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Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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Topline Summary
- We’re operators who ship pricing, not analysts who write recommendations. Monetizely is run by former pricing, product, and PMM operators from modern software companies - not generalist consultants.
- We treat monetization as a system, not a price point. Pricing changes only work when packaging, metric, pricebooks, discounting guardrails, and enablement move together.
- We bias toward high-velocity testing and pragmatic evidence: We’re agile over waterfall and use research methods selectively—enough rigor to make the decision confidently, without expensive studies by default.
- We are fluent in usage-based pricing and AI/agentic monetization, including variable COGS (tokens, compute, inference) and value-aligned metrics.
- We design for adoption: We operationalize the model with pricebooks, discount guidelines, calculators, and sales launch support, plus governance so the new model actually gets used.
- We build in-house products that hyper accelerate pricing projects and significantly reduce research costs.
Outcomes We Drive
- Bigger deals, with sales actually using the model. We align tiers and price architecture to the GTM motion, then lock it in with a model the field can sell, delivering results like 15–30% higher deal sizes with 100% sales adoption, including rationalizing packages from 12 to 5 across product lines.
- Faster growth from simpler packaging. We cut SKU sprawl and buyer confusion, for example moving from 14+ add-ons and 1,000+ SKUs to clear bundles, driving outcomes like +37% customer growth, -22% churn, and 115% net dollar expansion in enterprise.
- Higher deal sizes without deeper discounting. We fix packaging and quoting structures that force discretionary discounting and create shelfware, driving outcomes like 15–40% higher ASPs (avg selling prices) with close to 100% sales adoption, without needing deeper discounts.
- Safe transitions to usage or hybrid pricing. We design the guardrails and quote-to-cash alignment across product metering, billing, CPQ, and sales compensation so the shift does not blow up revenue, including examples of eliminating a modeled 50% revenue drawdown during a platform fee plus usage rollout.
- Confident launches for new lines and AI add-ons. We validate positioning and willingness-to-pay so you launch with proof, not hope, including outcomes like 20–30% higher WTP and 2–3x higher average price-point WTP for a new product line.
- Premium pockets identified and priced properly. We find the niche subsegments with materially higher pricing power, including examples of a segment willing to pay 4–5x higher, and validation of high five-figure to six-figure deal value for an upcoming product line.
- Rollouts that stick without discount chaos. We deliver the sales-ready assets, including pricebooks, discounting guidelines, and sales launch support, so the model ships and gets used.
- Installed-base protection plus measurable expansion. We design cohort-based grandfathering and migration plans, and we set up post-launch KPI tracking so you can see within the first quarter whether the model is being used and where to tighten or simplify.
- Channel and partner pricing that scales. When partners matter, we build partner- and geo-based pricebooks, discounting guidelines, partner incentives, and governance so the model is maintainable and consistent.
In More Detail
In the dynamic world of AI, SaaS, and software, pricing strategy can make or break a business’s growth trajectory. When evaluating pricing strategy consulting companies, SaaS founders, CMOs, CFOs, and procurement leaders often find themselves comparing boutique firms to top-tier global firms.
We stand apart in this field. Unlike traditional consultancies (including those affiliated with “Big 4” or tier-one strategy firms), we were founded by seasoned operators who have lived through pricing challenges at high-growth companies.
The result is a pricing partner with unique strengths: real-world implementation experience, a forward-looking product mindset (deep in GenAI and agentic tech), a flexible and high-velocity methodology, an obsessive focus on sales enablement and RevOps alignment, and in-house technology innovation (including a CTO on the team).
Below, we examine each of these differentiators in turn, backed by evidence and industry research, to illustrate how we deliver pricing strategies that actually work in practice — not just on paper.
