Understanding Revenue Operations

Your board wants 20% growth next year. Your team hears that number and their souls leave their bodies. 20%??? After they just killed themselves to hit this year's number? Todd Caponi , during this past week's Revenue Manager Lab at Sales Assembly, broke down a formula that should hopefully result in folks who are faced with goals like this exhaling a huge sigh of relief. The Results Formula: Revenue = (Qualified Opportunities × Deal Size × Win Rate) ÷ Cycle Length. Now here's where it gets interesting. Improve each metric by just 5%: - 5% more qualified opportunities (literally one more per rep). - 5% higher deal sizes ($2K on a $40K deal). - 5% better win rate (win one more deal you'd normally lose). - 5% faster cycle time (close 3 days faster). Result: 22% revenue growth. Don't believe Todd? Run it through whatever spreadsheet you want. Change the variables. Use different baseline numbers. ALWAYS comes out to 22%. Try 10% improvements across all four? You get 46% growth. But here's a mistake many leaders make: They pick one metric and try to double it. "We need MORE PIPELINE!" So they hire more SDRs, blast more emails, book more meetings. Pipeline goes up 50%. Revenue goes up 8%. Why? Because they flooded the zone with bullshit opportunities that destroyed their win rate and extended their cycle time. The magic is in the compound effect of tiny optimizations. A 5% improvement is nothing: - One better discovery call per month. - One less discount given. - One deal closed three days faster. - One bigger upsell identified. Stack those improvements. Compound them. Watch what happens. Your team doesn't need to raise their hand another foot higher. They need to raise it one inch higher in four places. Stop asking for heroics. Start asking for tweaks. The math is undefeated.

I've watched organizations rush to implement AI tools across their revenue functions, often with mixed results. Today, I'm sharing a crucial insight: the companies seeing transformative results are not those with the most advanced tech stacks. Instead, they deploy AI with surgical precision at the intersection of efficiency and trust. In my latest piece, I break down specific AI tools reshaping revenue operations and offer strategic guidance on implementing them without eroding the customer trust that underpins sustainable growth. Key takeaways: 🎯 Conversation Intelligence Platforms (Gong, Chorus): Not just for call analysis, but for scaling successful behaviors while maintaining authentic customer interactions 🎯 Predictive Lead Scoring (MadKudu, 6sense): Allowing targeted deployment of human capital against high-probability opportunities (with critical guardrails) 🎯 Personalization Engines (Mutiny, Optimizely): Creating tailored experiences without increasing operational complexity or crossing the "creepy line" 🎯 Content Generation (Jasper.AI, Copy.ai, Claude.ai): Achieving velocity without sacrificing quality (but still requires human oversight to be more, well, human). 🎯 Customer Journey Orchestration (Drift, a Salesloft company, Qualified): Creating guided buying experiences that feel personalized while operating at scale 🎯 AI Assistants (Grok, ChatGPT): Rapid iteration and testing of multiple approaches before committing resources The most successful revenue organizations aren't those using the most AI but those using AI most strategically. There is a competitive advantage in knowing where NOT to automate - in preserving human connection where it creates differentiating value. What AI tools are you implementing in your revenue operations? And more importantly, how are you measuring their impact beyond efficiency metrics? Read more here: https://lnkd.in/e4Ang6Nj __________ For more on growth and building trust, check out my previous posts. Join me on my journey, and let's build a more trustworthy world together. Christine Alemany #Strategy #Trust #Growth

Change is rarely blocked by technology. It is usually blocked by what the technology implies. Over the past year, I have been observing how different industries respond to AI. The pattern is consistent. People closest to learning and reinvention tend to move first. People closest to reputation and responsibility tend to pause. From my research, I have learned that most hesitation is not a knowledge gap. It is a risk calculation, wrapped in a story. Reaction sounds like: “This feels like hype.” “We are doing fine without it.” “Why buy a Ferrari if the current car, even though we can afford better, still runs?” Presence sounds like: “What problem are we solving?” “What would make this safe to scale?” “How do we keep trust while we move faster?” When you look at the data, the same blockers appear repeatedly: skills gaps, poor data quality, privacy and security concerns, integration challenges, ethics, and unclear regulation. Here is what shifts adoption from stalled to steady: Treat AI as a capability, not an experiment. ↳If it remains a side project, it stays fragile. Start with one clear use case. ↳Resistance drops when the value is specific. Make data readiness unglamorous and non-negotiable. ↳AI is only as reliable as the information it depends on. Lower the fear of “getting it wrong”. ↳People do not experiment when mistakes feel career-limiting. Name the real worry. In many cases, the unspoken question is, “Where do I fit if this works?” →Choose the right model for the job. →Sometimes that is a smaller, more controllable model. →Sometimes it is a larger one with stronger safeguards. →The point is fit, not fashion. Put governance on the same timeline as delivery. Speed without guardrails creates backlash later. Invest in AI literacy across the organisation. Not everyone needs to build models, but everyone should understand the limits and responsible use. The organisations that move fastest are not the most aggressive. They are the calmest. They create clarity, make learning safe, and treat trust as part of the design. That is what composure looks like when the world changes. Sources I drew on (for the data points and recurring barriers). ➕ Follow (Jyothish Nair) for reflections on AI, change, and human-centred AI. #ArtificialIntelligence #AIAdoption #DigitalTransformation #FutureOfWork

