, Madhavan just released a new book called Scaling Innovation that also explores these topics. Highly recommend!

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One of our <$5M ARR SaaS clients invests $75k/month in cold email. Here’s the surprising reason why, what it taught us in 2024, and where we’re heading in 2025. BACKGROUND What are Sales Automation Systems’ 2024 highlights? 1. Signed up 42% of RB2B’s revenue as they passed $4M ARR in just 8 months. 2. Worked with 139 clients, including names like Yotpo, Riverside.fm, and Eric Siu ✓ 3. Implemented Adam Robinson’s playbook for The Alliance, identifying 50k+ website visitors every quarter over 14 sites and hitting them across 238 campaigns. 4. Fyxer AI now sends 2 MILLION emails per month using our approach (and they're not even our biggest client) Thanks to our clients and their referrals, we grew from a team of 1 to 4, pushed our Annual Run Rate to $2,652,000, and saw 1244% revenue growth in 2024. (Yeah, we double-checked the math—twice.) WHY COLD EMAIL CHANGED IN 2024 It’s no longer enough to rely on SDRs spamming 15-part sequences—especially when AI can crank out better copy at scale without torching your domain. Founders are replacing entire teams with one person who sets up bulletproof Cold Email Infrastructure, uses AI-driven personalization (like Clay), automates every touchpoint, and matches the perfect offer to the right audience. Once that’s dialed in—and you’ve got the TAM—you can send a million emails a month and still land in the inbox. But if your offer is weak or your infrastructure is sketchy, no AI magic will save you. Bottom line? You can’t just use the "Predictable Revenue" model anymore. Teams that merge AI, automation, and real-time data to deliver 1-to-1 relevance at scale are the future. That’s why our go-to strategy is sending one great email per quarter to everyone who firs your ICP within your TAM. 2025 - WHATS NEXT We’re seeing more clients who want to send millions of emails monthly. Fuck yeah it’s expensive—but massive scale demands a massive investment. So we're about to Alpha a “grand master sequencer” that analyzes EVERY email sent—its configuration, deliverability, replies—and auto-adjusts our infrastructure daily, no matter what Google or Microsoft throw at us. As for copy, we’re embedding our AI with HUNDREDS of pages of proven campaigns and offers to generate inidividual emails for each lead. So when “Sallie from Company X” is in your TAM, our AI picks the right angle—no manual campaign building needed. But here’s the kicker: our only bad churn this year came from underbaked offers, so we’re helping clients dial in their value props, too. After all, no infrastructure can rescue a weak proposition. The end result? Better deliverability, better targeting, and better copy—at scale. P.S. My top priority this quarter is to talk consistently about what we're doing. So if you want to watch these strategies in action for 2025, make sure to drop a follow → Taylor Haren

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Preferred Stock = 'heads I win, tails you lose' Marc Benioff built Salesforce with common stock and revenue sharing instead of traditional preferred rounds. 84% of startups that take preferred stock see founder equity diluted below 15% by Series C. The math is brutal but predictable. The time to end preferred stock has come. Lawyers love preferred stock for the fees, and the preferences help investors in downside scenarios. Optimizing for downside is the wrong strategy. The reality is preferred just costs more and adds needless complexity. Here is a dirty little secret. I asked two of the top lawyers in Silicon Valley what would be the best thing to do to improve funding, and they both independently said, "eliminate preferred." If everyone has common stock, then there is: 🌱 Faster and simpler funding rounds at every stage 🌱 Dramatically less legal costs for everything 🌱 An easy to understand cap table with clear exit value 🌱 Shared risk that creates shared commitment to long-term value 🌱 Clear stakeholder governance for community voices in major decisions The old system concentrated wealth in the hands of a few while extracting value from founders, employees, and communities. We can build something better.

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PMM managers hit a point where they feel disconnected from the work. You’re suddenly... - Reviewing GTM strategy docs/decks you have (more) limited context on - Coaching teams on how to position against competitors you haven’t heard customers talk about directly - Helping with messaging for products you have limited hands on exp with This drift is natural, but risky. The further you get from the craft, the harder it is to make the right calls on strategy, resourcing, or hiring. The fix isn’t to jump back in everywhere. It’s to choose the right leverage points: 👉 Lead one messaging workshop yourself. 👉 Run a win/loss deep dive with a direct report and actually sit and participate on the calls 👉 Own a competitive research project end-to-end These are a few high-value touchpoints where you sharpen your own intuition and elevate your team. PMM leaders who never touch the work risk managing in abstraction. PMM leaders who dive in with intent build sharper instincts - and stronger teams. In my experience...almost every manager begins to feel the balance shifting. Don't be ashamed or feel awkward about it. But DO try and address it - this is where we're all headed.

