Estd 4.22.2023
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Ok, so we’re now. We’ve finally done all the strategic decision making and analysis to arrive at the pricing structure.
Time to celebrate? Not in the least.
Later in the book, I’ve documented my interview with Natalie Louie who is currently the Sr Director of Product Marketing at Zuora. One of her quotes really resonates with my own experience of implementing a new pricing model inside a company, “I would almost argue, for me at least, pricing strategy is the easy part. Pricing operations, that is where you start pulling out your hair. And that's where all you're faced with is ‘no’. ‘No, we can't do that.’ ‘No, we can't do this’”
Pricing Operations involves all systems, processes and people involved in ensuring the new pricing model is fully adopted in your company and such that the sales engine works like a smoothly running machine.
Not even the best pricing model can yield any result if it's not operationalized to enable a smooth sales process and 100% adoption by the sales, professional services, ops and finance teams.
This is especially true of sales-driven cultures where ad-hoc deal by deal pricing has been part of a company’s history.
So let’s make sure we get this right. What do we need to do?
That’s a lot! It really is.
Compared to the creation of the pricing model, the implementation takes 3-5x the amount of effort (depending on which items you check off this list above). I say this to caution you before committing a full implementation in 4-6 weeks (been there, done that) and that any meaningful rollout will take at least a quarter (3 months), often more.
With that caution out of the way, let’s now discuss each of these items.
One document that will help truly align your packaging with all GTM stakeholders internally (product, sales, sales engineering, finance, you name it) is a simple shared (and up to date) product packaging grid that lists out the features included in each Tier, as well availability across geos, constraints and implementation notes.
The following table below shows a simplified version of such a grid that I’ve used, and one that has been very convenient to rid of any confusion during the regular sales motions. The effort taken to keep the document current (mostly once-a-quarter updates) is always well worth it in having clarity about basic questions, ‘what can we sell?’, ‘what’s in the elite plan?’, ‘does this work in Europe?’, ‘how complex is the integration?’ and so on.
Once in place you can bet that it will drive projects to improve your website product pages, provide answers for RFP questions, serve as a source of truth by the company and limit one off questions on a feature or package set (of which there will be plenty once a new pricing model is released).
The decision to publish pricing on your website is not to be taken lightly, and it should align with your overall GTM strategy.
There is today a general consensus within SaaS circles that publishing your pricing is a de-facto good thing -- on this point I disagree. This is a decision that requires thought.
Publishing pricing on the website makes more sense for high velocity sales engines with a more transactional sale and cut and dry packages, but less so when the deals are complex, low velocity with larger deal sizes. As soon as you publish your pricing on the website it forces you to have robust differentiation between tiers as all types of customers, channel partners and even competitors will start to use this as a reference.
Publishing pricing will also lead prospects to comparison-shop and question their software needs, existing customers may also start to want downgrades (this scenario is covered in the Citrix case study later in the book).
Every company’s GTM is different and the decision should align with the GTM strategy.
What you should know is there are many options here:
There are thousands of examples of pricing pages out there. Let’s consider a few pricing pages as mini case studies and try to analyze why a company in question may have selected to build their pricing page a certain way - a process that will guide your own thinking as you build your pricing page. Note that we may not find pricing pages for truly enterprise facing GTM companies, so note that this discussion of analyzing publicly available pricing pages inherently suffers from an inherent self-selection bias.
Company & Page
Ahrefs leaves nothing to conjecture. They lay out all their plans clearly and comparatively. All their features are plainly listed with the pricing.
Their highest plan is ~$12,000 a year, more of a SMB/Mid-market type offering whereas the lowest plans are more for users/consumers/small teams. For their GTM segments, this is exactly the right kind of page that will help them scale deal velocity.
What I also find interesting is that they charge $7 for their trial plans. The most likely reason for this is that they want to increase the trial conversion rate. Free trial conversion rates are historically really poor to convert (2-6%) and take a significant amount of resources to sustain. Adding a nominal charge to use the trial, likely weeds out non-serious users and lets the company likely achieve higher conversion rates.
