The three worst B2B SaaS pricing errors – and how to avoid them

These software pricing errors zap revenue and profit 

The number 1, absolutely worst error you can make in B2B SaaS pricing is to copy or undercut your competitor’s pricing. I’ll explain why in this blog, but first let me say I understand the motivations behind price copying and undercutting.  

Some software companies do it to match or undercut a particular competitor at all costs. In most cases, though, I think a big part of the motivation is fear of making pricing errors. Pricing decisions are complicated and strongly impact revenue streams. So it’s tempting to think you can avoid screwing up by basing your pricing on a successful competitor who seems to have it all figured out. But copying or undercutting another company’s pricing is one of the riskiest things software companies can do.  

It’s a risk you don’t have to take. So first, eliminate the fear of pricing by familiarizing yourself with the most common grievous pricing errors. Then, avoid them as you craft an optimized pricing model (part of an integrated software monetization strategy) that works well for your software and company.  

The three worst B2B SaaS pricing errors: 

1. Copy or undercut a competitor’s pricing

You may be omitting their context while assuming their risk 

Copying a competitor’s pricing or adopting the same pricing approach to undercut their price point is extremely risky. It’s dangerous because you’re borrowing a pricing decision made—if done correctly—based on multiple interlaced, carefully considered factors. These include, most importantly, their customer mix and how users derive value from their software. Impose a competitor’s pricing onto your own product, and it’s devoid of that context. The results won’t be the same and may be dangerously unpredictable. 

Also, you’re assuming your competitor has priced the product correctly. What if they haven’t? Perhaps they’ve made one or more pricing errors examined in this blog. Perhaps they even came up with their pricing by copying another competitor—and that company’s pricing was chock full of errors.  

When you copy a competitor’s pricing, you also copy their risk. Unfortunately, such risk is not usually well understood by the borrower, who is, therefore, unprepared to assume the risk and take measures to mitigate it. As a result, there’s no way to control unexpected impacts on revenue. You don’t know enough about what’s going on in your revenue stream to manage it, much less to confidently move business performance forward through continuous improvement. 

2. Overcomplicate pricing with inconsistent modules 

The importance of price-integrating third-party components 

Incorporating third-party software components or services, such as cloud storage, into products can help companies add value, grow faster and take a more prominent position in the marketplace. But if the component or service is priced differently from your core-IP offerings, you can end up with overcomplicated pricing that slows sales and shrinks profit margins.  

Let’s say you’re pricing your core software on a location basis when you add a third-party component priced based on the number of users. Then, maybe you add another component whose pricing is based on some consumption metric. In an attempt to control your costs and profit margin, you decide to adopt the third-party suppliers’ pricing methods for these modules.  

What happens? Your customers and prospects hate it because now they’re forced to calculate their costs in different ways—not only for evaluating the present deal but when trying to forecast future costs (which becomes near-impossible). Your sales process becomes full of friction. 

Another problem is that unless you’ve added no margin on top of the component, you’re exposing your cost-plus pricing to buyers. That undercuts your sales team’s ability to sell on value—in fact, it’s the antithesis of value-based pricing and selling. It also leaves you vulnerable if the supplier, having a slow quarter or facing heightened competition, suddenly decides to cut its retail prices. Although your salespeople can point out the added value of having the component pre-integrated with your software, customers are likely to argue that they could get it cheaper by buying directly. 

3. Gum up the sales process with tiering and hyper-gearing 

Buyers can get stuck in the works 

There are two major types of tiering used in B2B software markets:  

Tiered product offerings are software editions, generally with each successive tier providing a wider range or level of capabilities. Their purpose is to encourage upsells when buyers need more capabilities.  

Tiered pricing generally consists of purchase volume thresholds (units might be measured in users, consumption, dollar expenditure, etc.), with each successive tier providing a higher discount and, therefore, a lower unit price. It’s an artifact from manufacturing physical goods in the industrial world that has been coarsely applied to software. Its purpose is to allow pricing to scale to encourage expansion sales when buyers need more units. 

The problem is that software companies often mush together these two concepts., trying to design tiers that simultaneously promote expansion and upselling.  In my view, this is a prime example of over-engineering monetization frameworks. Packaging and pricing that ought to add fluidity and momentum to the sales process become very complex, creating friction points that slow everything down and force many buyers to make choices that don’t fit.  

For instance, some companies create tiered product offerings with embedded tiered pricing. Let’s say you have a product where you charge based on the amount customers spend advertising on your platform. A “Good” product tier provides a basic set of software capabilities for advertising spend between $250K and $1M. A “Better” tier includes more capabilities and covers ad spend between $1M and $2.5M. With this approach, you’re predicting buyers will need the additional capabilities and the additional volume of ad spend. But for many buyers, that won’t be the case. They’ll need just the added capabilities or just the added volume.  

This kind of combined product-price tiering often forces customers to buy what they don’t need, or at least what they don’t need yet. Some will pay for extraneous volume to get higher-level capabilities. Others will pay for extraneous software capabilities because they must have additional volume. Neither situation creates a happy customer. Competitors offering a better fit have an opportunity to get through the door.  