𝗙𝗶𝘅 𝘁𝗿𝘂𝘀𝘁 𝗳𝗶𝗿𝘀𝘁, 𝗻𝗼𝘁 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀. 𝗧𝗵𝗮𝘁’𝘀 𝗵𝗼𝘄 𝘆𝗼𝘂 𝗺𝗮𝗸𝗲 𝗱𝗮𝘁𝗮 𝘄𝗼𝗿𝗸 𝗳𝗼𝗿 𝗲𝘃𝗲𝗿𝘆𝗼𝗻𝗲. A new Head of Data walks in. 𝗧𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝟵𝟬 𝗱𝗮𝘆𝘀 𝗮𝗿𝗲 𝗮 𝘁𝗲𝘀𝘁. Many start with dashboards, pipelines, and plans. They rebuild what’s broken and expect trust to follow. 𝗕𝘂𝘁, 𝗺𝗼𝘀𝘁 𝗳𝗮𝗶𝗹. They forget that trust, not tools, is the real foundation. You can fix every schema and still have leaders asking, “Why are we still in this mess?” 𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝘄𝗼𝗿𝗸𝘀: 𝗣𝗵𝗮𝘀𝗲 𝟭: 𝗗𝗶𝗮𝗴𝗻𝗼𝘀𝗲, 𝗗𝗼𝗻’𝘁 𝗗𝗲𝗹𝗶𝘃𝗲𝗿. Meet every key person. Ask what data they trust. Listen to real pain, not just reports. Find your “data superusers.” See where data dies before it reaches the decision. 𝗣𝗵𝗮𝘀𝗲 𝟮: 𝗔𝗹𝗶𝗴𝗻 𝗮𝗻𝗱 𝗗𝗲𝘀𝗶𝗴𝗻. Prioritize quick wins. Rank by impact, complexity, reach, and risk. Set clear ownership for metrics. Share updates every week. 𝗣𝗵𝗮𝘀𝗲 𝟯: 𝗗𝗲𝗹𝗶𝘃𝗲𝗿 𝗣𝗿𝗼𝗼𝗳, 𝗡𝗼𝘁 𝗣𝗿𝗼𝗺𝗶𝘀𝗲𝘀. Pick the highest priority. Deliver one visible win in 30-45 days. Align on definitions so everyone speaks the same language. Over communicate wins and issues. 𝗔𝘃𝗼𝗶𝗱 𝘁𝗵𝗲𝘀𝗲 𝘁𝗿𝗮𝗽𝘀: • Don’t rush to buy new tools. • Don’t rebuild dashboards before fixing trust. • Don’t promise AI if you have ten definitions of revenue. The first 90 days decide if data drives growth or stays a reporting chore. 𝗜𝗳 𝘆𝗼𝘂𝗿 𝗖𝗙𝗢 𝘀𝘁𝗶𝗹𝗹 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗯𝗲𝗹𝗶𝗲𝘃𝗲 𝘁𝗵𝗲 𝗻𝘂𝗺𝗯𝗲𝗿𝘀 𝗯𝘆 𝗗𝗮𝘆 𝟵𝟬, 𝗻𝗼𝘁𝗵𝗶𝗻𝗴 𝗲𝗹𝘀𝗲 𝗺𝗮𝘁𝘁𝗲𝗿𝘀. Trust comes first. Visible wins come next. 𝗧𝗵𝗮𝘁’𝘀 𝗵𝗼𝘄 𝘆𝗼𝘂 𝘀𝘁𝗼𝗽 𝗯𝗲𝗶𝗻𝗴 “𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗽𝗲𝗿𝘀𝗼𝗻” 𝗮𝗻𝗱 𝗯𝗲𝗰𝗼𝗺𝗲 𝘁𝗵𝗲 𝗽𝗲𝗿𝘀𝗼𝗻 𝘄𝗵𝗼 𝗺𝗮𝗸𝗲𝘀 𝗱𝗮𝘁𝗮 𝘄𝗼𝗿𝗸. 𝗛𝗼𝘄 𝗮𝗿𝗲 𝘆𝗼𝘂 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘁𝗿𝘂𝘀𝘁 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 𝘁𝗲𝗮𝗺𝘀?