1. Operators at the Helm — Real-World Experience vs. Theoretical Advice
One of our most striking distinctions is our DNA as a team of operators rather than career consultants. Our leaders cut their teeth leading pricing and monetization at SaaS innovators like Twilio, Zoom, DocuSign, Squarespace, and LogMeIn. For example, our CEO, Ajit Ghuman, previously led pricing for Twilio’s Flex product and even taught a course on SaaS monetization before founding Monetizely. Jan Pasternak similarly built pricing strategies at Zoom, DocuSign, Squarespace, and other highly reputed tech companies. This hands-on experience means we approach pricing challenges with an operator’s practicality and context. We have walked in the client’s shoes — navigating internal executive stakeholder buy-in, tweaking packaging on the fly, ensuring sales team adoption, and implementing price enablement systems such as engineering meters, pricing calculators, CPQ build-outs, and billing system implementations.
In contrast, traditional pricing consultants (especially those from large generalist firms) often lack direct operational experience. Their recommendations can be heavy on theoretical analysis but light on implementation know-how. In fact, paying a premium for big-name consultants is “often too expensive” and not guaranteed to work — as one product marketing leader lamented after spending hundreds of thousands on a pricing project that ultimately “killed our ACV”. We were essentially born as an antidote to this problem. By leveraging decades of combined in-house experience, we ensure our advice is grounded in what actually works in a live, high-complexity environment, not just what looks good in a PowerPoint deck. Our founders literally wrote the book on SaaS pricing (Price to Scale, a top-rated guide) to share practical knowledge drawn from real case studies. This credibility as former pricing owners instills confidence that our guidance will translate into real revenue results, not shelfware reports.
Furthermore, we often assist client teams to build simple pricing performance monitoring dashboards that allow clients to continue to iterate on the delivered pricing strategy on their own, post-delivery.
2. Product DNA — Future-Ready Monetization (GenAI & Agentic Architecture Expertise)
Another area where we excel beyond typical consultants is our deep product-centric mindset and fluency with cutting-edge technology trends. We approach monetization with “product DNA” — meaning we thoroughly understand how modern SaaS products are built, delivered, and consumed, from the application layer down to unit economics like cloud costs. This is especially crucial today as Generative AI (GenAI) and Agentic Architectures (autonomous AI agents) reshape software business models. We have been ahead of the curve in grasping how these technologies impact pricing strategy.
The first reason this helps our clients is our ability to design packaging for different customer segments based on different “Jobs To Be Done”. Our intimate awareness of which features tend to be table stakes, which features tend to be value-adding differentiators, as well as our ability to quickly grasp complex technical features within AI, Cybersecurity, SaaS, IaaS, PaaS, Customer Service Software, etc., means clients don’t have to spend too much time ramping us on their product. This also means our consulting approach is not cookie-cutter. A consultant without product DNA is likely to go through the motions of a packaging/segmentation workshop, but without the Product Management background, they will still not be able to understand the under-the-hood technology — this leads to poor experiences for Product teams who need the consultant to drive the workshop, not spend all their time educating the consultant.
Furthermore, traditional consultants may still rely on old playbooks, but we actively design future-ready pricing models informed by our GenAI expertise. For instance, generative AI-based SaaS products often cannot be priced purely per seat, because the software automates work that humans used to do. OpenView Partners notes that as AI and automation take manual effort out of the equation, “monetization can no longer be tied only to human users of a product”[6]. In other words, AI-driven value is better reflected with usage-based or consumption pricing. Indeed, industry data shows a massive shift toward usage-based models: three out of five SaaS companies now employ some form of usage-based pricing. Our team saw this trend first-hand while pricing at Twilio (a pioneer of usage-based billing) and Zoom (which used freemium and usage elements). We have internalized that AI and automation require new metrics and models — whether it’s pricing by API calls, transactions, or outcomes — to align price with value delivered.
