🔖 Contents on this page:
- 💶 Pricing Models
- 💰Simple vs multi-dimensional pricing
- 💸 Strategies to find the right price
- 📚 Useful Resources
Several conflicting dimensions influence a pricing strategy:
- Unit economics: Of course as a startup, you want to make as much money as possible from selling your product. At the very least you want to achieve strongly positive unit economics, i.e. you want to make money on every sale that can fund general company functions such as marketing, sales, and R&D.
- Customers' willingness to pay: Needless to say, you won't be able to charge more than customers are willing to pay for your solution. Figuring out this point is difficult however. Different types of customers will have different price points they might be comfortable with, and this might change over time.
- Competitors' pricing: Even if you have a very differentiated product, your customers will compare your pricing to that of your competitors. If your price point seems way out of bounds, it will be hard to convince customers.
- Preferences for different pricing models: Customers might not agree with your preference for a particular pricing model. For example, most SaaS companies like to charge in advance for a multi-year subscription contract, but that might not fit your customers' budget realities.
💶 Pricing Models
There are many different approaches for setting a price for your product, and some strategies can overlap. Creative pricing (well beyond just being cheaper) can be a strong competitive advantage for your company, so it's more than worth thinking through this creatively.
Typical pricing models are:
- Straight-up standard product pricing This is of course the simplest approach: Set a price point for the product and charge it to every customer in the same way. This simple approach is often used for B2C products.
- Subscription pricing (recurring revenue) This model has become very popular in multiple industries. Originally probably pioneered by the media industry, it is not the most common approach in software and increasingly direct-to-consumer brands. Scaling dimensions often include the number of users that can use the product, plus the specific combination of features that users can access (typically broken down into different "plans").
- Usage-based pricing This method charges users based on how much they consume of the product. Examples would be compute and storage capacity in cloud services, number of contacts stored in a CRM, or the number of transactions conducted in a fintech product.
- Freemium Many products, particularly digital ones that have near-zero marginal cost, are offered in a freemium variant, i.e. there is a basic tier of the product that people can use for free. Once they want advanced features or increase their depth of usage, they are required to upgrade to a paid version, often in a subscription model.
- Free Many digital products can be used for free by end users because they are monetized indirectly through different means, most often advertising. Another monetization approach is selling or using the data generated through free users' activities, e.g. in retail stock trading apps.
- Solution pricing Most often used in complex enterprise products, customers are charge for a holistic solution comprised of one or several products and the necessary services to implement them in a particular customer situation.
- Value-based pricing In an ideal world, you could charge every customer the maximum they are willing to pay. Value-based pricing is an attempt to do that, running under the assumption that customers willingness to pay scales with the value they are getting out of the product. This strategy is often used with pricing tiers that charge a particular price level for each different edition of a product. Other approaches try to measure the customer value, e.g. by tracking savings generated by the product.
💰Simple vs multi-dimensional pricing
Generally speaking, a simple pricing approach that is easy for customers to understand sounds like it's the most compelling way. It certainly makes marketing and sales easier and potentially can shorten sales cycles.
However, there is also plenty of evidence in the industry that the fastest-growing, most profitable companies actually use more complex, multi-dimensional pricing models, often combining three or more pricing dimensions.
A main reason is that customers are different and are willing to pay for different things. Being able to adapt pricing to a specific customer situation can therefore be very effective.
Some possible considerations might be:
- Paying for services: Some customers expect an all-in-one price that includes basic support, while others might be happy to pay for premium support and training.
- Fixed vs. flexible pricing: Some customers are comfortable with usage-based flexible pricing, but others might prefer (e.g. for budgetary reasons) to pay a fixed price, even if it might be higher than the best possible flexible price.
- Pay in advance vs. monthly: Some customers are willing to pay in advance, particularly if they can get a discount. Some are also willing to buy e.g. more seats of a software product well in advance in return for better pricing.
💸 Strategies to find the right price
Getting to the right pricing strategy and level is going to be an experimental, iterative in most cases. Only mature industries typically have an established pricing level and commonly accepted practices. Startups operating in market sectors that are just emerging have to be more flexible.
Influence factors include:
- Maturity of the market: Very early, just emerging markets typically start at a low willingness to pay because customers have limited budgets for experimental products. Once the market matures, price sensitivity often declines because the sector produces must-have products. With further maturation, products often become commoditized and prices are reduced due to competitive pressure.
- Maturity of the vendor: Buying a young startup's product is a considerable risk for a customer, so most customers are reluctant to pay high prices. Once the vendor is more established, these concerns are reduced.
- Maturity of value creation: New types of products often have limited adoption at companies or limited usefulness for consumers. Therefore they are not willing to pay a high price. As adoption and utility increase, this will change.
Taking these elements into consideration, startups often go through the following steps to find the right price level:
- Start with a price level used by a comparable product or even competitor. For example, if you provide a productivity tool for developers, looking at an established player like Atlassian will help you understand your customers' expectations about what a product of that type will cost — at least a ballpark number.
- Decide on the right pricing approach (subscription, freemium, etc.) for your product. Again, comparables can help with that, but there is also room for creativity.
- Verify your assumptions in user interviews. It's rarely effective to ask people directly how much they would be willing to pay because it's of course not in their best interest to tell you. Rather, ask them about how they would measure the value of such a product and which pricing dimensions might work best for them.
- Set a price and start selling, and note customer feedback closely. A rule of thumb: If no prospect ever complains about your price, you are selling your product too cheaply.
- If possible, A/B test different pricing approaches. You could for instance serve different versions of your pricing page on your website and measure how conversion rates change. This of course needs to be done carefully since people hate to find out that they have been overpaying.
- As you roll out new product capabilities, try raising prices and carefully note customer reactions. If you package the improvements right, there shouldn't be too much push-back.
- A great trick is to grandfather in existing users into a new price point, i.e. existing users will keep paying the old (lower) price for a while. This avoids making your customers unhappy and will keep up their willingness to recommend you to others.
📚 Useful Resources
Thoughts? Feedback? Something missing? Please let us know: andreas.goeldi@b2venture.vc