Pricing Strategies for Project Deliverables

Set and forget is not a pricing strategy ! Price--> Design--> Build We know that's what everyone says, but thats an oversimplification of what the entire process should look like. The assumption your pricing was correct in the pre-design phase and doesn't need change is dangerous, dangerous, dangerous !! I have seen too many physical and software products change drastically between initial design to final delivery. Product owners will typically assume that pricing still holds. You have to change that philosophy. In the real world we need a lot more iteration in price: Step 1: Initial Price: This stage you quantify the value and set an initial target price. This is a combination of internal/external research, some value quantification and pricing knowledge. Step 2: Design: With that price info, the product team designs a product that hits product and profitability targets. This is also where you need to keep track of the product margins. Often product will go design a better product at the expense of higher cost, and margins suffer before launch. Step 3: Reprice: Now that we know the new design constraints that impact the profitability, this stage gives you the opportunity to reprice the product based on the design. If substantial value has been added, price should go up. Do not fall into the 'lets over deliver on value and keep price same' trap. Step 4: Build: Now with that new price info and product roadmap the product goes through the build stage. Step 5: Pre launch reprice : Now significant time may have passed since last price review. The market for the product, the economy etc may have changed. This stage can assist in making last changes before product goes out. Good time to also establish guardrails for price performance, discount strategy, or sales strategy. Step 6: Launch: Goes without saying the product is out in the real world. Great way to capture feedback. Also a stage where performance is measured against the price guardrails. Step 7: Reprice 3: Based on sales feedback, you start charting next steps. Selling too slow, you may need discount or reprice. Selling too fast, it may be overdelivering on price vs value. Pricing metric may need change. Fx may have changed. This is the price adjustment stage, should be annual or semi annual. You can incorporate these steps into new product introduction framework or annual or semi annual pricing strategy process, either ways it will help establish good pricing principles in the org. I know of many products that once designed were never repriced years into its life.. Surely things must have changed all those years... Think of Pricing as a lifecycle !! -------------------------- We are in #Pricingtribe.

📦 Jobs-Led Pricing: A 10-step framework for transforming feature-led products into monetization-ready, jobs-based pricing models. Built on 4 stages: 1. Product (Discovery Layer) 2. Value (Logic Layer) 3. Customer (Preference Layer) 4. Pricing (Monetization Layer) 🔹 STAGE 1: PRODUCT [Discovery Layer] 🔹 Step 1: Feature Inventory What it is: ▪️ List every feature, tool, and function in the product
▪️ Include hidden, premium, or internal-use features Why it matters: ▪️ Creates a complete picture of what’s being delivered
▪️ Prevents missing monetizable elements 🔹 Step 2: Feature to Plan Mapping What it is: ▪️ Show how features are bundled into pricing plans today
▪️ Expose arbitrary or legacy packaging logic Why it matters: ▪️ Reveals pricing misalignment with value
▪️ Highlights over- or under-incentivized plans 🔹 Step 3: Feature Usage Mapping What it is: ▪️ Track actual customer usage of each feature
▪️ Look for engagement patterns by segment Why it matters: ▪️ Identifies “dead weight” vs “core value” features
▪️ Helps assess ROI per feature 🧠 STAGE 2: VALUE [Logic Layer] 🔹 Step 4: Feature Valuation What it is: ▪️ Qualitatively or quantitatively assign value to each feature
▪️ Use proxies: time saved, revenue unlocked, cost reduced Why it matters: ▪️ Establishes which features are worth monetizing
▪️ Anchors the price-to-value logic 🔹 Step 5: Jobs Identification What it is: ▪️ Identify core Jobs-To-Be-Done (JTBD) your product enables
▪️ Use user interviews, surveys, task analysis Why it matters: ▪️ Shifts the model from features to outcomes
▪️ Connects monetization to customer success 🔹 Step 6: Feature–Jobs Mapping What it is: ▪️ Map each feature to one or more customer Jobs
▪️ Create a logic layer: feature → outcome → value Why it matters: ▪️ Bridges product design with pricing strategy
▪️ Enables bundling and upsell opportunities around outcomes 🎯 STAGE 3: CUSTOMER [Preference Layer] 🔹 Step 7: Rank Jobs What it is: ▪️ Prioritize Jobs by importance and frequency
▪️ Use customer feedback and behavior data Why it matters: ▪️ Surfaces which outcomes matter most
▪️ Enables tiering or segmentation logic 🔹 Step 8: Value Jobs What it is: ▪️ Quantify perceived value of each Job
▪️ Use surveys, conjoint analysis, BWS, or proxies Why it matters: ▪️ Links value perception to potential willingness to pay
▪️ Avoids feature-based pricing traps 💰 STAGE 4: PRICING [Monetization Layer] 🔹 Step 9: Value Capture [%] Analysis What it is: ▪️ Decide what % of value created you can capture
▪️ Compare to industry benchmarks or strategic posture Why it matters: ▪️ Sets pricing defensibility
▪️ Avoids overcharging or leaving money on the table 🔹 Step 10: Pricing Metric / Model What it is: ▪️ Choose pricing metric: per seat, usage, credits, % of revenue, hybrid
▪️ Align it to how value is delivered + Jobs solved Why it matters: ▪️ Ensures pricing scales with value
▪️ Sets the business up for sustainable revenue growth #Pricing #JLP