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Most SaaS companies get stuck at $5M–$10M ARR. Here’s how to breakthrough👇 1️⃣ Not knowing your numbers Unit economics aren’t optional at scale. - ACV: Annual contract value - CAC: Cost to acquire a customer - ARPA: Average revenue per account - Churn: The % of customers or revenue you lose - LTV: Revenue a customer generates over their lifetime - Payback months: How long it takes to earn back your CAC If you can’t recite these numbers on command, you don’t truly know your business. And when you don’t know them, every investment decision is a guess. 2️⃣ Underinvesting in sales & marketing The companies that break through $10M ARR consistently spend 10–25% of revenue on acquisition. That means: • Building outbound prospecting into muscle memory • Mastering paid acquisition channels like Google, Meta, LinkedIn, and Bing • Turning on both paid search AND paid social • Scaling profitable campaigns But too many founders stay timid. They starve sales and marketing for short-term profits. And then wonder why growth flattens. 3️⃣ Weak product experience + onboarding UI and UX aren’t window dressing - they are retention levers. So is onboarding. If a new user doesn’t get value in the first 7–14 days, you’ve already lost them. You can’t brute force growth when the bucket is leaking from day one. 4️⃣ Neglecting customer success Customer success isn’t “support.” It’s revenue protection. It’s expansion. The best SaaS companies: • Track adoption and usage • Intervene when customers get stuck • Turn accounts into champions The worst? They staff it late and treat it as a cost center. 5️⃣ Ignoring upsell & cross-sell At $5M–$10M ARR, the name of the game shifts from acquisition to net revenue retention. That means: > Upselling into higher tiers > Cross-selling into adjacent products > Expanding contracts with power users If you’re not creating new ways for customers to grow with you, you’re capping your own upside. Breaking through $10M ARR requires a mindset shift. You can’t scale on hustle alone. You can’t scale on acquisition alone. The companies that make it to $50M ARR do three things differently: ↳ They know their unit economics cold. ↳ They invest deliberately in every growth lever: sales, marketing, product, customer success, expansion. ↳ They build systems that compound. Because what gets you to $5M ARR won’t get you to $50M ARR. --- Today, I run three private communities that might help you: → SaasRise: for founders with $1M+ in ARR → VentureRise: for VC-backed CEOs with $5M+ raised → GrowthRise: for B2B Marketing Leaders with $1M+ in ARR

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Top revenue performers have options. If you want to attract and keep the best, you need more than competitive comp plans. 🎯 What actually matters: — Clear career progression. Specific paths and timelines, instead of vague promises. — Real-time transparency. Show performance metrics now, not in quarterly reviews. — Leadership that gets it. Revenue leaders who've done the job themselves earn trust. — Culture of winning. Celebrate success, learn from losses, and set aggressive but achievable goals. The bottom line: Treat revenue professionals like the revenue drivers they are. Give them what they need to succeed, and they'll choose to stay and perform.

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Perplexity's ($16B) CBO says AI is rewiring SaaS sales. Here’s what that means: • 𝗘𝘃𝗲𝗿𝘆 𝗿𝗲𝗽 𝗶𝘀 𝗻𝗼𝘄 𝗮𝗻 𝟴𝟬% 𝗱𝗼𝗺𝗮𝗶𝗻 𝗲𝘅𝗽𝗲𝗿𝘁: AI compresses learning across functions. Sales reps can understand legal, technical, or industry specifics before ever hopping on a call. Discovery isn’t dead but it’s happening before the meeting. • 𝗧𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝘀𝗮𝗹𝗲𝘀 𝗮𝗿𝗲 𝗴𝗼𝗻𝗲: AI handles FAQs, objections, and even pricing conversations. If your product is simple, your buyer doesn’t want a rep they want speed and self-service. Humans now earn the right to sell by adding real insight. • 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗿𝗲𝘃𝗶𝗲𝘄𝘀 𝗮𝗿𝗲 𝗻𝗼𝘄 𝗱𝗮𝘁𝗮-𝗱𝗿𝗶𝘃𝗲𝗻: Forget gut feel. AI summarizes emails, transcripts, and signals from every touchpoint to predict deal outcomes more reliably than reps. Forecasting just got a hard reboot. • 𝗠𝗲𝗲𝘁𝗶𝗻𝗴 𝗽𝗿𝗲𝗽 𝗴𝗼𝘁 𝘀𝗺𝗮𝗿𝘁 𝗮𝗻𝗱 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰: No more spending 90 minutes on background research. Now it’s 90 seconds with AI and you walk in with insight, not just info. Bonus: ask AI live on the call. It builds trust in real time. • 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗴𝗼𝘁 𝗽𝗿𝗼𝗮𝗰𝘁𝗶𝘃𝗲: Instead of asking “what’s happening with this account?”, AI tells you before the rep knows. Layoffs, exec changes, new funding? AI flags it. The best teams now strike early. My 2 cents: 1. Challenger Sales is becoming real. reps show up with insight, not just questions. Creativity and judgment are now core to selling. 2. These tools increasingly show up where reps already work. That’s how lagging industries might leapfrog. 3. Hack: Weekly AI standups for GTM teams to test tools, share wins, and move fast. 📌 Source: SaaStr Annual session w/ Dmitry Shevelenko (Perplexity) + Sam Blond (SaaStr) on YouTube. #ai #llms #startups #founders #saas #sales

