Budget Allocation Efficiency

You’ve got 4%. Now what? That’s the salary increase budget you're working with for this fiscal year. Not 5%, not 6% just 4%. And you’re being asked to use it to reward performance, retain top talent, stay market competitive, fix pay inequities, and support internal mobility. Sound familiar? Here’s a strategic way to allocate that 4% budget across four essential priorities: 1. Merit & Performance (~60% of the total 4% budget or 2.4%) Performance still matters, but the days of providing the same salary increase to all employees is behind us especially if you have a pay for performance philosophy. Tight budgets demand sharper differentiation. High performers should see meaningful increases. Use a merit matrix that includes the performance rating to ensure the highest performing talent feels the recognition. 2. Market Adjustments & Pay Equity Corrections (~25% of total 4% budget or 1%) Data-driven decisions and analysis are essential here. Use them to identify jobs or employees that are underpaid relative to market or similarly situated peers, especially in high-demand roles or historically underrepresented groups. 3. Promotions & Reclassifications (~10% of the total 4% budget or 0.4%) Use this to fund promotional increases and grade reclassifications. Promotions shouldn’t cannibalize your merit budget. Make sure they’re meaningful pay increases to recognize significant job responsibility changes. 4. Critical Retention Reserve (~5% of the total 4% budget or 0.2%) Set aside an “emergency reserve” for off-cycle adjustments. These are your just-in-time retention tools for flight risks, counter offers, or mission-critical roles where losing talent would be costly. Use sparingly but strategically. Why it matters: Without intention, budgets get used up quickly and by the end of the fiscal year there is nothing left to spend on critical talent. Allocating your 4% with purpose ensures alignment to business goals and talent needs. It also helps you communicate more clearly with leaders about how the overall budget is aligned to the various reasons for pay changes throughout the year. Build in budget reviews quarterly. Your compensation decisions should be agile especially in today’s labor market. How are you allocating your salary increase budgets this year? #Compensation #TotalRewards #PayEquity #HR #HumanResources #MeritPay #Retention #InternalMobility #CompensationPlanning #WorldatWork #SHRM #CompensationConsultant #FairPay

Doubled return on Google Ads by flipping branded vs. non-branded allocation. Most ad accounts don’t fail because the strategy is “wrong.” They fail because the money is in the wrong place. I audited an e-commerce brand spending $40k/month on Google Ads. On paper, their numbers looked fine: → $72 CAC (within target) → 3.1x ROAS → Branded campaigns dominating their reporting But here’s the problem: branded clicks were eating 65% of their budget. Which meant they were paying top dollar for customers who were already searching for them while starving the non-branded campaigns that actually brought net-new demand. So we flipped the allocation. 1. Reduced branded to protect efficiency, not inflate results. 2. Pushed the freed-up budget into non-branded categories where CPCs were undervalued. 3. Layered auction insights to identify which competitors were overbidding and avoided head-to-head battles. The results? ✅ CAC dropped from $72 → $44 in 45 days. ✅ ROAS jumped from 3.1x → 5.6x. ✅ Net-new conversions grew 41% while branded volume held steady. This wasn’t about “spending more.” It was about spending smarter. When most brands panic about rising CPAs, they start cutting campaigns. In reality, the win is usually hidden in how the budget is distributed, not how big it is. ↪ Running Google Ads but unsure if your budget is working as hard as it could? ↪ I’m offering a quick 15-minute ad spend audit (link in comments). ↪ I’ll pinpoint the 1–2 reallocation shifts that will instantly lift your ROI.