Stop charging for the thing you’re trying to reduce ⛔ Per-seat pricing punishes collaboration and is antithetical to your mission if your product automates work. Pure usage punishes exploration when teams most need to iterate. And it elongates the learning curve, as you fear hitting enter. Pricing is part of product design. It shapes behavior long before features do. Here’s the simple playbook I drafted to pick the metric that reinforces outcomes (not fights them) 👇 If your product’s value grows with… 🤝 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 → avoid per-seat. Price by project or workspace. 🌊 𝐓𝐡𝐫𝐨𝐮𝐠𝐡𝐩𝐮𝐭 → usage can work, but add guardrails (credits, alerts, soft caps). Better yet, connect it with the client's unit of work 🌐 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐞𝐝𝐧𝐞𝐬𝐬 → charge per data source/integration/environment, not per human. ✅ 𝐎𝐮𝐭𝐜𝐨𝐦𝐞𝐬 → consider per decision package (like case closed for support) often in bundles or scaling plans. When we moved Zentrik teams from seats to flat fees with project soft limits, more stakeholders joined from week one, exploration went up, and decision latency dropped–no one had to “justify another seat” Why this aligns incentives » Collaboration stays free invite reviewers early; no login rationing. » Bills stay boring finance can forecast initiatives per quarter. » Automation is rewarded if you save time, we don’t lose revenue for removing “seats” What this looks like in practice: 1. A plan includes up to N active initiatives/projects per workspace. 2. Unlimited collaborators and viewers. 3. A gentle overage buffer for spikes, then a human conversation. Seats exist only for permissions, not price. --- If you’ve shipped pricing that changed user behavior in a surprising way, what was it? I’d love real stories and counterexamples! #ProductManagement #Pricing #SaaS #ProductOps

Every $150/hour you charge puts you in direct competition with every other agency quoting hours. Every value-based project puts you in competition with business outcomes. Most $2M - $10M agencies stay trapped in hourly billing because it feels safer. You can predict cash flow, track utilization, justify bench costs. But hourly rates create a ceiling on your gross margin that value pricing removes entirely. Here's what changes when you shift to value-based pricing: 1. Your proposals compete on results, not rates. Instead of competing with 15 other agencies on who can deliver faster or cheaper, you're solving a $500K revenue problem or protecting 40% of at-risk revenue. The conversation shifts from cost to ROI. 2. Utilization pressure disappears. When a developer solves the problem in 40 hours instead of 80, you don't lose money. You deliver value faster and keep the same project fee. 3. Presale conversion improves. Prospects understand paying $50K to solve a revenue retention problem better than paying $150/hour for undefined development work. The value connects directly to their P&L. 4. Account management becomes strategic. Your teams focus on delivering measurable outcomes rather than logging billable hours. QBRs shift from time reports to business impact discussions. 5. Pipeline pressure reduces. Higher-margin projects mean you need fewer clients to hit the same revenue targets. Your team can focus on fewer, better relationships. The transition takes 6 to 12 months, but agencies that make the shift see gross margins increase 15 to 25 percentage points. The business becomes more predictable and less dependent on constant new client acquisition.

