Pricing Everywhere All at Once

March 21, 2023

Author

James D. Wilton

Managing Partner

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I love TV. Not trashy, “let me see what’s on” TV. I’m more for the high production quality comedies and drama. #classy 


I also love pricing. As you can imagine, combining these two loves is somewhat difficult. If you’re a lawyer, a policeman or a doctor, you are completely spoiled for vocationally relevant output. There aren’t many shows about pricing strategy. 



This all means that, as a pricing strategist, you really have to take your inspiration from nontraditional sources. And, maybe it’s because I live and breathe this stuff, but I actually think there’s a slew of pricing-relevant content out there, tucked away within shows like ‘The Sopranos’, ‘Mad Men’, ‘Parks and Rec’ and even ‘The Last of Us.’ 

Still skeptical? Let’s review: 


The Last of Us: “You have to kill me” – Anna (Ellie’s mom) 

We’re still all recovering from this. In this episode we learn how Ellie gained her immunity and lost her mother in Episode 9’s cold open. And it was a very cold, cold open. 


Anna: You have to kill me.
Marlene: I can’t.
Anna: You have to. 


This grim scene makes reminds me of how people think about their old pricing strategy after launching a new one. In order to capture value from it, especially if you have a large initial base, you have to migrate customers over from your old one, which implies not honoring the old structure anymore. It can feel very scary – and you can phase the transition after you have some new customer “success stories” to boost confidence – but there is no reward without risk. 



Ellie, Anna’s baby, wouldn’t have had chance to live if Anna had stayed with her. And your new pricing strategy won’t ever truly live up to its potential if you keep the old one. 


Parks and Rec: “Never half-ass two things. Whole-ass one thing.” – Ron Swanson. 


Ah, Ron. When he’s not trying to bring down the government from within, he’s dispensing sage wisdom to his friends. In this case, convincing Leslie to put all her efforts into running for city council and not trying to do two things at once. 


He may as well have been talking about giving your customers options for the pricing model they want. Executives often think some customers want to pay by usage, and others want to pay by users, so why not just let them choose? But this is rarely a good idea because 


(a) the customer usually chooses whatever option will result in the lowest prices for them, and 


(b) you never get never get to put a firm stake in the ground on how customers should perceive your value, which is one of the most important things your pricing model can do for you. Ideally, your pricing strategy and value proposition should be self-reinforcing. How can you do that if you’re non-committal about your pricing model? 


The one exception I’d made to this if you are using a “dummy” pricing model to make your core model seem more attractive. For example, it’s often a good idea to offer a “outcome-based” option alongside a traditional subscription, because the customer sees that if the product performs how they expect it to, they’ll pay more on the outcome-based model, and the subscription is therefore a good deal. Importantly, in this situation you still need to know what your preferred model is. 



Remember – having every pricing strategy is the same having as having no pricing strategy. Whole ass one thing! 

 
Sopranos: “People only allow you to see what they want you to see” – Jennifer Melfi
 

Dr.Melfi tops the TV league tables for sociopath enablement. In this clip, she’s helping Tony realize that, even though he’s not feeling on top of things, he doesn’t have to let people know that. Act as if. 


This made me think about simplicity in pricing structures. There’s always a trade off in pricing structures between simplicity – so that customers can understand the pricing – and granular monetization – so we can price differentiate effectively. In growing companies, the desire for customer acquisition, facilitated by simplicity, is so great that they often opt for over-simple structures than leave a lot of value on the table. 



This isn’t always necessary. Just because you have complexity in your pricing strategy doesn’t mean it’s always all shown to the customer. For instance, if I’m primarily setting price by number of users, but I change the price per user depending on the industry segment they are in, there’s potentially a lot to take in. But you don’t need the customer to see the full grid. Once you know their industry, you can just show them the price per user. It’s about controlling the optics of the pricing to give you the best of both worlds – simplicity for your customer, value capture for you. Perhaps Dr. Melfi would have made a better pricing strategist than a psychiatrist. 