Let me walk you through the math that should make every CFO question their resource allocation. Using the latest 2025 industry benchmarks from SaaS Capital, here's the stark reality for a typical $200M ARR company: Revenue Responsibility: • Sales team: Manages $40M in new ARR (20% of total revenue) • CS team: Manages $160M in existing/expansion ARR (80% of total revenue) Budget Allocation Reality: • Sales: 13% of ARR ($26M) - up from 10.5% in previous years • Customer Success: 8% of ARR ($16M) - down from 8.5% in previous years Enablement Investment (based on industry benchmarks): • Sales enablement: ~$780K annually (3% of sales budget) • CS enablement: ~$160K annually (64% of CS teams spend <$200K on all programs, tools, and training combined) Investment per revenue dollar managed: • Sales: $780K ÷ $40M = $19.50 per $1M managed • CS: $160K ÷ $160M = $1.00 per $1M managed They're spending 19.5X more per revenue dollar on the team managing 20% versus the team managing 80%. In what other business context would this allocation be considered rational? Imagine if manufacturing allocated 19.5X more maintenance budget to machines producing 20% of output versus those producing 80%. Or if airlines invested 19.5X more in routes generating 20% of revenue versus those generating 80%. The CFO would be fired. Yet this exact irrational allocation persists in SaaS because of tradition, not logic. The Efficiency Data only makes this more baffling: • CS Efficiency: 1 CSM manages $2-5M in ARR • Sales Efficiency: 1 rep manages $600K-$1M in quota • CS is 2-5X more capital efficient, yet receives proportionally less investment The Revenue Economics defy conventional business wisdom: • According to BCG, "Over 25X more value is generated over a customer's lifetime than in the year when the customer is acquired" • TSIA data shows companies with dedicated CS teams achieve 17% base revenue growth vs. just 5% with a sales-only approach • Forrester Research found dedicated CS teams deliver 107% ROI within 3 years Remember the 120-day challenge from my earlier post? For this company, achieving a 1% churn reduction and 3% expansion increase would be worth millions, yet they're investing $1 per $1M in revenue for the team responsible for making that happen. The reality: McKinsey explicitly states that "slower-growing SaaS companies underinvest in customer success." This investment imbalance explains why many companies struggle to achieve the critical 3-5% improvements that transform business fundamentals. Next week, I'll explain why training is the most obvious investment decision in CS and why it's the most overlooked. What's the enablement investment ratio in your organization? Does it match your revenue responsibility ratio? Calculations based on industry benchmarks from SaaS Capital's 2025 Private SaaS Company Spending Benchmarks #CustomerSuccess #Enablement #Investment #ARR #ROI Previous Post: https://lnkd.in/g_bpYGzr Next Post: https://lnkd.in/g76FYFMf

Stop using ROI only when evaluating the Effectiveness of Paid Media channels 📊 For years, marketers and performance marketing specialists have been using Return On Investment (ROI) as the main metric to measure marketing effectiveness. Unfortunately, this has led to wrong conclusions and incorrect optimization and budget allocation across media channels. Why? ROI is not an effectiveness metric; it's an efficiency metric. In isolation, ROI doesn't provide insights into the impact on business results. It will always favor tactics that cost very little money and generate very little revenue. Therefore, the easiest way to boost ROI is to reduce the budget, which is why you should never draw conclusions based solely on ROI numbers. Instead, interpret the results using two other critical factors: 1. Share of Spend Understanding where your budget is allocated across different media channels is essential. Share of Spend helps you see if your investment aligns with your strategic goals and market opportunities. Are you putting enough resources into the channels that matter most to your target audience? 2. Share of Effect This metric gauges the impact each channel has relative to others. Share of Effect measures the contribution of each channel to your overall marketing objectives. It helps you identify which channels are truly driving your desired outcomes. By considering Share of Spend, Share of Effect, and ROI together, you gain a more nuanced understanding of your paid media performance. This holistic approach ensures that your marketing investments are not only financially efficient but also strategically effective in achieving your broader business goals. #marketing #roi #paidmedia #advertising #measurement