If you’re like me, you’re probably the bottleneck in pricing engagements. Here’s how I fixed that in our firm: 1. Made a list of all of our services… every possible deliverable. This is a good exercise by itself because it helped me realize we were doing too much for too many. 2. Broke down individual steps for each service, including specific roles for each step (which doubled as an SOP for our workflow tool Karbon). 3. Set an hourly cost rate for each person involved and estimated time required for each step. 4. Researched market pricing for every service identified in step one. Set that as the target fee for each individual service. 5. Made sure we could hit our target profit margin based on the market value of the service, and the aggregate cost rate to provide the service. NOTE: under no circumstances should the fee from step four depend on the cost rate calculated in step three. I wanted the data just to make sure that the service was profitable. If it wasn’t, then we stopped providing it and opted instead to find a referral partner like Gusto. 6. Created a dynamic pricing tool that considered every relevant factor that I would normally consider when I was doing my “gut check” when pricing an engagement. 7. Once the pricing tool was substantially complete, put every service and standard fee into Ignition so the team could just point and click to create engagements. 8. Took it a step further and created proposal templates in Ignition to group a set of standardized services based on client profiles. It’s not perfect, and it needs to be updated from time to time, but the result is that for a standard service, anyone on my team can price it without me getting in the way.

When I first started consulting, I was underbilling like crazy. Here are the biggest pricing mistakes I made (and how I fixed them) 🔴 Project-based pricing I charged per project, thinking it gave clients clarity. The mistake? I didn’t account for scope creep. One “small” extra request turned into five, and suddenly I was working double the hours for the same fee. 👉 If you use project pricing, have a plan to monetize when things spiral. 🟠 Hourly-based pricing I figured if I charged for every hour worked, I’d never lose money. My clients also loved it because they only paid for what they got. But… I quickly realized there are only so many hours in the day. Unless I kept raising rates, my revenue had a hard ceiling. 🟡 Retainers This was a big step forward. For the first time, my income was predictable. No more wondering what I’d earn by the end of the month. But I was still charging for time, not results. The floor felt safer, but the ceiling was still there. ✅ Value-based pricing (VBP) This is where everything shifted. I stopped charging for inputs (hours, deliverables) and started charging for impact. This is when my pricing became aligned with the value I was delivering to clients. Pro tip: Value-based pricing isn’t technically a billing model. It’s a mindset shift that can be applied to whichever model you’re already using. A good rule of thumb? Charge 10-30% of the value you create. Here’s what that looked like for my sales enablement services: 🍔 Restaurant client - Sales per seat went from $34 → $38 after better training - 50-seat restaurant, open 12 hrs/day with 90-min turnover - $4 increase = $1,600 more revenue/day - That's value of roughly $584,000 more per year 💡 Fair fee under VBP: $58k–$175k 🚗 Car dealership client - Average car price: $40,000 - 1,000 cars/year → improved close rate by 5% - That’s 50 more cars = $2M more per year 💡 Fair fee under VBP: $200k–$600k Does that sound steep? Not when you frame it like this: 👉 For every $1 you spend on me, you will see $5–$10 back. That’s when consulting finally became scalable. If you’re a consultant: Are you charging for your time… ...or for the transformation you deliver? Next week, I’ll share how to pitch value-based pricing to clients (and where/when it’s an easier sell). #Consulting #PricingStrategy 