Aftership serves mostly up and coming D2C ecommerce brands, and thus it makes sense they keep their pricing mostly transparent.
What I like about their pricing page is that they use the 3 Part Tariff structure that we discussed earlier with a very convenient slide scale to convert the 3 Part Tariff table into someone can easily understand visually. They display the overage fee in small text as well.
The overage price ends up being more than the per unit price of the tariff structure to incent customer to move up in plans, a feature of most well designed plans.
I find Intercom’s pricing page interesting and reflective of the company’s size, segments and use cases.
The first image, ‘For Most Businesses’, highlights primarily its product packaged into three different use cases. It is a great example of how a single product can be crafted to look as if it's built-to-purpose for a specific use case, a challenge shared by many companies that serve multiple use cases.
Given the variance in use case and potentially different value/price points, they do not show pricing in this pane -- to not inhibit revenue potential.
The second image, ‘For Very Small Businesses’, offers an insight into Intercom’s down market offerings positioned at attractive price points vs Zendesk.
Intercom does a great job at representing its capability clearly, simply and with high relevance.
I find Basecamp’s pricing to be truly unique and somewhat of a mold breaker.
No matter how much you use their product, Basecamp charges a flat fee of $99/month for a team, whereas competitors align price to usage.
The question is why?
My hypothesis for their decision is to stay an SMB/mid-market product and go to market with a purely product led growth model.
The comparable organizations cited scale from SMB to enterprise, whereas Basecamp seems to have decided where to focus from a segment perspective.
Another hypothesis with this pricing plan is that Basecamp truly wants deep customer retention and I would not be surprised to see their retention rates being far superior to their competitors.
Finally, if you’ve read about their philosophy, Basecamp has always eschewed the high-growth, high-burn Silicon Valley startup model, opting instead for a close to lifestyle business approach.
In general there are a few responsibilities that will need owners for a pricing model to be functional:
In the competitive landscape of Software as a Service (SaaS) businesses, the Pricing and Monetization team is pivotal in driving revenue growth and ensuring sustainable profitability. Often misunderstood and undervalued, this team is responsible for more than just setting prices. Their responsibilities span across strategy development, data analysis, project management, and operational execution, all of which are essential to the financial health and competitive positioning of a SaaS company.
Many teams within a SaaS company hold distinct biases about pricing, often viewing it from their specific functional perspectives. The Product Team, for instance, may overvalue features based on the effort invested in their development. The Sales Team might push for lower prices to close deals quickly, especially towards the end of a quarter. Meanwhile, the FP&A Team could emphasize the cost of goods sold (COGS) and advocate for pricing to meet margin goals. These varied viewpoints highlight the need for a dedicated Pricing and Monetization team to integrate these perspectives into a coherent strategy that aligns with the company’s objectives.
The term "Pricing Team" is often reductive, failing to convey the full scope of responsibilities. A more accurate designation is "Monetization Team," reflecting their broader mandate, which includes setting prices and determining the optimal ways to generate revenue from the company's offerings. This involves strategic decisions about market segmentation, competitive positioning, and product bundling, among other considerations.
Successful monetization strategies require seamless collaboration across various teams:
Ongoing governance is essential to maintain the integrity of the pricing strategy. This includes:
In many companies, the lack of a centralized owner for pricing can lead to missed opportunities and strategic misalignments. Without a dedicated Pricing and Monetization (P&P) owner, companies may struggle to optimize for value and coherence across different functional areas. Engaging a specialized firm or establishing an internal team focused on pricing can yield significant benefits by ensuring a unified approach.
Pricing is inherently cross-functional, impacting every team from Sales and Marketing to Customer Success, Accounting, and even Legal. One crucial, often overlooked role of Pricing is uncovering underlying strategic inconsistencies. For example, if the Product team focuses on building premium features while the Marketing team aims to generate a high number of leads, it indicates a clash: one team follows a strategy to maximize revenue per account, while the other operates on a high-volume, low-cost model. These inconsistencies can lead to significant inefficiencies.