Your sales team missed quota again last quarter. Your first instinct? Blame the reps. Fire the underperformers. Hire "better" salespeople. I've seen this cycle destroy hundreds of sales organizations. After analyzing 100+ revenue teams and helping clients generate $950M+ in additional revenue, here's what I've learned: 87% of sales problems aren't people problems. They're system problems. Here are 3 revenue leaks that are killing your numbers 👇 #1 Discovery theater Your reps are asking questions, but they're the wrong ones. They're focused on pain points instead of business impact. They're not quantifying problems or connecting features to financial outcomes. Result: Buyers stay unconvinced because they can't justify the investment. #2 Process chaos Every rep has their own "method." There's no repeatable playbook. Your top performer closes deals through sheer force of personality, but you can't scale that. When they leave, their numbers leave with them. #3 Coaching theater You're having weekly "check-ins" but they're just status updates. No systematic skill development. No data-driven improvement plans. You're managing activities instead of developing capabilities. The real solution is Revenue Intelligence Stop guessing what's broken. Start diagnosing systematically: → Map your actual conversion rates by stage (not your CRM fiction) → Audit what your reps really do vs. what they should do → Identify the specific skills gaps causing deal loss → Fix the systems before you blame the people A company that was a client of mine used this approach to go from $10K average deal size to $250K in 6 months. Same reps. Different system. The millions you're looking for aren't hiding in new hires. They're hiding in your current processes. P.S. Want to identify exactly where your deals are dying? Book a call here to get help: https://lnkd.in/ghh8VCaf

Most founders can tell you their revenue. Not all can tell you if their business is healthy... Early on at HomeServe, I made a mistake that I see repeated constantly by founders building serious businesses. I thought that if I grew revenue fast enough, economies of scale would follow and profitability would take care of itself. It did not. As our emergency plumbing business grew, the break-even line got further away, not closer. Monthly losses grew from £10,000 to £50,000. Revenue was going up, but the business was getting worse. That was one of the most important lessons I have ever learned. So let me break down what a Profit and Loss statement actually is, why it matters, and what most founders get wrong. What Is a P&L? A Profit and Loss statement shows whether your business is making or losing money over a set period. It tracks every pound coming in and going out, from revenue down to net profit. The Formula: - Revenue minus cost of goods sold equals gross profit. - Gross profit minus operating expenses equals operating profit. - Operating profit minus interest and tax equals net profit. The three numbers every founder needs to understand: 📈 Revenue (Vanity) It tells you nothing about the cost of generating it.  Growing revenue before you have a proven model increases losses faster. 📉 Profit (Sanity) You can be profitable on paper and run out of cash.  Blockbuster was profitable before it went under. 💵 Cash (Reality)  The one number that tells you the true health of your business.  Cash will always be king. Three mistakes founders make with their P&L: 🚫 Chasing revenue before the model is proven. 🚫 Mistaking profit on paper for cash in the bank. 🚫 Checking the P&L monthly instead of tracking cash weekly. The dashboard rule: Review cash weekly.  Review revenue and profit monthly. By doing so, you can avert any crisis. A P&L isn't just for your accountant's eyes only. It is the most honest picture of the health of your business. If you cannot read yours confidently, I suggest you fix that this week. For more frameworks like this, subscribe to my weekly newsletter, How to Make a Billion. It has lessons and stories from the world's top founders and CEOs. Subscribe here: https://lnkd.in/ergDQtiK Comment below if you have any questions about your P&L statement.  And be sure to share this post with other founders and CEOs who might benefit. 

