3 minute read / Oct 15, 2015 /
5 Mistakes SaaS Startups Often Make with Pricing
The purpose of a price is to tax usage of a product. That’s how companies generate revenue. Discovering how to tax a product properly is a perpetual challenge. It’s a moving target and so it requires an ongoing discovery process as the company and market evolve together. These are some mistakes I’ve noticed.
Complex or unintuitive pricing model. A good pricing model appears simple and logical to the customer. It may be complex behind the scenes, with different prices for varying customer sizes, product complexity and add ons, but the tax align itself to the customer’s perception of ROI clearly. Customers have their own unit of measure. Often for applications, it’s people - hence a pricing model by seats. Other times for infrastructure, it’s bytes for storage or cycles for compute.
But mixing these models by charging for a people-based product in units like bytes. A pricing model for Slack that charged based on the number of bytes sent by the team in a month works conceptually, but is intangible, hard to understand, and also impossible to predict the ultimate cost for the buyer.
Move to annual prepay too late. Salesforce popularized the annual prepay idea, and for good reason. Annual prepay generates cash flow to accelerate growth. Customers effectively lend the startup money to grow. It can be intimidating to push a customer toward annual prepay, or to demand it from an account executive, especially when a startup is young and the product immature. But it’s worth pushing as early as possible. Your startup will grow faster and need less capital to grow.
Employ static pricing. The optimal price for a subscription product is the one that maximizes the revenue on the supply/demand curve. But unlike the charts my Economics professor drew on the blackboard, startup price demand curves aren’t static. They change with time.
In fact, the marketing team exists to improve the demand curve by building a brand, developing reference customers, building strong return on investment case studies, building the lead funnel. As a startup becomes better known, the demand for the product increases, lifting the price demand curve, and with it the optimal price point. These effects can be dramatic. For example, Box’s revenue has grown from a few hundred to a few million dollars per year.
Fail to embed concessions in the proposal. When selling to mid-market companies who buy software with purchase orders, not credit cards, startups will need to survive the procurement gauntlet. Procurement teams are often compensated on their success negotiating lower prices from vendors. Structuring proposals with this in mind is key to achieving the ultimate price target for your product.
Using the wrong price discovery questions. When asking a customer or potential customer, how much they are willing to pay for a product, the customer will almost never be forthright. And for good reason - it’s against their economic interest to reveal their maximum willingness to pay.
It’s much easier to ask a customer to think about relative price. How much is the customer willing to pay compared to another product? In the sales SaaS world, buyers think of the cost of new tools as a function of the cost of a Salesforce seat. 10-20% of a Salesforce seat for a productivity tool seems reasonable. But is this new lead generation product equally as valuable as Salesforce?
Pricing is a moving target and found should view it as an ongoing product discovery process. Pricing should be re-evaluated regularly. Monthly at the very beginning stages of commercialization and then less frequently as the company approaches a the local maximum when a product matures and the company establishes itself as a leader. Beware of the pitfalls above and you’ll reach that optimal pricing mechanism faster.