“Should we add more CSMs, or add more CS Ops?” It’s the allocation question every CS leader faces as budgets tighten and expectations rise. The wrong choice can damage customer retention, blow the budget, or both. The best CS leaders are following a simple formula: Make tech investments where they create efficiency. Make human investments where they generate retention and growth. The Clear Division of Labor Technology excels at tasks requiring consistency, speed, and scale where human judgment isn’t critical: • Administrative work and data processing • Routine communications and follow-ups • Process orchestration and workflow management Humans excel at tasks requiring judgment, creativity, and strategic thinking: • Strategic guidance and complex problem-solving • Relationship building and value creation conversations • Turning satisfied customers into advocates But here’s where segmentation changes everything. Segmentation Drives Everything What works for enterprise accounts doesn’t work for SMBs: High-value segments require human investment. The impact on retention and growth justifies the cost. High-volume segments require tech investment. They value speed and reliability, and unit economics demand efficient delivery. Scaling Isn’t Just Automation — It’s Trust Many CS leaders assume scaling means automating everything. But trust - the foundation of customer success - scales through a strategic blend of tech and human touch: Trust scales through consistency- Reliable delivery of promises, whether automated or human Trust scales through competence- AI-powered insights helping CSMs provide better guidance Trust scales through transparency- Proactive updates that keep customers informed Trust scales through personalization - Understanding unique needs at scale The Resource Allocation Framework Your segmentation strategy drives your resource allocation decisions. Map your customer journey by segment and classify touchpoints as either: • Efficiency-focused (perfect for tech) • Growth-focused (requiring human investment) Then audit where you’re using expensive human resources on automatable tasks, and where you’re using automation for interactions that demand human judgment. CS organizations that execute this principle operate with fundamentally better unit economics. They deliver personalized, strategic value to high-value customers while serving high-volume customers efficiently. They aren’t choosing between efficiency and growth - they’re achieving both. The framework is simple: tech for efficiency, humans for growth. But applying it requires knowing your customers well enough to understand which approach builds the most trust with each segment. Where are you misallocating resources between tech and human investments?

In a down market, the loudest voice isn’t always the one spending the most—it’s the one spending the smartest. For most of us, market volatility is real—and it’s leading to pipeline softening, tighter budgets, and an executive team that wants to see exactly where every dollar is going (and what it’s doing). So how do you ensure marketing efficiency without losing momentum? It’s all about balance and optimization across the full funnel. Here's how we’re approaching it: Marketing leaders must balance short-term wins vs. long-term growth. You are fighting to show ROI for every dollar. For many marketers, that means driving most of your budget into paid media and events. But if you're not focusing on signals, you are just spraying and praying and hoping someone happens to be in market. But if that’s all you’re relying on? You're renting results. It's important to not throw out the baby with the bathwater. Continue allocating a portion of your budget toward long-term bets like content and SEO because those channels compound over time. And they’re a lot more cost-effective when CAC scrutiny hits. Funnel efficiency matters more than ever. Every stage—awareness, consideration, conversion, and expansion—should earn its keep. We run regular funnel diagnostics to identify drop-offs and inefficiencies: Are MQLs converting to pipeline? Is our nurture strategy working? Do we have sales enablement assets mapped to buying stages? If something’s underperforming, we test before we scale. Small experiments, tight feedback loops, quick pivots. Efficiency ≠ cutting spend—it means spending smarter. This is not about doing less. It’s about doubling down on what works and eliminating what doesn’t. That means: Clear attribution models Tight alignment with sales Ruthless prioritization Marketing teams that do this well will come out stronger. Because when growth returns (and it will), we’ll have the systems, processes, and channels in place to scale smarter. For my marketing leader friends, I'm curious—how are you shifting your marketing strategy this year to make every dollar count?