What if I told you that your payment system is quietly leaking millions of dollars every year — and you don’t even see it? Let’s learn a case study by Tranzzo. Most conversations around payment orchestration focus on connectivity, compliance, and coverage. But the real threat to revenue often hides in plain sight: your routing logic. Revenue leakage from poor routing rarely shows up as a red flag. Merchants don’t usually “see” the missed approvals — they only notice slightly lower revenue, unexpected churn, or strange fluctuations in conversion metrics. Each misrouted transaction quietly erodes unit economics, and the damage only becomes obvious when it’s already significant. 👉 From my experience, key sources of hidden loss include: 🔹 Grey zone transactions - delayed approvals that temporarily block cash flow and reduce operational predictability. 🔹 Overpaid transaction fees - static routing often sends payments through suboptimal PSPs, unnecessarily increasing costs. 🔹 Data loss for fraud and risk models - limited routing insights reduce the predictive accuracy of anti-fraud algorithms. 🔹 Short-term channel optimization - focusing solely on the cheapest PSP or corridor can negatively impact customer lifetime value (LTV), especially in cross-border payments. Industry data confirms the impact - approval rate gaps between optimal vs. suboptimal routing can range from 5% to 12%, depending on vertical and geography. For large merchants, that difference translates directly into millions of dollars annually. I have had a conversation about this topic with the team at Tranzzo, who’ve spent years refining adaptive smart routing for merchants across Europe, America, and MENA. Their approach to dynamic orchestration — routing decisions made in real time, based on live data: 🔹 PSP uptime and latency 🔹 Geo-specific approval trends 🔹 Currency conversion efficiency 🔹 Even time-of-day performance patterns In practice, this means the system continuously learns and adapts. Every payment is routed along the optimal path to maximize approval rates while minimizing costs. The benefits extend beyond cost efficiency — merchants gain faster settlement cycles, improved cash flow predictability, and stronger customer trust. 👉 The key takeaway In a fragmented global payments ecosystem, relying on a single acquirer or static routing logic is no longer viable. The real competitive edge lies in the ability to adapt transactions dynamically, at scale, and in real-time. The question I keep returning to is: how many merchants are silently leaking revenue today — and how many will take the strategic leap to treat routing as a core part of their growth playbook? #fintech #payments #paymentorchestration

CFO: We can't invest in brand because we'll see a short term drop in revenue and ROAS. CMO: That's wrong. CFO: You're telling me we won't see a drop in revenue? CMO: Did I stutter? CFO: I'm listening, but every time someone mentions "brand" I envision dollars lighting on fire CMO: When we track revenue from organic search and direct traffic sources, they have 2x the profit margin of ad clicks. And their lifetime value? Even better CFO: That's great, but we can't just manifest more organic traffic. We need reliable revenue CMO: Here's what most people miss - a big chunk of our "high-performing" ad spend isn't actually driving new revenue CFO: What do you mean? Our ROAS numbers look great CMO: That's the trap. Quick test: cut 50% of our highest ROAS campaigns for a week. Most times, total revenue barely moves CFO: How is that possible? CMO: We're paying to tap people on the shoulder right before they buy. Taking credit for purchases that would have happened anyway. Remember that organic post from last month? CFO: The one with all the shares? That was impressive CMO: Right. We won't put ad spend behind it because it doesn't drive immediate purchases. But that engagement shows it's building emotional connection - which drives those high-margin organic sales CFO: But if we shift budget to that type of content... CMO: Yes, our reported ROAS will drop. But here's the key - revenue won't. Instead, we'll shift our traffic mix toward those 2x-margin organic channels. That's how we break free from this endless discount cycle CFO: I've noticed that. Every month we need bigger promotions just to hit numbers CMO: Exactly. We're stuck in this hamster wheel fighting over the same shrinking pool of in-market buyers instead of creating new demand CFO: How can you be sure this shift won't hurt us? CMO: Because we'll test everything first. We'll find the 20% of our "high ROAS" spend that isn't driving incremental sales. That's what we'll redirect to amplifying our best organic content CFO: And other brands have done this successfully? CMO: Every brand that's grown profit margins while reducing promotional dependency has made this shift. The alternative? Keep pushing harder on discounts until there's nothing left CFO: That's literally keeping me up at night. What's the first step? CMO: Run increment tests on our highest ROAS campaigns. I've built the measurement framework. We identify non-incremental spend, then gradually shift it to our best organic content CFO: You had me at "2x margin." When do we start? CMO: Already started CFO: You sly dog CMO: Nobody puts Baby in a corner