Despite pricing being the most powerful business lever for growing Operating Profits, many mid-market companies still rely on static, cost-plus formulas to generate prices, missing key opportunities to drive higher profits on both ends (leaving money on the table and missed sales opportunities). Price optimization is built on advanced analytics, including AI and machine learning, to set prices that maximize profitability while aligning with broader business objectives (i.e., balance revenues with gross profit $). It leverages transactional and market data to deeply understand customer behavior and adapt to changing inputs (i.e., competitor prices, inventory levels, seasonality, etc.). Whether you’re in manufacturing, distribution, or retail, some form of an insights-driven, dynamic, and automated pricing strategy is essential for profitable growth. In the below article (see comments), we explore foundational pricing methodologies such as dynamic pricing, value-based pricing, and competitor-based pricing: 1. Dynamic Pricing: Adjust prices in real-time (or near real-time) based on competitor actions, inventory levels, market trends, and financial goals. Amazon’s dynamic model exemplifies how real-time adjustments can balance a low-price reputation with margin optimization. 2. Value-Based Pricing: Set prices on perceived customer value rather than costs or competitors. This ensures your pricing reflects the unique differential value you provide. A simple approach is assigning a competitive price index premium based on detailed customer research. 3. Competitor-Based Pricing: Position products strategically by considering competitors’ real-time prices. Techniques like premium pricing, price matching, and loss leader pricing help assign the right comp-pricing strategy to each customer or product segment. Successful price optimization requires avoiding pitfalls. Overcomplicating pricing models can lead to inefficiencies and erode trust among commercial teams—we’ve seen this too often. Relying on opaque “black-box” AI systems can also cause a loss of control and transparency. The key is balancing sophistication with simplicity, ensuring strategies are effective and embraced by the sales team. Building or insourcing your price optimization capabilities offers significant advantages. It aligns your pricing with business goals, provides greater decision control, and strengthens long-term pricing acumen. You can create a robust, customized pricing engine tailored to your unique needs by fostering collaboration across teams and continuously refining your models. Mid-market companies have a unique opportunity to elevate price optimization from a tertiary (or non-existent) concern to a core business function. Achieving this requires a deliberate, thoughtful approach that leverages advanced analytics, your internal/external data assets, and a collaborative approach with your Finance/Pricing and Commercial teams. #revenue_growth_analytics

The Hidden Cost of "Just One More Thing" during a Cybersecurity Assessment project. I've seen it happen hundreds of times...a well-planned cybersecurity assessment suddenly balloons with "quick additions." Each request seems small in isolation: "Could you just check these extra servers too?" or "We also need this compliance report." Before you know it, your carefully scoped project consumes 40% more resources than budgeted, yet your revenue remains fixed. The math is brutal: your projected 30% margin evaporates into single digits-or worse. This isn't just an occasional headache. In my conversations with service business owners, scope creep consistently ranks as their #1 profitability killer. The good news? This is solvable with the right approach to scoping. After implementing these practices with dozens of service businesses, I've seen scope creep reduction of nearly 30% and margin improvements of 15-20%: **1. Modularize your services using standardized templates** Break cybersecurity assessments into discrete, clearly defined components like asset inventory, vulnerability scanning, policy review, and remediation planning. Define exactly what's included-and just as importantly, what's NOT. When you receive that inevitable "Could you just..." request, you can confidently reference your predefined scope boundaries and offer the additional work as a properly priced add-on. **2. Implement multi-phase approval gates** Structure your projects with clear milestone checkpoints requiring client sign-off before proceeding. Document the current scope at each gate and establish a formal change request process for anything beyond original parameters. This prevents the dreaded "scope amnesia" where clients forget what was initially agreed upon. **3. Shift from time-based to risk-based pricing** Time-based pricing links your compensation to hours worked, not value delivered. Instead, develop tiered pricing frameworks that account for system criticality, compliance complexity, and threat exposure. This allows you to embed appropriate risk buffers and contingencies while communicating price in terms of business outcomes rather than just labor. **4. Get it in writing, every time** Create bulletproof SOWs that explicitly define deliverables, exclusions, client responsibilities, and change order procedures. Include specific examples of what constitutes a change requiring additional fees. Make these documents visual and client-friendly-not legal walls of text-to ensure they're actually read and understood. Your ability to deliver excellent service while maintaining healthy margins depends primarily on your discipline during the scoping phase. By establishing clear boundaries upfront, you transform scope management from a source of friction into a foundation for long-term client trust. What's one change you've made to your scoping process that helped reduce scope creep?