How to Set Marketing Budgets at Different Stages of Growth: A 0 → 100 Journey Real-world case reflections from scaling three brands across early, growth, and scale-up stages. --- Stage 1: From 0 to 1 — The Search for Traction The context: You’re building something new. There’s no brand awareness, no repeat user base, no real benchmarks. Just hypotheses. Budgeting approach: Don’t think % of revenue. Think % of burn dedicated to learning. Framework to use: Allocate 70% to demand validation (Search, Social, Landing Pages, Influencers) 20% to brand experiments (creatives, storylines, positioning tests) 10% to tools + infra (analytics, CRM, A/B testing) Key metric: Cost per learning, not cost per lead. You're buying insight. How to talk to the CFO: > “We’re not spending to scale. We’re investing to learn what works, so we don’t waste 10x later.” --- Stage 2: From 1 to 10 — The Growth Engine The context: You've found PMF. Some channels are working. Retention is improving. Now you need scale. Budgeting approach: Start thinking marketing as a % of revenue — typically 15–30% depending on LTV:CAC dynamics. Framework to use: Full-Funnel Allocation 40% on performance marketing 30% on brand & content 20% on retention & CRM 10% on community, influencer & organic Add measurement layers: Attribution model Cohort analysis CAC payback period How to talk to the CFO: > “We’ve found our channels. We’re now scaling them predictably while improving CAC efficiency. Here’s the LTV:CAC projection by cohort.” --- Stage 3: From 10 to 100 — The Moat Game The context: You’re a known player. Now, it’s about building brand equity, increasing market share, and defending CAC against rising competition. Budgeting approach: Focus on portfolio thinking — mix of growth, brand equity, and future bets. Budget becomes 8–15% of revenue depending on margins. Framework to use: Portfolio Model Core growth (40%): proven performance channels Brand equity (30%): video, sponsorships, top-funnel pushes Retention & loyalty (15%) Innovation bets (10%) Infra & data stack (5%) CFO conversation now changes: > “We’re not just chasing growth. We’re protecting margin, building brand power, and investing in the future stack. Here’s how each line drives either revenue or long-term value.” Final thoughts: There’s no one-size-fits-all answer to “What should my marketing budget be?” But there is a right question: > “What does this stage of the business need most — and how can marketing deliver it efficiently?” Budget follows clarity. Clarity follows stage-awareness. --- Would you like a free budgeting template for these 3 stages? Drop a “Yes” and I’ll send one across.

Scaling a six-figure Paid Search budget by 20% month-over-month while maintaining efficiency isn’t easy. Here’s how we tackled this on a project for VEED.IO: 📊 𝗪𝗲 𝘀𝘄𝗶𝘁𝗰𝗵𝗲𝗱 𝘁𝗼 𝗥𝗢𝗔𝗦, 𝗮 𝗯𝗲𝘁𝘁𝗲𝗿 𝗳𝗶𝘁 𝗳𝗼𝗿 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀 For subscription products like VEED, not all users are equally valuable—churn rates, retention, and ARPU vary widely. CAC alone doesn’t account for these differences, so we moved to ROAS reporting. This allowed us to measure campaign performance with a focus on long-term value, rather than just upfront conversions. 🤝 𝗪𝗲 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝘀𝗽𝗲𝗻𝗱, 𝘂𝘀𝗲𝗿 𝗮𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻, 𝗮𝗻𝗱 𝗿𝗲𝘃𝗲𝗻𝘂𝗲 𝗱𝗮𝘁𝗮 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗨𝗧𝗠𝘀 To make ROAS reporting possible, we connected Google Ads spend data with VEED’s first-party payment (Stripe) and attribution models (Google Analytics). This integration allowed us to connect recurring revenue to specific campaigns, ad groups, and even keywords, providing a clearer picture of performance. 🐭 𝗪𝗲 𝗰𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗲𝗱 𝗥𝗢𝗔𝗦 𝗮𝘁 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗹𝗲𝘃𝗲𝗹𝘀 𝗮𝗻𝗱 𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝗶𝗲𝗱 𝗸𝗲𝘆𝘄𝗼𝗿𝗱-𝗹𝗲𝘃𝗲𝗹 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 Our granular reporting revealed (expectedly) that ROAS varied significantly across campaigns, markets, and use cases. At the keyword level, we saw the most variation—some features and search terms drove much higher value than others. 🔎 𝗪𝗲 𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝗶𝗲𝗱 𝘄𝗵𝗶𝗰𝗵 𝗸𝗲𝘆𝘄𝗼𝗿𝗱𝘀 𝗮𝗻𝗱 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 𝗱𝗲𝘀𝗲𝗿𝘃𝗲𝗱 𝗺𝗼𝗿𝗲 𝗯𝘂𝗱𝗴𝗲𝘁 Using ROAS data, we pinpointed keywords and use cases with the fastest payback period and highest ROAS, ensuring they received a larger share of the budget. Similarly, we identified lower-performing strategies that were better candidates for reduced spend, enabling more efficient allocation overall. 📦 𝗪𝗲 𝗿𝗲𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗲𝗱 𝘁𝗵𝗲 𝗰𝗮𝗺𝗽𝗮𝗶𝗴𝗻 𝘁𝗮𝘅𝗼𝗻𝗼𝗺𝘆 𝘁𝗼 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲𝘀 VEED’s original campaign structure was organized by market at the Campaign level and by features at the Ad group level. We flipped this model, creating campaigns based on use cases (e.g., “Add Subtitles”) and countries within them. This shift improved controlled budget allocation to the most valuable features. 💯 𝗢𝘂𝗿 𝘁𝗲𝘀𝘁 𝗰𝗮𝗺𝗽𝗮𝗶𝗴𝗻 𝘁𝗮𝘅𝗼𝗻𝗼𝗺𝘆 𝗱𝗿𝗼𝘃𝗲 𝗯𝗶𝗴 𝘄𝗶𝗻𝘀 Our ROAS insights led to a revamped campaign structure, which directly impacted VEED results: • 20% increase in subscriptions • 12% higher ARPU • Flat CAC despite increased spend This project is an A+ example of of how deep marketing analysis can (and should) drive actionable changes to campaigns. I’ll be sharing the full article article in the comments for those interested in reading about the set-up more in-depth. 👇