Think of Pricing not only as a function responsible for delivering the new line-up design but also as a key player in uncovering opportunities for organizational alignment. By identifying and addressing these strategic discrepancies, the Pricing team can help ensure that all parts of the organization work towards a common goal.
The Pricing and Monetization team is a cornerstone of a SaaS company's success, tasked with the complex and critical responsibility of maximizing revenue through strategic pricing and effective monetization. By leveraging data analytics, strategic development, project management, and operational execution, this team ensures that pricing decisions align with corporate goals and market dynamics. Their cross-functional collaboration and governance efforts further enhance their ability to drive sustainable growth and competitive advantage in the ever-evolving SaaS landscape.
Establishing a centralized owner for pricing can greatly enhance a company's ability to align its various functions and optimize for value. The Pricing and Monetization team delivers strategic pricing and uncovers and resolves strategic inconsistencies, fostering a cohesive and efficient organizational strategy.
In most organizations, building out a simple pricing calculator in Excel or Google Docs can be a very powerful enablement tool, and not just for sales but also for folks in your product team, sales operations team, finance and more.
Now let me couch the word ‘simple’. It is only simple in relation to a CPQ build out but can be significantly involved. When I revamped the calculator based on new packaging and pricing at Narvar, it took me well over 2 weeks to make sure it covered all our pricing scenarios and was setup in a user friendly way, where sales reps could easily duplicate the main tab of the calculator and get cracking at pricing.
Often you will need to build out both CPQ and a Pricing Calculator, with the former being more of a gold standard quoting system, and the latter being an agile sales and product tool.
Figure 1 illustrates a (fairly) simplified representation of a google-doc based calculator.
The simple calculator depiction shows that in order to price out a certain package, a sales rep needs only to take three simple steps to get to the price. Check off the packages and add-ons in question, enter the estimated quantity of the main pricing variable and then note down the itemized price for their selection. In most cases this can be really useful to provide a price range to prospects in the initial stages of a deal, followed later by using CPQ to formalize the process.
In reality, the calculator won’t be so simple. You will likely have many more SKUs, add-ons and special conditions to abide by. Even so, I hope this provides a general idea of what the inputs and outputs should look like.
The internet will probably give you dozens of such examples, but what you should note are the following tips:
Configure-Price-Quote (CPQ) refers to a system that allows a sales rep to configure a package, generate a pricing quote (including internal approvals on discounts, etc.) as well as the contractual paperwork for their deal in a seamless automated process, enabling fast deal closure with transparency, as well as keeping a record in the CRM of what exactly was sold and for how much.
Another larger benefit is that it enables complete adherence to the pricing model. Because a software quoting implementation imposes guardrails on use cases and limitations to manually closed deals, it forces sales reps to strictly adhere to the pricing model deployed. Quoting Johnny Cheng:
“My fundamental belief is that in order to do value selling, you need a lot of flexibility, a ton of flexibility. What ends up happening in a model where if you introduce a lot of flexibility, is it comes with complexity. But complexity is a deal killer, it slows down deals, complexity makes it so that the reps can't defend the deal, they can't defend the price points, they can't understand why it's at this price point. And so in order to solve for that complexity and keep the flexibility, you have to introduce tools such as CPQ“.
In practice however it is hard to implement well, and is something nearly every pricing leader I interviewed considers a headache or a challenge.
In order to implement a CPQ solution, as the pricing leader, you will need to interface with your Sales Ops, Finance and Sales teams. In most cases such an implementation should be owned by the Ops team with heavy input from you on the pricing structure.
Be warned however that your job here starts to mimic that of a software product manager and that requirements will have to be defined fairly granularly. You will need to produce documents that cover all of the following:
Suffice to say this work somehow always tends to take 2-3x more time than you will estimate initially whether or not you have a consultant or an internal team building this out for you. This is so mostly because the scenarios that have to be built into this piece of software go beyond the pricing structure; they have to do with the day-to-day process (sometimes informal) of deal closure and in many cases highlights undefined policies for certain internal business processes.
Keep this timeline in mind before committing a rollout timeframe to your leadership team.