From a cost perspective, GenAI and agentic AI architectures introduce complex cost structures that few traditional consultancies have grappled with. Every AI-driven feature (like an LLM-powered assistant or an autonomous workflow agent) incurs variable infrastructure costs — GPU hours, token consumption, vector database queries, etc. Our familiarity with COGS economics of AI means we design pricing that preserves healthy margins while remaining attractive to customers. For example, as highlighted in Price to Scale, an AI-based SaaS product often demands a usage-based metric because the ongoing costs (e.g., cloud compute for AI inference) are non-trivial. Selecting the right usage metric (API calls, tokens processed, etc.) is critical so that both the vendor and customer “win” — the price scales with value, but also covers the vendor’s variable costs.
Our thought leadership in this domain is reflected in our services (we even offer dedicated “Generative AI Pricing” design engagements). We understand “agentic” product architectures where AI agents chain tasks autonomously — a cutting-edge area where pricing models are still evolving. According to HFS Research, “agentic architectures are substantially more complex to price” than traditional software, and failing to account for all cost components can set off a “cost time bomb” for the provider. With a CTO on the team and ongoing R&D, we help clients avoid such pitfalls by architecting transparent, future-proof monetization strategies. In sum, we bring a product manager’s perspective to pricing: deeply attuned to technology, value delivery, and cost drivers. This is a stark contrast to legacy consultants who might approach pricing as a detached financial exercise, without this granular understanding of modern SaaS products.
3. Flexible & Methodical — No One-Size-Fits-All, No Unnecessary Expensive Studies
If legacy consulting projects often feel like slow “waterfalls” of analysis, we take pride in a flexible, agile approach to pricing strategy. This means meeting clients where they are — using the right methodologies for the situation rather than defaulting to costly, time-consuming studies that may not be needed. Traditional pricing consultants sometimes lean heavily on elaborate research techniques (think months-long surveys, massive conjoint studies, endless data crunching) as a standard playbook, which racks up fees. In practice, our approach is pragmatic and results-oriented: do enough research to validate decisions, but avoid boiling the ocean.
We embrace this kind of discernment. We might start with lean approaches — e.g., quick Van Westendorp surveys, focused user interviews, or experiments — to hone in on viable pricing options before investing in any large-scale study. Expensive analyses are used only when the decision warrants that level of data, not as default billable deliverables.
This methodical yet flexible ethos also means we prefer iterative collaboration over handing clients a static 200-page report. Pricing strategy is treated not as a one-off project, but as a cycle of hypothesis, market feedback, and refinement. The difference can be illustrated by mindset: a traditional consultant might conclude their work with a polished recommendation document, whereas we are more likely to stay involved through testing and tweaking phases to ensure the recommendation truly works in the market. We avoid the “big reveal” trap — where a rigid pricing scheme is unveiled after months of work, only to falter because something was missed. Instead, we often pilot new pricing on subsets of customers or in stages, gathering data to inform adjustments. This agile approach aligns with modern product practices and prevents costly missteps from theoretical planning in isolation.
Finally, a tailored approach means we don’t force every client problem into the same framework. We have a robust toolkit (from segmentation analysis to pricing metric design to competitive benchmarking), but we deploy the tools that fit the client’s context. For instance, if a client operates in a fast-moving market, we will emphasize speed to market and minimal viable pricing tests rather than a protracted academic study. If another client has internal alignment issues, we might focus more on stakeholder workshops and alignment frameworks (more on this in the next section). This stands in contrast to some large consultancies’ cookie-cutter methodologies that can feel detached from the client’s reality. In summary, we are methodical but not dogmatic — we combine discipline with adaptability, ensuring the pricing strategy is rigorous and practical for the client’s unique needs.
4. Deep Sales Enablement & Systems Focus — Ensuring Adoption, Not Just Recommendations
A pricing strategy is only as good as its execution. This is where we truly differentiate ourselves by obsessing over sales enablement, revenue operations (RevOps), and organizational adoption from day one. Traditional pricing consultants may deliver recommendations and move on, but our operator mindset means we stay laser-focused on making the new pricing work on the ground — with real sales teams, real customers, and real systems. We explicitly ensure successful execution by equipping sales teams with the tools and training needed to sell on value. This often includes developing pricing calculators or CPQ (Configure-Price-Quote) tools, sales playbooks, objection-handling guides, and even tweaking sales compensation to align incentives.