Mad Men: “Make it Simple but Significant” – Don Draper 


Don Draper was the master of succinct powerful statements. Lifting too much from Don would perhaps be cheating for this article because both advertising and pricing could be considered to be closely related as elements of marketing. But in this case, he was talking about his drink order(!) so I feel ok with it. 


This is a *great* line for packaging. If you look at typical SaaS pricing pages, you’re hit in the face with a gluttony of check marks, representing which features are included within each tier. Such information overload can be super confusing and make it hard to understand why it would be beneficial to you to upgrade to the higher tiers. 



Ideally, what you want to do is build your tiers around a simple but significant difference in value delivered. Whittle it down to its bare essentials. That way you can drive people to the package that makes sense to them based on what they’re trying to achieve, or who they are. For a deeper dive here’s an article I wrote for Monevate on common packaging pitfalls. 


Better Call Saul: “Confidence is good. Facts on your side, better.” – Chuck McGill 

I haven’t forgiven Chuck for what he did to Jimmy, or “Saul” as he became. But – you had to give it to him – he did drop the odd pearl. And this quote about getting data and facts works in many places, not least of which is when it’s time to explain your new pricing strategy to your sales reps. 


When you change your pricing strategy or raise prices, it’s like a house of cards. If a customer pushes against it, and your sales reps don’t have the facts and data to justify the change, the whole thing comes tumbling down. Your salespeople will assume the changes were poorly baked. They won’t stand their ground, and you can look forward to approving a whole bunch of discounts. 


Unfortunately, it is incredibly common for executives, upon changing pricing, to just give the sales reps the “answer” without giving the detailed fact base. “Why bore them with the details?” Being told you can raise price by 10% feels a lot less trustworthy than being shown that customer willingness-to-pay, sourced via the comprehensive research we did, supports a 10% price increase. If your sales team is armed with all the justifications and data, it’s a much different conversation with the clients, and your house of cards becomes a house of.. um… bricks or something. 

You can read more about this in my post for Forbes here



That’s just a sample of some of the things that I’ve seen lately. If you think I’ve missed any obvious ones, or perhaps see pricing inspiration in movies or songs, drop me a note at james.wilton@monevate.com and I’ll include them in a future post. 