Beyond the pricing and process definition it is critical to involve some key friendly sales reps in the build phase. These reps can test to make sure the software is simple enough to use without unnecessary complexity, confusion or friction. Many implementation teams scramble to get an implementation finished without sales involvement and call it a day with a basic sales training. Inevitably this will lead to some unexpected usability or use case issues cropping up that may limit sales adoption of the product. The worst thing after months of implementation would be for your sales team to rebel, eschew the process and revert back to a totally manual way of selling, if this happens you will be left cleaning the mess on the other hand.
There are a ton of resources online that offer best practices on CPQ implementation. One that I liked is a book on the topic, CPQ Implementation Guide by Marcin Krzych.
As a final note of personal opinion, fast growing companies where pricing structure may undergo evolution every other quarter, may not want to overinvest in this CPQ capability. Primarily because CPQ implementations take a long time, and by the time you have put something into product use, new requirements come up - sinking a lot of time and resources in this never ending process. At some point you may still need to do this, I would personally live on a Google spreadsheet based calculator until ~15-20M revenue which would provide (hopefully) enough time to have a mature internal deal closure process.
One of the tools that always works to your advantage in B2B software pricing is discounting, as long as customers can’t just put their credit card information in and buy which is the only case where discounting is bound to be 0.
In most other cases where customers negotiate the price with sales, discounting not only needs to be baked into the price point you come with due to industry-default expectations of the sales process, but it also lets you survive without very robust statistical models to arrive at the price point(s) for your product as the price point can vary somewhat even amongst lookalike customers.
This is the closest tool that lets us reach a price optimized local maxima that can account for variations in price elasticity between customers.
As a very rough rule, you can expect discounting in different customer segments to obey the following ranges:
If you have three customer segments that can be defined by size and map to the descriptions above, then you can simply pick a rough number from the ones above and essentially pad the price point you would have come up with by that amount, e.g. your commercial plans will have a buffer padding increasing the price point by 10 to 30%.
Additionally, but limiting the discounting authority of your reps, managers and leadership in sales to steadily increasing approval limits, you actually create a sales tool for your reps that helps them build trust with their prospects as they end up fighting for a better deal for the customer. The best analogy is that you are purposely adding some friction to the sales process. Just remember a little friction goes a long way, a lot of friction leads to a disgruntled sales team and customers who balk at the initial number they see.
Once a discounting structure has been implemented, it’s essential to evaluate whether it is functioning as intended. There are two critical aspects to assess:
1. Customer Behavior Impact: The primary goal of any discounting strategy is to influence specific customer behaviors. It’s important to verify whether the discount is indeed driving the desired outcomes, such as a higher close-rate, faster movement through the sales pipeline, longer-term commitments, or an increase in multi-product purchases. The effectiveness of the discount should be measured by its ability to achieve these objectives. If the anticipated behavioral changes are not materializing, it may indicate that the discounting strategy needs to be re-evaluated or adjusted.
2. Correlation with Sales Performance: Another key factor to examine is whether the level of discounting is more closely correlated with the attributes of the customer or with the actions of the sales representative. In other words, is the discount being applied based on the characteristics and needs of the customer, or is it largely dependent on the individual sales rep’s approach? If discounting patterns are more reflective of who is selling rather than who is buying, this could suggest inconsistencies in how discounts are applied across the sales team. Such a scenario might indicate the need for retraining the team or it could highlight flaws in the discount design itself.
By regularly monitoring these two aspects, organizations can ensure that their discounting strategies are not only effective in achieving their intended goals but also that there is no ‘revenue leakage’ occurring as a result of unnecessary discounting that does not yield the results.
In order to make this usable, a very standard operational document is something called a Discounting Matrix. It lets your Sales team know the level of discounting authority different people in the team have to offer a discount to the customer. Even if you may have built say a 40 to 50% padding in list prices, you should give your AEs lesser discounting authority than that -- the idea is to include a little bit of friction in the process that lets an AE run a discount up their hierarchy and be able to offer something that the customer wants. Yes it is artificial, but it works. Higher discounts must appear to prospects as being earned or negotiated and not just given away by any sales representative - which will dilute the value of the discounts.