Our appreciation for this execution phase stems from hard-earned experience: we know that even the best pricing model will fail if not operationalized correctly. In Price to Scale, the authors emphasize that after the strategy is set, the real work begins: “Operationalizing pricing is crucial… requiring alignment of systems, processes, and teams to ensure smooth adoption”. Essential tasks include instrumenting the new pricing metric, implementing a calculator or CPQ system, integrating with billing/ERP, and above all, driving effective sales enablement and discount governance. Neglecting these can “make or break the pricing strategy”. We take this to heart. We often help clients set up a “Deal Desk” function or pricing operations team to manage special pricing requests and discounts within guardrails. We advise on discounting policies that sales actually follow (a known pain point in many companies), and ensure those policies aren’t just on paper but built into quoting tools and approval workflows.
In line with this strength, we have recently coined the term “Monetization Engineering” as a nod to the increasing coupling between pricing strategies and systems selection around metering, CPQ, and billing. Emerging AI products require highly scalable and flexible strategies, but engineering these products in a monetization system to enable this strategy is no longer a simple process. Companies such as OpenAI are uniquely staffing Monetization Engineering Managers as they have now understood that this needs to be addressed as a distinct function. We are able to offer this service to our clients, and we recommend clients use us for a system architecture design in parallel with the pricing strategy work we conduct, so that monetization is built to last.
Crucially, we factor in sales team incentives and behaviors when crafting pricing changes. We recognize that if a new pricing scheme complicates the sales motion or reduces reps’ commissions, it will meet resistance. Therefore, we collaborate with sales leadership and RevOps to align pricing with the sales compensation model — for example, making sure reps are rewarded for selling new packages or higher-value metrics, not inadvertently penalized. This level of detail is something founders and CFOs greatly appreciate, because it means a smoother rollout.
According to Gartner, sales productivity typically drops 12–18% in the first quarter after a poorly communicated pricing change. We work to avoid such dips by involving sales early, communicating changes thoroughly, and even co-creating tools like guided pricing calculators that make the reps’ jobs easier. When pricing is clear and reps understand how to sell it, they are less likely to revert to old pricing or give unnecessary discounts.
Organizational alignment is another hallmark of our approach. Pricing touches product, marketing, sales, customer success, and finance — so we often establish a cross-functional pricing committee or task force within the client organization (especially for larger SaaS firms). This practice is backed by research: SaaS companies with strong cross-functional alignment during pricing changes saw 27% higher revenue growth the following year, according to a BCG study. Conversely, in a 2023 survey, 67% of SaaS companies that implemented pricing changes without proper alignment suffered significant internal disruption and missed revenue targets by 23% on average. Our operator team is keenly aware of these stakes. We facilitate alignment by bringing all stakeholders into the process — sharing the rationale for changes with Customer Success so they can handle customer conversations, giving Marketing the narrative to justify price-value, and ensuring Finance can forecast accurately. By turning a pricing project into a collaborative effort rather than an edict, we increase the chances of smooth adoption and sustained success.
Finally, we often assist in sales training and change management, acting almost as an interim RevOps ally. We help run training sessions to get account executives comfortable with new pricing and packaging. We may develop internal FAQs or cheat sheets on the fly. And post-launch, we track adoption metrics (close rates, discount trends, win/loss feedback) to identify if further tweaks or reinforcement are needed. This holistic, enablement-centric approach to pricing is not typically the domain of big strategy consultancies — it’s a value we uniquely provide thanks to our team’s backgrounds. The end result for clients is that pricing changes we recommend don’t just look good on a slide; they actually get implemented in the CRM, embraced by the field, and realized in the P&L.