Spreading your budget evenly wastes money. Concentrate on winners. Companies make this mistake constantly. They distribute budget roughly equally across dozens or even hundreds of keywords. It seems logical but it's also completely wrong. Here's what actually happens: You have keywords that drive qualified sales meetings consistently, and then you have keywords that generate clicks but never convert to pipeline. When you spread budget equally, you're funding both groups the same way. You're spending just as much on keywords that waste money as you are on keywords that make money. The key is to look back to see which keywords actually drive qualified sales meetings consistently. When we pull that data, we typically find that no more than five keywords consistently perform. Honestly, sometimes it's even less. But companies keep spending equal amounts on one hundred keywords when they could focus their entire budget on the five that work. The solution requires tracking which keywords actually drive sales meetings, not just conversions. Then reallocating aggressively based on that data. Which of your keywords are earning their budget allocation?

You don't need to run experiments on every channel in your mix. In fact, you shouldn't. The channels worth testing share two characteristics: 1) You spend significant money on them 2) You're uncertain about their incremental performance For enterprise brands, testing a channel with $10K/month in spend won’t provide learnings that move the needle for the business. On the other side, testing a channel with high spend but very low uncertainty across measurement methods isn’t going to tell the brand anything new. At Recast, we built a report called the “Uncertainty Contribution” that visualizes this exact intersection. It shows clients which channels are driving the most total uncertainty in their forecasts. This can reveal situations like the following: Your model forecasts $52-60M in revenue next quarter. That $8M range? The chart shows that 40% of that uncertainty is coming from Meta Prospecting, where you're spending $2M/month. Meta Prospecting becomes your testing priority. Meanwhile, Display spend might have similar uncertainty associated with its measurement, but you only spend $40K/month there. Even perfect knowledge of Display’s incremental ROI will lead to decisions that meaningfully impact your business. The Uncertainty Contribution chart makes bet prioritization systematic: - High spend + high uncertainty = test priority - High spend + low uncertainty = secondary testing priority - Low spend + high uncertainty = test before scaling - Low spend + low uncertainty = maintain and monitor Our most successful clients use this chart to create experimentation roadmaps that yield clearer forecasts, better budget allocations, and actual profit improvement. The math is simple: reducing uncertainty on your largest media investments delivers the highest ROI on testing.