Figure 2 presents one example of such a discounting matrix table. It shows a progressively increasing discounting and deal term authority structure across sales hierarchy levels.
A routine performance analysis on your pricing model’s performance is absolutely critical for your pricing initiative to become successful. In most cases, everything from packages, pricing and sales operations will have to be tweaked quarter over quarter for your pricing model to really work.
Here is a quick list on the metrics that I recommend measuring in a given quarter:
Average Selling Price: The product ASP is generally a board-level top line revenue metric that offers directional information on product-line performance. The benefit of such high-level, non granular metrics is that even across different pricing models, the ASPs can be trended over time providing an apples to apples understanding of revenue movement that does not rely on knowledge of market movements or pricing model trends. Over time, it is one of the key directional indicators that investors are most interested in. Even when the underlying packaging structures change, the ASPs at the global product family level are very helpful directional indicators.
Median Selling Price: The Median Selling Price is very similar to the ASP. The only reason it would be advisable to calculate the median is because if, as is usual in startups, the number of deals closed is small, then a number of very small or very large deals can swing the ASP. This can provide one indication as to why there is a change/swing in the ASP.
Number of Deals Closed: For the most part, for growing startups, in most quarters the number of deals closed should be slightly greater or the same than previously. In some cases, such as in the case of the COVID-19, a change in the market situation might significantly reduce the number of deals closed. In that case an increase in ASP would not mean the same thing if the number of deals closed decreased sharply. To use ASP as an indicator of how the pricing model performed, it helps to look at this metric to ‘normalize’ the true impact.
Unit Price: Just like the ASP, unit price ($ per seat or $ per unit consumption, etc.) is one of the most important factors in assessing the price power of a product or package. A gradually increasing unit price indicates how compelling prospects find your product in the market. It does better at indicating pricing power than the ASP because the ASP can often vary with a change in the deal mix (many smaller deals or many large deals, for e.g.), and the unit price will tend to be more stable over time.
Average volume sold: The average number of seats or estd consumption volume sold is a metric that roughly correlates to the size of opportunities you tend to sell for a given product, segment or package. When analyzed at a package level, this will tend to be consistently different across packages as they generally tend to diverge based on the size and hence consumption needs of the prospect. Two packages that aim to target different customer segments with similar average volume may indicate that you just need one package, not two.
Discounting %: Discounting is a very helpful number to analyze in the context of a given pricing model. Combined with benchmarks (both internally and for the industry), it can help inform if the price point is too low or too high. It can break internal disagreements where Sales might push for lower price points where the real discounting may not be very high, it can also be helpful to see if Sales is inflating list prices (-ve discount rates), indicating the price may be too low.
Important Segmentation Criteria: Additionally, for the above metrics to provide actionable information, the closed deal dataset you prepare would benefit from the following segmentation of data for you to truly be able to dive deeper into performance:
Be prepared to munge through data in excel and manually calculate these variables if the data is not readily available in your CRM (which tends to happen a lot). But the effort in analysis and understanding business performance will be worth it.
True Attribution Of Pricing Model Changes
As you start this exercise you will quickly realize that perfect attribution of the change in a pricing model is hard to measure. Given the growing nature of any business, many other factors change quarter over quarter, and say a 20-30% net change in revenue could be attributed to many other variables such as new products, better market conditions, more sales people or better sales productivity.
The closest possible way to measure attribution would be to re-price deals sold under the new pricing model, with the older model, apply the same discounting percentages and then compare the outputs. Even then, applying the newer discounting thresholds makes it a less than perfect exercise, but it can still be helpful.
All this to say, that measuring performance in practice often becomes more about whether or not the older problems experiences are solved, such as reduced ASPs, shelfware or low package adoption. If performance under the new model consistently solves these problems quarter over quarter, then in most cases that should be proof enough.
Now that you’ve built out the packaging, tools, and team processes to operationalize your new model, the next thread is the Deal Desk operations. This function lives at the intersection of pricing strategy and sales execution, making sure every quote uses the latest price book and follows your guardrails. Let’s explore how a well-run Deal Desk keeps deals moving fast and margins intact.