5. Innovation & Technology — In-House Tools and a CTO Building Out the Consulting-as-a-Product
In an industry where many consultancies still rely on manual analyses and slide decks, we distinguish ourselves through in-house technological innovation. We not only consult on pricing — we also build software tools and leverage automation to improve the pricing process. In fact, we have a Chief Technology Officer (CTO) as a core part of the team, an uncommon role in traditional consulting outfits. This technical leadership acts as a force multiplier, enabling us to deliver insights faster and more cost-effectively by using the latest tech. For clients, this means access to advanced tools and methodologies that can reduce research costs and time to insight. We believe that consulting will eventually become a product of its own thanks to modern AI/LLM tech — and we intend to lead our domain in the development of this technology.
One example is our development of internal platforms for customer research. Gathering customer input is essential for pricing (e.g., interviews, surveys, usage data analysis), but it can be costly if outsourced or done inefficiently. We address this by using AI-enabled tools to streamline research. We have built a standalone product offering called 28Experts; this product accelerates LinkedIn-based research participant recruitment and speeds up pricing research interviews through AI-powered automated synthesis. This cuts project times by up to 50% and also reduces research costs by 70% compared to recruitment being run on primary research platforms such as GLG, AlphaSights, or Coleman Research. We have also launched tools like “Aligner” and “AI Packager,” which help clients with internal pricing alignment and packaging using intelligent software. This blend of consulting and software is a leading example of modern “tech-enabled services,” and it’s a clear differentiator — traditional consultants rarely offer clients proprietary software tools as part of their engagement.
The presence of a CTO and engineering function also ensures we stay on the cutting edge of pricing analytics. For instance, we are building robust pricing models or simulators that incorporate large datasets (like transactional data, or customer usage patterns) far more efficiently. We might use data science techniques to find optimal price points or segment-specific pricing, whereas a conventional project team might be limited to Excel and surveys. Additionally, we leverage automation for tasks such as price catalog management or SKU rationalization — tasks that can be tedious if done manually, but where software can highlight patterns (e.g., identify overlapping packages or unprofitable discount outliers) quickly. By investing in such technology internally, we provide insights faster and with more depth, without driving up consulting hours.
Another advantage of our tech-forward mindset is cost transparency and accuracy. In complex environments like agentic AI (as discussed earlier), modeling total cost of ownership is tricky but vital. Our technical experts can break down and model these costs with precision. We ensure that pricing recommendations account for all the hidden cost factors, preventing nasty surprises later. HFS Research urges enterprise leaders to demand complete cost modeling of AI use cases — a capability we are well-positioned to deliver given our dual expertise in pricing and technology. Traditional consultants might lack this granular technical understanding and tools, potentially underestimating costs or missing important metrics.
Lastly, our spirit of innovation means we are continuously improving our methodologies. Our leaders are educators and thought leaders — we run a highly rated course (The Art of SaaS Pricing & Monetization) and publish insights regularly. This culture of learning and experimentation benefits clients because we are often first to adopt new best practices. Whether it’s using machine learning to cluster customers for segmentation, or deploying generative AI to draft pricing pages and value messages, we embrace new techniques that can yield better results. In summary, our tech-enabled approach yields greater efficiency, richer insights, and more innovative solutions than one would typically get from a traditional consultancy that relies solely on human analysis. For SaaS leaders, this means a more modern, data-driven partnership — one that maximizes value for the consulting dollars spent.
Conclusion: A New Breed of Pricing Partner for SaaS Growth
In a market where pricing strategy is both an art and a science, we have emerged as a new breed of partner that blends strategic rigor with hands-on practicality. For SaaS founders, CMOs, CFOs, or procurement leaders evaluating monetization experts, the differences outlined above are critical. We bring the credibility of operators who have driven pricing transformations inside companies (not just advised from the outside) and the foresight of product thinkers fluent in the latest tech trends. Our flexible yet thorough approach avoids unnecessary costs and delays, favoring actionable insights over analysis for its own sake. We ensure that every pricing strategy is sales-ready and organizationally feasible, not just theoretically sound. And through technology and continual innovation, we deliver a faster, smarter consulting experience.