🔍 Pricing Strategies. ➡ Cost-Plus Pricing Price = Cost + Markup Simple and ensures profit margin. Often used in manufacturing and contracting. ➡ Value-Based Pricing Based on perceived value to the customer rather than cost. Common in luxury or brand-sensitive industries. Role of Predetermined Pricing in Forecasting, Analysis & Budgeting Forecasting Predetermined prices help estimate future sales volume and revenue. Pricing assumptions are central in financial models and sales projections. Financial Analysis Assists in calculating profit margins, break-even points, and return on sales (ROS). Key to assessing product viability, pricing power, and cost-efficiency. Budgeting Pricing influences revenue budgets, marketing budgets, and cost planning. Supports cash flow planning and resource allocation. ➡ Competitive Pricing Based on competitors' pricing. Often used in price-sensitive markets or commodities. ➡ Penetration Pricing Low price to enter market and gain share quickly. Increases volume, reduces per-unit cost over time. ➡ Skimming Pricing High initial price for new/innovative product. Used when demand is inelastic initially. ➡ Psychological Pricing Prices like $9.99 instead of $10.00 to seem cheaper. Influences consumer behavior. ➡ Dynamic Pricing Adjusts prices based on demand, time, or competition. Common in airlines, hotels, e-commerce. ➡ Bundle Pricing Combine multiple products/services for a single price. Increases perceived value. 📊 Case Scenario: Launching a Bluetooth Speaker Step 1: Strategy Choice After market research, you find customers perceive high value. You decide to go with Value-Based Pricing at $60. Step 2: Forecasting Using $60 price × 2,000 units = $120,000 in forecasted revenue. Profit forecasting helps you plan cash inflow and potential reinvestment. Step 3: Financial Analysis Calculate: Break-even volume = Fixed Costs / (Price - Variable Cost) → $20,000 / ($60 - $25) = 571 units Gross Margin = (Price - Variable Cost) / Price = 58.3% Contribution Margin = (Price - Variable Cost) / Price Step 4: Budgeting Set marketing and operational budgets knowing you'll generate ~$90,000 in profit. Allocate funds for advertising, distribution, future R&D, etc.

Complete Guide on How to Price Agentic Workflows I made $60K+ with this pricing system: Everyone wants to make money with AI workflows, but pricing is the part nobody teaches you. How do you define the value? How do you justify the number? How do you say the price with confidence? So here's the guide I wish I had when I started. 1️⃣ Stop charging by the hour Charge for the outcome instead. Every workflow delivers 3 types of value: ↳ Saves money (cuts costs) ↳ Saves time (frees up hours) ↳ Reduces errors (prevents expensive mistakes) If you charge hourly, you cap your own income. The faster you build, the less you make. That's the wrong game. 2️⃣ The 2 core pricing models ↳ Value-based project pricing (based on business impact) ↳ Monthly retainer (for ongoing maintenance and optimization) Most freelancers only use one. The best ones use both. 3️⃣ The 10x ROI rule This is the number that makes pricing obvious. Price at 10% of annual savings. Example: ↳ Workflow saves €12K/year ↳ You charge €1,200 That's a no-brainer for any business owner. 4️⃣ How to price retainers Simple formula: ↳ Estimate your monthly cost ↳ Apply a 50% margin (double it) No guessing. No undercharging. 5️⃣ Present the transformation, not the number Lead with what changes for them. Define what "done" looks like before you say the price. Scope it clearly so there's no room for creep. Then say the number. 6️⃣ Handle objections by adjusting scope Never discount your price. If the budget is tight: ↳ Remove deliverables ↳ Reduce scope ↳ Phase the project Your price signals your value. The moment you discount, you signal the opposite. 7️⃣ Turn one-off projects into recurring income Every project is a door to a retainer. Offer: ↳ Maintenance ↳ Optimization ↳ Training ↳ Reporting One client. Multiple invoices. 8️⃣ The V.A.L.U.E. framework ↳ Vision — tie the automation to real business goals ↳ Assess — audit and map the current workflow ↳ Leverage — find the opportunities with outsized returns ↳ Unveil — present the solution with simple ROI math ↳ Elevate — review, optimize, and expand continuously If you want to learn how to price and sell AI automations properly, this is where you start. Full guide + community here: https://lnkd.in/d5nE_Fuc ♻️ Repost to help your network