Another problem is that buyers who don’t upgrade for their additional needs may not have the right configuration to get to value quickly, increasing the risk of a faltering pilot or, worse, a churned account. (Some of these buyers will implement the software at a minimal level but then start looking for an alternative. The shallow deployment reduces their switching costs, which they will use against the seller in future negotiations.) This is the classic trap of land-and-expand strategies. The salesperson lands the initial deal, but since it’s for a non-ideal configuration, the customer is only partially satisfied and the expand phase never happens. A better approach is the “land to expand” strategy (download our ebook on the topic). 

Some companies make the fit problem worse by “punishing” customers who choose lower tiers by charging them steep overage fees if their volume exceeds the tier limit. This is super-annoying and painful to buyers. It makes people angry. 

Even when not embedded into tiered product offerings, tiered pricing can complicate sales. Buyers whose needs are just over the edge or even in the middle of the next higher price tier may need more incentives to buy more and so fall back to purchasing the lower tier. (In the above example, if there’s no price break for $2.3M in ad spend, why not pilot at $1M instead?) Consequently, you take in less revenue than you could have by giving buyers exactly what they needed and charging accordingly. 

Similarly, discomfort with poorly fitting price tiers leads buyers to press salespeople for deeper discounts (“Hey, I’m really close to this next tier; can’t I just have that price for all the units I am purchasing?”). 

Price tiers can also lead sellers to misread their market. For example, imagine you’re selling user licenses for a security tool. You charge $10 per license for quantities 1 through 25. For quantities between 26 and 100, there’s a 25% discount, so the unit price drops to $7.50.  

Is a $2.50 reduction enough to get deeper penetration into customer organizations with users who only need the tool once in a while? If the incentive isn’t enough, you’ll find that one of your most frequently purchased quantities will be right at the price tier breakpoint (in the above example, 25 licenses). Many organizations purchasing that quantity will have a core group of users who really value the tool and a larger population of potential users who could get some value from it but don’t need it as much. Perhaps the buyer would purchase licenses for all these users if the unit price were as low as $5 but decides it’s not worth it at $7.50.  

It’s tough to predict what those cut-off points should be; the risk of getting them wrong is very high. In many cases, since salespeople can work effectively with no more than about a half-dozen tiers, tier widths successively widen.  Sizes are fabricated with numbers (1K, 2.5K, 5K, 10K, 50K, etc.) that form pretty Excel charts but aren’t helping the sales process. In some cases, tier widths can reach absurd levels. Imagine your price tiers are usage-based, and volume skyrockets. You soon have a catch-all tier of everything above 100M units—which doesn’t align with the value customers derive from this usage.   

If you don’t understand how tiering changes buying behavior—forcing buyers to take less or more of what their organization needs—you may take this skewed data seriously. Going back to the example above of selling a security tool, you might believe most buyers in your markets want 25 licenses and that this would cover the broad array of their use cases. 

In these and other ways, pricing tiers can lead to a loss of fidelity in the software company’s understanding of its customers. Nuances of customers’ behavior and value perception are blended out of important analytics and strategies. Marketing and sales have reduced visibility into changes emerging in customer mix. Finance has a hard time forecasting revenue (especially if tiers cover “up to X units”—a common tactic for revenue recognition these days under GAAP). Critical decisions about product roadmaps and customer support get made from bad data.

Adding to the organizational complexity and fog, tiered product offerings (especially if you take the concept to an extreme through hyper-gearing—see sidebar) and tiered pricing may get stitched into multiple areas of operations. Billing systems, sales ops, licensing entitlements, renewal processes, self-service and partner channels may all need to accommodate tiers. When pricing tiers are interlaced through operations in this way, changing them creates work in multiple departments and requires leaders to come together, agree and coordinate efforts. Tiering can become an impediment to innovation and efforts at continuous improvement. 

How to simplify pricing for sales teams and customers without hurting your company financially 

I’ve talked about how the worst B2B SaaS pricing errors involve overcomplication, counteracted by attempts at simplification that hurt the company by further reducing pricing effectiveness and business performance.  

To avoid these blunders, go for simplicity from the beginning. Treat pricing as an element in the design of your product rather than something you tack on at the end of development before going live. Gather detailed quoting data (for example, our LevelSetter software collects every quoting action, via API, taken by your sales team or partners and a wealth of information about buyer and salespeople behavior patterns). Then validate all of your assumptions during rollout and make the appropriate improvements to the model based on real-world usage and transaction data. 

Optimal pricing models emerge from this design mindset equipped with a deep understanding of how your customers will use your software to derive business value. Potential customers who are similar in this respect can be seen as classes of buyers. For monetization purposes, they are a far more accurate and powerful means of segmentation than the more typical buying personas. 

This deliberate design process involves finding ways to absorb within your pricing model the various ways you will be charged for third-party components and services. The goal is to create a single, rational, uniform, value-based pricing model (including a structured discounting framework) extending across all SKUs the sales team offers. In addition, pricing should be simple enough that it can be readily explained by salespeople and easily understood by buyers.  

With this approach, discounts are earned, not given. Salespeople can fluently explain how pricing works and what buyers can do to increase their discount. They can show buyers how adding more capability (module or product) or adding more volume will affect their net price. If that’s not of interest, they can remove that component of the deal, snapping the net price right back to where it was. The math works; there are no mysteries. Customers are treated fairly, with everyone having the same opportunities to improve their net price. Net prices are predictable, enabling the company to better forecast and manage the revenue stream. 

To find out more about optimizing pricing for value-based selling, keep reading this blog, or contact me: chrismele@softwarepricing.com.