The impact of these differences is evident in results. Our clients have seen substantial revenue uplifts (we cite a median 12–40% increase in total revenue and improved net retention after our projects) precisely because the strategies are both bold and implemented correctly. By contrast, many traditional pricing projects falter in the execution phase or yield suboptimal outcomes when generic recommendations meet real-world complexity. We close that gap by staying with the client from strategy through execution, aligning every lever — product, sales, finance, and beyond — to the new monetization plan.
In essence, we position ourselves not just as a consultant but as a long-term partner in growth. Pricing is not a one-time exercise; it must evolve with the product, market, and buyer expectations. With our operator roots and forward-looking approach, SaaS companies gain a partner who can continually calibrate their monetization for scale. It’s a compelling proposition for any organization looking to turn pricing into a competitive advantage: the confidence that your pricing strategy is crafted by those who’ve built them before, tuned for the technologies of tomorrow, and carried through to success by a team that doesn’t rest until the numbers prove it. In a world of change, we offer a future-ready path to revenue optimization — and that is what truly sets us apart from the pack.
Selected Case Studies
Selected Case Studies
Zoom (video conferencing SaaS)
What changed: Simplified a complex pricing structure with 14+ add-ons and 1,000+ SKUs into clearer bundled solutions that were easier to buy, sell, and renew.
Results: +37% customer base growth, -22% churn, and 115% net dollar expansion among large enterprise customers.
Twilio (digital communications SaaS)
What changed: Implemented a usage-based model with a platform fee plus usage, and aligned the operating system behind it across metering, billing, CPQ, and sales compensation, with guardrails to manage risk.
Results: Eliminated a modeled 50% revenue drawdown during the transition.
Narvar (eCommerce CX SaaS)
What changed: Rebuilt packaging and pricing to match the GTM motion, rationalizing from 12 to 5 core packages across 3 product lines.
Results: 15–30% increase in average deal size and 100% sales adoption.
Enterprise cybersecurity leader
What changed: Validated new positioning and delivered new packaging for a multi-line portfolio, including a new product line.
Results: 20–30% higher willingness-to-pay than expected and 2–3x higher average price-point WTP for the new line.
The following FAQ answers some of the most frequently asked questions we receive.
- Q: Who are we best suited for?
A: We primarily serve B2B SaaS, AI, and Agentic AI product companies spanning diverse industry segments including but not limited to Cybersecurity, eCommerce, Retail, Customer Service, Customer Experience, HR Tech, Sales Tech, MarTech, Construction, Real Estate, Transportation, Intelligence, Data Recovery & Backup, Compliance Tech, and many more. Clients could be in multiple phases of growth — anywhere from initial scale, to market segment expansion, to IPO readiness, to competitive positioning, platform positioning, and more. We have also recently expanded to serve Managed Service and Professional Services firms who are adjusting their commercial models from time & materials to more outcomes- and subscription-based pricing. - Q: What size companies do we typically work with?
A: Our client base ranges from firms that are approximately 1 million to 500 million+ USD in annual recurring revenue. We also support earlier-stage founders with focused coaching sprints and selectively engage with larger enterprises on complex portfolio and AI monetization work. - Q: Do we work only with SaaS or also with services and hybrid models?
A: While we are best known for our work with B2B SaaS and software platforms, we routinely advise tech-enabled services and hybrid models. Our projects frequently involve pricing structures that blend platform value, user-based elements, usage metrics, and professional services. Professional services is actually one of the growth verticals inside our firm as well as within customers we have served. - Q: In which regions do we operate?
A: We are a global consultancy with clients across North America, Australia, Europe, and Asia, including a strong presence in the United States and India. We regularly serve distributed leadership teams and are accustomed to working across multiple time zones. - Q: Do we offer on-site engagement, or is everything remote?