By James D. Wilton May 28, 2025
Outcome-based pricing (OBP) is one of the hottest topics in AI and SaaS monetization today. Instead of charging customers for access or usage, vendors charge based on measurable results. The idea? Customers only pay when they see real value. It sounds like the ultimate pricing model - perfectly aligned incentives, no wasted spend, and a direct link between cost and benefit. So why don’t more companies use it? Because in reality, OBP is much harder to execute than it looks. It’s been around for decades, but few companies truly succeed with it. That’s because OBP introduces complexity, risk, and friction that can make it more challenging than traditional SaaS models. Here are the five biggest pitfalls of OBP - and what to do about them. 1. Defining the Right Metric is Harder Than It Looks The biggest challenge in OBP is choosing a metric that accurately reflects value - without creating unintended consequences. If the vendor defines success too loosely, customers will feel overcharged. If the metric is too restrictive, vendors won’t get paid fairly. Example: Zendesk’s AI Ticket Resolution Pricing Zendesk introduced AI-powered customer service pricing based on resolved tickets. But customers pushed back - because Zendesk’s definition of a "resolution" didn’t always match what customers considered a real resolution. The lesson? A pricing metric must be: Meaningful to the customer (aligned with their definition of success). Tied to the vendor’s real value-add (not just surface-level activity). Difficult to game or manipulate (or customers will optimize against it). 2. Attribution is a Nightmare (Even with AI) Choosing the right metric is only part of the battle - there’s still another problem: Can you prove that YOUR product drove the result? In many cases, multiple factors contribute to an outcome. If revenue grows, was it because of the AI-powered sales tool, better sales reps, or an overall market uptick? Example: IBM Watson & Salesforce Einstein Both were positioned as transformational AI platforms, but customers struggled to isolate the AI’s impact. They could see business improvements, but couldn’t confidently say, “Watson/Einstein was responsible for X% of that success.” Notably, neither IBM nor Salesforce uses OBP for these products. Why? Attribution is too difficult. If vendors can’t prove they caused the outcome, customers won’t want to pay for it. A better approach: Control more of the process (the more your product influences the outcome, the easier it is to claim credit). Use proxy metrics (if direct attribution is hard, find leading indicators that correlate with success). Offer hybrid pricing (mix base fees with OBP so revenue isn’t fully dependent on attribution). 3. Baselining Gets Messy, Fast Even if a vendor picks the right metric AND can prove attribution, there’s yet another challenge: How do you measure improvement? The problem: Many OBP models assume a static baseline - but in reality, customer environments change over time. Example: Fraud Prevention in Financial Services Some AI vendors charge based on the reduction in fraudulent transactions. But this raises tough questions: What’s the starting fraud rate? (Pre-existing fraud levels may fluctuate.) Should the baseline reset each year? (If the vendor permanently reduces fraud, do they still get paid for maintaining it?) The lesson? Customers won’t want to pay for improvements they believe they would have achieved anyway. And vendors need a way to continuously justify their impact. A better approach: Define clear baseline periods (e.g. compare against the 6 months before implementation). Adjust pricing over time (the vendor’s impact might be front-loaded, requiring a different model in later years). Use tiered pricing (higher fees early, lower fees as impact normalizes). 4. Revenue Delays Can Kill a Vendor Even if everything else works - the metric is solid, attribution is clear, and baselining is fair - there’s still one big problem: Vendors often don’t get paid until months (or even years) after delivering value. This creates massive cash flow risks. Many SaaS companies depend on predictable, upfront revenue to fund operations. But OBP means revenue recognition is delayed, making forecasting difficult. Example: Riskified’s Outcome-Based Model Riskified, a fraud prevention platform, only gets paid when transactions are successfully approved without fraud. This aligns incentives - but it also means their revenue is inherently unpredictable. The lesson? While this approach works for Riskified, not every vendor can afford to wait for long-term verification before getting paid. (Note: Investors may not love it either - Riskified trades at just 1.89x EV/Revenue, a very low multiple for a SaaS company.) A better approach: Charge a mix of fixed fees + OBP to ensure steady cash flow. Offer performance tiers (higher base fees for lower-risk customers, full OBP for riskier bets). Use milestone-based payments - instead of waiting for full verification, charge in phases. 5. Customers Prefer Predictability - Even Over Potential Savings Even if an OBP model delivers better value, many customers still choose predictable pricing over variable costs. Why? Most businesses prefer stable, budgetable expenses over a fluctuating fee - even if the predictable price is technically more expensive. Example: Conversational AI in Customer Support A vendor offering an AI chatbot asked customers to choose between: Payment based on how many conversations the AI fully handled (OBP model). A flat subscription fee. Most customers chose the flat subscription. The lesson? Even if OBP is theoretically the best model, buyers often prefer predictability. The existence of an OBP option, however, can signal vendor confidence and reinforce the value of a fixed-price plan. A better approach: Give customers a choice (some will prefer OBP, but many want predictability). Use OBP as an anchor (show the OBP price, but steer customers toward a fixed option). Cap OBP costs to reduce buyer anxiety. Final Thoughts: OBP Works - But It’s Not for Everyone Outcome-based pricing sounds great in theory, but it’s tough to get right. When structured poorly, it leads to: Customer friction (over unclear metrics or unfair pricing). Revenue instability (due to attribution and baseline issues). Delayed payments (which can crush cash flow). The best OBP models: Pick the right metric - aligned to value and hard to manipulate. Solve the attribution problem - proving the vendor’s role in success. Balance cash flow - with a mix of fixed fees and variable components. OBP isn’t broken - but it’s not a magic bullet. Companies that embrace it need to go in with open eyes and a clear strategy. What’s your take? Have you seen OBP succeed or fail? Let’s discuss.
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