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Outcome-based pricing (OBP) sounds great, but it's almost impossible to implement. Attribution is the obstacle. For example, did the new marketing software increase sales, or was it the new BDR training, the tweaked comp plan, or a new feature? The world is messy For most SaaS products, it's impossible to attribute value directly. However, there are a few cases where it can be done. To achieve outcome attribution, you need: 1. software that performs tasks autonomously 2. business cases that are simple and binary Agentic AI is the most obvious example and the reason the OBP is gaining traction. Yet, the use case must be straightforward and binary, and the completed task must have quantifiable value. Here are two seemingly straightforward cases. Customer support provider Zendesk defines a "Successful Automated Resolution" using seven pages and three flowcharts. Even with all that precision, the comments section of the pricing page is filled with complaints. Pricing optimization software vendor Spotlight Solutions delivered millions of dollars in gross margin improvement. It pursued a pricing plan based on the savings, but when it came to calculating the bill, it was a contentious cluster of competing spreadsheets. Outcome-based pricing, while seemingly win-win, can be a zero-sum game when deployed. It's the journey to Outcome-Based Pricing that's important. While outcome-based pricing is difficult, identifying the outcomes you are trying to deliver for your customer can be very useful. James Colgan from Slack explains how to identify metrics that drive customer value: "The key is to step back and understand what success looks like to them and how that manifests within the product in terms of actions." In Slack’s case, it was the number of messages in a channel sent by more than one person within six days. Based on data analysis, Slack knew that once this number was achieved, activation and engagement would start to grow organically. Slack’s specific metric of success informed everything they did, but it was too esoteric for pricing, which they simplified to “active user.” Pricing the work, not the outcome. Zapier would be an example. Their automation platform saves companies money by automating routine tasks, but it’s impossible to estimate the labor savings of each automation. It is, however, easy to count the automations and charge for each one. Clay is another good example of work-based pricing. They charge based on how much work their AI agent does and how "hard" the request is. Finding a work email for someone is easy, while finding their mobile number is hard. Anchoring pricing to real value. As software becomes more autonomous, fixed pricing tied to users makes less sense. The only way to capture the value of your application is by tying it to your customers' value drivers. Working through that value chain will deliver benefits regardless of whether it results in outcome-based pricing, which it probably won't.

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“We sell to SaaS companies.” That’s not an ICP. That’s a category. The biggest mistake I see early-stage startups make with their ICP? Going too broad, too fast. Early on at Clarify, we tried to get specific based on which early users were finding most value: founders at Seed / Series A B2B saas startups with 5-25 employees who are either using complex legacy solutions or spreadsheets as their CRM. And it informed decisions across the company: • Our product roadmap got sharper • Marketing campaigns got more precise in their targeting / prioritization • Sales cycles got shorter as we refined our pitch and found qualified leads Choosing an ICP isn’t about shrinking your market; it’s about standing out in it. Focus takes guts. It means saying no to revenue. Ignoring “easy wins.” But if you want to build something people love, you can’t build for everyone. Here’s how we keep our evolving ICP operationalized: ✅ Ruthless roadmap prioritization: “Does this help our ICP?” If not, cut it. ✅ Channel alignment: Be where they actually hang out. ✅ Reinforcement: It's a decision making lens for product, sales, and marketing. How are you operationalizing your ICP across your company?

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