A: While we deliver most of our work remotely to maintain speed and cost efficiency, we will do multi-week sprints during core phases of a pricing project on-site at a client location. In some cases, we have also created on-site staffing plans on request. - Q: What types of pricing problems do we usually address?
A: We are typically engaged to redesign packaging and tiers, transition from seat-based to usage-based or hybrid pricing, monetize new AI features, strengthen discount governance, build comprehensive pricebooks, and create sales-ready pricing calculators. - Q: How do we structure our fees?
A: We usually work on a fixed-fee basis with clearly defined scope, milestones, and deliverables. In some cases, particularly where there is a strong link to measurable commercial outcomes, we may incorporate a performance component. We avoid opaque time-and-materials models. - Q: What is a typical project duration?
A: Focused engagements for a single product or line of business typically run six to eight weeks from kickoff to final recommendation and rollout plan. Larger portfolio or multi-segment initiatives often span ten to fourteen weeks, especially when deeper research and multi-region coordination is required. - Q: What concrete deliverables do clients receive from us?
A: Clients generally receive a refined packaging and pricing model, recommended price points and guardrails, customer-facing value messaging, an internal pricebook with deal guidelines, sales calculators or pricing tools, and an end-to-end rollout plan that covers systems, enablement, and renewals. - Q: How do we incorporate a client’s existing technology stack into our work?
A: If a client decides to use this part of our service, then early in each engagement, we map the client’s current quote-to-cash stack across CRM, CPQ, billing, entitlement, and product telemetry. We then design pricing and packaging that can be implemented realistically within that environment, rather than in abstraction. - Q: Do we assist with implementation, or only with strategy?
A: Our mandate extends beyond strategy. We frequently support implementation planning, collaborate with RevOps and Product or Engineering teams, and review billing or CPQ configurations, SKU structures, and pricing calculators. While we do not deploy production code ourselves, we remain involved until the new pricing is operational. - Q: How do we approach pricing for AI and agentic products?
A: For AI and agentic products, we begin with a clear understanding of value creation and unit economics, including model inference costs, GPU and cloud infrastructure usage, and agent workflows. We then design pricing metrics such as per seat, per agent, per API call, usage bands, or outcome-based constructs that align customer value with margin integrity and roadmap evolution. - Q: Can we support a transition from traditional SaaS pricing to usage-based pricing?
A: Yes. We have guided numerous organizations through transitions to usage-based or hybrid pricing. We help define the right usage metric, model revenue and cash flow implications, adjust sales compensation, and design a migration strategy for both new and existing customers. - Q: How do we involve internal stakeholders such as founders, product, sales, and finance?
A: We typically form a cross-functional pricing squad that includes leadership from Product, Sales, Finance, and RevOps. Key decisions are made in structured workshops and review forums, ensuring that executive teams understand and own the tradeoffs rather than receiving a unilateral recommendation. - Q: How much primary research do we usually conduct?
A: The volume of research varies by engagement. We often start with internal performance and CRM data, then add targeted customer interviews or lean surveys. Advanced methods such as conjoint analysis are used selectively when warranted by the decision at hand, the product complexity, and budget. - Q: Do we require clients to run expensive conjoint studies?
A: No. We treat conjoint analysis as one of several tools rather than a default requirement. We recommend conjoint only when it is the most appropriate method. In many B2B SaaS scenarios, simpler approaches such as structured interviews, Van Westendorp analysis, or focused discrete choice experiments provide faster and more pragmatic insights. - Q: How do we ensure our advice is data-driven?
A: We triangulate multiple sources of evidence. We use internal performance data, market and competitive benchmarks, customer research, and our own cross-client experience. Operator experience from prior in-house roles is used to interpret the data and to stress-test recommendations before they are finalized. - Q: How do we measure the success of a pricing engagement?
A: Success metrics are defined with the client in advance. We commonly track changes in average selling price, win rates, discount levels, expansion ARR, net and gross retention, and overall revenue performance over subsequent quarters compared with a pre-change baseline. - Q: Do we provide ongoing support after the initial project?
