Source of article reprint: The trend of AI
Source | Hard AI
Many venture capitalists have found that AI startups are adopting a new business model - usage-based pricing, rather than sticking to the traditional per-user charging method (or seat-based pricing).
For example, generative AI startup Cresta, which initially charged per user, has now moved to charging per conversation its AI tools help contact center employees have.
In March, customer service company Intercom released Fin, an AI chatbot, priced at 99 cents for each customer request it could resolve, as opposed to the company’s core customer service product, which charges a fee on a per-user basis.
Hume AI, a lab and AI startup that studies expressive communication and aims to use AI to analyze people's emotions based on intonation and facial expressions, has also begun charging per minute, per annotation, and per word.
Public information shows that usage-based pricing (UBP), also known as consumption-based pricing, is a model that allows customers to pay based on the actual usage of the product, and the indicators that measure usage correspond to how customers obtain value from the product.
Currently, UBP pricing is becoming increasingly popular in the "Software as a Service" (SaaS) field and is gradually replacing more traditional pricing models based on subscriptions and user seats.
Because UBP directly links the price customers pay to the value of the products they receive, this pricing approach has been described as "becoming synonymous with value-based pricing."
Karthik Ramakrishnan, partner at Institutional Venture Partners (IVP), said that usage-based pricing models can help AI startups more closely link product pricing to the value they actually provide, which can be measured by the time and effort they save for customers.
However, compared to traditional per-user seat charges, usage-based pricing (also known as pay-per-use) may not lock customers into packages that generate more predictable revenue streams. C3.ai, a public company and artificial intelligence application developer focused on enterprise AI, encountered the dilemma of fluctuating revenue and gross profit margins when it switched to UBP pricing.
Currently, there are three broad usage-based pricing models:
Pay as you go: customers only pay for what they actually use or consume, which is ideal for companies with fluctuating business needs.
Per-unit pricing, where customers pay based on resource usage measured in units, and cloud providers that offer more granular services prefer this model;
Tiered pricing: customers can choose a tier that suits their needs, and upgrade to the next tier and higher pricing when usage exceeds the limit. There is usually a free tier to start with.
Usage-based pricing is also called "metered services," which is similar to the metered service model of purchasing electricity or water from a utility company. This pricing model was first favored by SaaS and "Infrastructure as a Service" (IaaS) cloud providers to retain customers by allowing customers to explore how to use the service in a natural way without having to spend money on subscriptions upfront.
The advantage of UBP pricing is that it is easier to directly link the customer's usage costs with the supplier's resource consumption through the transparency of the pricing model. For users, they can start using the product at a relatively low cost, minimizing adoption resistance. For suppliers, allowing more users to access the product in the same account can spawn more new use cases and even encourage a group of users to share their experience with other potential users within the company or external organizations, thereby expanding the total addressable market (TAM).
On the downside, this pricing model relies on the changing needs of customers, which may make it more difficult for suppliers to predict financial data and obtain sustainable recurring revenue, and may even harm the long-term growth of the enterprise. However, data shows that in the past five years, the adoption rate of UBP pricing in the B2B SaaS field has almost doubled, and three out of five companies are using some form of UBP strategy.
Naomi Pilosof Ionita, a partner at venture capital firm Menlo Ventures, also said that in addition to the fact that the products are newer and need to use faster strategies to prove their value to potential customers, if artificial intelligence startups improve the efficiency of their customers' employees, it may cause their customers to ultimately hire fewer employees, which means that the number of user seats that bring revenue to AI companies under the traditional subscription model will decrease.
All of the above reasons make AI startups more willing to try new pricing models.
At the same time, amid the current macroeconomic challenges, as enterprise customers increasingly lay off employees and cut spending and take longer to make software purchasing decisions, usage-based pricing may be more acceptable to enterprises because it allows customers to flexibly adjust spending over time.
Other analysts pointed out that the rise and gradual popularization of UBP pricing is closely related to the development characteristics of the technology itself:
• Automation: Software increasingly automates manual processes. The more successful a product is, the fewer user seats customers need, and pricing based on user seats does not scale with the value of automation.
• Artificial Intelligence: AI takes automation a step further, ultimately eliminating the need for entire teams to continually perform tasks, making monetization no longer tied solely to the human users of a product.
• API: For many of the fastest growing software companies, the value lies in the API (the ability of software to talk directly to other software), not the UI (user interface), and users are not required to see the value.