Why the Best CMOs Think Like CFOs Here’s the truth: the best CMOs don’t just market, they think like CFOs. That might sound counterintuitive, but if you want a seat at the table, you need to stop leading with campaign metrics and start speaking the language of business outcomes. CEOs and boards care about revenue, profitability, and market share not clicks or impressions. The most effective CMOs connect marketing metrics to financial outcomes, proving that marketing isn’t just a cost centre — it’s a growth engine. Here’s how to start thinking like a CFO: 1. Focus on ROI, Not Activity: Replace “we ran a great campaign” with “our campaign added $3M to the pipeline and reduced CAC by 10%.” It’s not about what marketing did but what it achieved. 2. Tie Metrics to Revenue: Metrics like engagement and lead generation matter internally, but you need to translate them externally into revenue impact. For example: “This lead generation effort contributed $2M in ARR with a 3:1 ROI.” 3. Prove the Financial Impact of Long-Term Investments: Marketing isn’t just about quick wins. Show how brand-building efforts improve CLTV, shorten payback periods, and increase pricing power over time. CEOs don’t just need to see what’s happening this quarter, they need to trust that marketing is driving sustainable growth. 4. Bridge the Gap Between Marketing and Business Strategy: Marketing doesn’t operate in a vacuum. Collaborate with product, sales, and finance to ensure marketing initiatives align with the company’s goals. Whether it’s launching a product, refining pricing, or improving retention, marketing should be the connective tissue that drives alignment. The best CMOs don’t just report on what marketing does, they show how marketing creates value. Thinking like a CFO isn’t about abandoning creativity or strategy, it’s about tying them to outcomes that matter most to the business. Finally. To connect marketing metrics to business outcomes, don’t just report numbers, translate them into a narrative that resonates. Instead of saying, “Our campaign generated 1 million impressions,” frame it as, “This campaign increased unaided awareness by 15%, positioning us ahead of Competitor X in market share for Segment A. This sets the stage to capture an additional $5M in TAM.” It’s about making every metric a stepping stone to the CEO’s growth, profitability, and market leadership priorities. The more you can bridge the gap between what marketing measures and what the business values, the more indispensable marketing, and you, become.

“My CEO ordered me to never use the word ‘brand’ again,” lamented a CMO from a $75mil SaaS brand. “Then he told me to only spend money on things that drive revenue,” the CMO shared. Ah, yes, the double whammy. Everyone in the huddle sympathized with a “been there” nod. I silently stewed. A productive rant to follow. Should CMOs stop using the word “brand?” Yes. It’s toxic. Time to move on, and this is from the guy whose latest book subhead reads, “12 Steps to Building Unbeatable B2B Brands.” If you must venture into brand-like language, use the word “reputation.” It’s much easier to grasp. Even CFOs can understand the difference between a good reputation and a poor one. Does that mean I can have budget items for reputation building? No, unless you want that part to be cut faster than you can say “brand.” If possible, avoid sharing spending buckets beyond people, programs, and tech. If you, like many CMOs, divide your budget into demandgen or growth marketing and everything else, your CFO will assume that everything else is unmeasurable and possibly wasteful. Choose your budget-bucket labels carefully. Events, for example, can drive new logos, accelerate late-stage deals, help with expansion, and reduce churn. If events are funded from your “growth marketing” budget, then that’s how they will be measured, and that may limit this invaluable channel. What about the “only spending on revenue drivers” directive? Live with it. All marketing drives revenue (there, I said it!). It’s just a matter of timeframe and targets. Unless you’re selling an impulse item (Of course, I would buy another penguin hat if it showed up in my Instagram feed), you operate in the world of considered purchases and buyer journeys. Different marketing activities impact different parts of your target at different times in different ways. Let’s take Analyst Relations. It can take 12-18 months to build a quadrant-shifting relationship with an analyst. When that higher rating or new category of your own making suddenly arrives, you’ll be rewarded with higher consideration and close rates. That’s revenue too. Just a bit slower. Could we shift this conversation altogether? Yes. Please. Let’s start at the end and work backward. Right now, every B2B brand has a win rate. If you, for example, compete against three better-known brands, your win rate is likely lower than that of the top three. What would it take to improve your win rate? Most likely, it is a combination of product changes, pricing, positioning, CX, and promotion, including analyst relations. Lead that conversation. The second conversational shift is to pricing power. Conduct a thorough analysis of the discounting required to close deals. Understand how much discounting impacts profit margins. Find out the last time you took a price increase. Reputational strength equals pricing power and higher close rates. Work with your CFO to build the model. Marketing does drive revenue. But it's not about SQLs.