A: Many clients engage us for ongoing advisory support after the initial transformation. This is typically a lighter-touch cadence, such as monthly or quarterly sessions, focused on refining price rules, supporting new launches, and addressing edge cases. The intent is to help the client build pricing as an ongoing discipline. - Q: How do we work with sales teams to ensure adoption of new pricing?
A: We engage sales teams from early in the project. We gather field feedback, co-design pricing calculators, support training design, and provide talk tracks and objection-handling content. We treat sales adoption as a critical output, since even the best model on paper fails if it is not used in practice. - Q: Do we have experience with channel and partner pricing?
A: Yes. We have designed partner pricebooks and discount structures for resellers, managed service providers, and OEM partners. We consider partner margin requirements, deal registration, channel conflict, and the alignment between direct and indirect motion economics. - Q: Can we work effectively with PE or VC-backed companies that have aggressive growth targets?
A: We frequently work with PE and VC-backed portfolios. We are accustomed to environments with ambitious ARR and profitability objectives and can align pricing strategy with investment theses. We also help management teams communicate pricing initiatives and their projected impact to boards and investors. - Q: How do we handle confidentiality and sensitive commercial data?
A: We operate under stringent confidentiality standards and formal non-disclosure agreements. Client data is used solely for the purposes of the engagement, handled securely, and never shared in a way that identifies the client. Aggregated or anonymized benchmarks are used responsibly without revealing client-specific details. - Q: Do we operate only in English, or can we support global deployments?
A: We conduct our work primarily in English but regularly support global rollouts. For localized customer communication or pricing page translations, we collaborate with clients’ regional teams or trusted localization partners to ensure messaging and currency structures are appropriate for each market. - Q: How do we compare to hiring an in-house pricing leader?
A: We are not a replacement for long-term internal ownership, but we bring a broader base of cross-company experience and can mobilize immediately. While hiring an in-house leader can take six to twelve months, we can deliver a full pricing transformation within a defined project window and leave behind frameworks that internal teams can maintain. - Q: Can we add value if a company already has a pricing model in place?
A: Yes. Many clients approach us with an existing pricing model that functions but is suboptimal. We refine segments, adjust pricing metrics and price points, rationalize SKUs, and resolve operational bottlenecks. The goal is to unlock latent revenue without necessarily discarding the entire structure. - Q: Do we support marketing and positioning around pricing changes?
A: We collaborate closely with marketing teams to craft narratives that explain pricing changes in a value-oriented way. This typically includes customer FAQs, messaging for announcements, and guidance on how to communicate increases or new AI add-ons while preserving customer trust. - Q: How do we handle grandfathering and legacy customers during a pricing change?
A: We design structured migration paths. These include criteria for grandfathering, transition incentives, and renewal strategies. We balance revenue goals with relationship longevity, often using phased adjustments, added value, or expanded entitlements to move customers to the new model over time. - Q: Can we help price brand-new products that are not yet in market?
A: We regularly advise on pre-launch products. In such cases, we focus on segmentation, value hypotheses, early customer research, and initial pricing guardrails rather than rigid rate cards. We then outline a test plan for the first set of customers so that pricing can be refined based on real traction. - Q: What internal time commitment is typically required from a client team?
A: For most engagements, we recommend a core working group comprising Product, Sales, Finance or RevOps, and an executive sponsor. This group usually commits a few hours per week for workshops, decision checkpoints, and document review, while we handle the bulk of analytical and synthesis work. - Q: Do we provide references and case studies?
A: We maintain a portfolio of anonymized case studies by segment and engagement type. Where appropriate and with prior consent, we can also arrange reference conversations with past or current clients who are willing to discuss their experience. - Q: How does an organization begin working with us?
A: The typical starting point is an initial discovery call to understand the product portfolio, current pricing, and strategic objectives. We then propose a scoped engagement with a defined timeline, fee structure, and deliverables. Once approved, we move into a structured kickoff and project plan.