In the face of the B2B recession, are you simply staying afloat, or are you charting a course to thrive? 

As the VC/PE market’s waters continue to be choppy, the winners will be those who can adjust their sails to catch every shift in customer demand. While there are many tactics an executive team could evaluate to respond to current market conditions, one that is often underappreciated is pricing. Sticking to static pricing models won’t be enough in today’s market. The data from our recent Maxio Growth Report shows that you’ll need to adapt your monetization strategy quickly, aligning your pricing with customer-perceived value in real time to stay ahead. Those that do will not only survive but will thrive long after this storm passes.

Fixed-Rate for Stability, Usage-Based for Growth

Stability is critical in the early stages of your company’s growth. Our report showed that companies with revenues less than $1M benefited from adopting a fixed-rate pricing model.

We believe that fixed-rate pricing gives you the predictability needed to manage cash flow, streamline processes, and focus on building a strong market presence. At this stage, this model keeps things simple—exactly what a growing company needs. But once you hit product-market fit, it’s time to shift gears. For companies >$1M, usage-based pricing becomes the engine that drives growth. 

At this stage, you have enough financial stability to start experimenting with more volatile pricing models. By tying your pricing directly to the value your customers experience, you create a business model that accelerates as your customers’ businesses grow. This isn’t just about scaling revenue—it’s about capturing the full potential of what your product delivers as customer engagement increases.

Hybrid Pricing Models: The Best of Both Worlds

Hybrid pricing models are gaining significant traction as SaaS companies balance the need for predictable revenue with the flexibility to capture more value as customer usage increases. In fact, recent studies show that 46% of SaaS companies have either implemented or are experimenting with hybrid pricing models, allowing them to combine fixed-rate pricing for stability with usage-based components for growth​.

Companies can maintain steady cash flow while offering fixed-rate pricing for basic services, incorporating usage-based pricing for premium features or higher service tiers, and scaling revenue alongside customer demand. Research from the OpenView 2023 SaaS Benchmarks Report shows that companies adopting hybrid pricing models can achieve a 10-15% increase in annual recurring revenue (ARR), underscoring the financial benefits of this flexible pricing approach​.

Hybrid pricing offers financial stability and the agility to meet varying customer needs and maximize the value delivered across diverse usage patterns, making it a resilient model in today’s fluctuating economic landscape. This approach is especially beneficial for industries like AI, where significant R&D and infrastructure investments are common.

AI Companies Leading the Charge in Pricing Innovation

Regarding AI, the industry is buzzing with excitement—and for good reason. AI-powered companies are pushing the boundaries of pricing innovation, experimenting with advanced models like cost-based and domain-specific strategies. They are also capturing the lion’s share of investment these days. According to an article on CNBC quoting Forge Global (a company that tracks private market transactions). “AI as a percentage of total fundraising jumped from 12% in 2023 to 27% so far this year. The average round for AI companies is 140% bigger this year compared with last, the data shows, while for non-AI companies, the increase is only 10%.” No wonder every early-stage company is adding AI to their names again. But let’s be clear: navigating this new terrain isn’t easy. Aligning pricing with customer value in the AI space is challenging, and the industry is still very early in experimenting with various models.

I recently attended a seminar hosted by Ibbaka Performance that got me thinking about how companies can evolve their pricing models–especially those working with AI. They divided the AI landscape into user-based, AI cost-based, and domain-based pricing models. What struck me was how this breakdown reflects the broader complexity we’re seeing in AI pricing today. Based on a survey that Ibbaka analysts conducted, 27% of companies are sticking with the familiar user-based models, while 36% are shifting to AI cost-based, which is more like a utility model—think paying for water, something people inherently understand. However, the most interesting piece was the 37% of companies exploring domain-based pricing. This model is all about the value created within a specific domain, and the challenge lies in articulating and capturing that value effectively. As Stephen Forth at Ibbaka wrote in a recent article: 

One of the most interesting recent developments is how OpenAI is pricing the first two models of its reasoning model o1. They have added a new metric, Reasoning Tokens. It is pricing these at the same price as Output Tokens. Output tokens are priced at 4X input tokens, and how many reasoning tokens will be generated in a typical process needs to be clarified. Putting all this together, higher prices, higher differential between Input and Output tokens (from 3X to 4X), a new type of token that is basically hidden but gets priced as an output token … it seems that o1 is priced anywhere from 5X to 8X higher than earlier models—quite a difference.

This took me back to my time at RocketFuel. In 2015, RocketFuel was one of the first “real-AI” companies, and we pioneered AI-driven media buying–building machine learning models that powered real-time bidding for advertisers. We invested heavily, spending hundreds of millions on infrastructure and data centers to support the data processing needed to create near real-time marketplaces, as hosting in AWS was not a viable option then. 

The results spoke for themselves. Ad campaigns powered by Rocket Fuel’s models delivered–on average–three times the ROI for customers because we knew how to apply AI in ways that unlocked real value. And it wasn’t just about the technology—it was about how we leveraged the proprietary data to drive those results.

Today, the same lesson applies. AI companies are leading the charge in innovation, but the real value isn’t in the models themselves—those are increasingly commoditized. The true differentiator is how companies apply AI to their own data to extract value. 

Interestingly, according to the latest data from Maxio’s B2B Growth Index Report, AI companies’ growth rates are stabilizing, bringing them more in line with the broader SaaS market. This could indicate that the AI Hype Cycle is starting to return to Earth, which is probably true. 

At the same time, AI pure-play companies are still growing at 31% YoY, significantly better than the overall growth rate (17%) across all industries. When we talk to some of our 75+ AI companies, we hear that they are now refining their pricing strategies to better align with customer value, moving beyond experimentation and toward real-world applications.

The companies that succeed in the AI space will be the ones that, like RocketFuel, know how to turn raw data into meaningful insights and outcomes. They’ll refine their models, adapt their pricing, and, most importantly, capture the value they create in ways that resonate with customers.

At Maxio, We Think About and Talk about Pricing Models A LOT!

The shift toward flexible pricing models requires more than just strategy—it demands infrastructure that can handle complexity. And this is where Maxio comes in. Maxio offers a robust platform that simplifies billing, invoicing, and revenue recognition for companies using fixed-rate, usage-based, and/or hybrid pricing models. My head of Marketing, Julie Neumann, and I just participated in the SaaS Metrics Palooza this week. We discussed these trends in the broader market and specific insights from our Maxio Growth Report. You can find the recording here if you are interested in learning more. Join the conversation on LI here.