The Decline of ARR and the Rise of Success-Based Pricing

What’s the buzz

Annual Recurring Revenue (ARR) is foundational in SaaS metrics. It’s the cornerstone of SaaS valuation multiples—high margin, predictable, and (usually) growing. This model enables SaaS companies to become highly profitable at scale.

However, the rise of AI is shaking up the traditional software revenue model. What happens when ARR isn’t the primary driver of value and can no longer be used as the basis for SaaS company valuations?

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So what?

Different Non-Traditional Pricing Models

With AI-driven solutions, we’re seeing a shift in how AI companies charge for value:

• Charging per successful AI resolution of a support ticket

• Charging per photo edited by AI

• Charging per audio/video (or audio/video minute) produced

• Charging per assigned task completed by an AI agent

• Charging per conversation finished by an AI agent

• Charging per input/output token to access an LLM

We’re moving away from subscription-based models toward charging for outcomes and results—the work successfully delivered by software and AI agents.

Now what?

The Rise of Disruptive AI Pricing Models

The demand for new pricing models has been wild. In an era where automation and APIs are growing, the value of a service isn’t tied to how many people use it, how much bandwidth it consumes, or server calls it enables.

Instead, it is increasingly based on the tangible outputs and measurable and billable results it delivers.

Salesforce created a buzz by introducing Agentforce, charging $2 per conversation, and paving the way for others.

• Intercom introduced Fin AI, charging $0.99 per resolved customer issue. “You only pay when Fin resolves a customer’s question,” they explain.

• Zendesk charges based on autonomous resolutions, offering flexible pay-as-you-go or discounted upfront plans.

Different AI categories are in the process of developing their unique pricing flavors:

• Legal AI might establish charging per AI-generated summary or demand package.

• Creative AI might charge based on the number or volume of (audio-visual) content produced, like video/audio minutes generated or images completed.

• GTM AI tools might charge per task completed or workflow executed.

Bardeen is another example of a disruptive pricing model. They use a credit-based system to charge for their AI and premium services. Key points about their pricing model entail:

1. Credit Currency: Credits are the "currency" used to pay for different premium actions and outcomes within the Bardeen platform

2. Premium Playbooks: Only premium playbook-runs consume credits. Non-premium playbooks remain available for unlimited usage at no charge

3. Credit Cost: Each premium action costs one credit, making it easier to understand and predict usage

4. Pricing Tiers: Bardeen offers different pricing tiers (Free, Pro, Business, and Enterprise) with varying amounts of monthly credits

AI-Specific Charging

1. AI-Powered Actions: Bardeen has introduced AI-powered actions like Categorizer, Message Generator, and Research Generator. These likely fall under the premium actions that consume credits

2. Complexity-Based Pricing: The number of credits spent varies based on the complexity of the automation. For example:

   • Basic automation, such as writing or categorizing an email, typically uses one credit.

   • More complex automation, such as exporting data to a CSV, may use multiple credits per line of data

3. Autobooks Example: For automated processes that run periodically:

   • If a scraper runs over one link and scrapes a list of 10 items, that's ten credits.

   • If those ten items go through a second scraper, producing ten results, that's another ten credits.

   • In total, this autobook would consume 20 credits per trigger

Pricing Structure

• The Free plan offers a 14-day trial with 250 credits

• Paid plans (Pro, Business, and Enterprise) provide a set number of monthly credits that replenish each month

• Users can purchase additional credits if needed

• It's worth noting that Bardeen has recently simplified their pricing structure to make costs more transparent upfront and to allow for unlimited team members on all plans

The table below lists the first 25 of 50 AI companies with (partially) disruptive pricing models (companies 26 to 50 follow in the next table):

AI companies 1 - 25 with different pricing models.

And next?

Selling Work, Not Just Access

This shift mirrors usage-based or consumption-based pricing models but with a twist. Companies are moving from selling access or usage to selling completed tasks.

This means customers may have a lower total cost of ownership (TCO) with greater pricing flexibility employing much fewer people.

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Knowledge Corner - A History of Software Pricing

In the early days, software was sold on-premise, with customers paying upfront and taking on the financial risk.

Subscriptions evolved to make software accessible, with lower upfront costs and the option to cancel if the product didn’t deliver value.

Today, most subscription-based SaaS captures around 10-15% of the economic value they deliver.

Success-based models, where billing fully aligns with outcomes, can easily capture up to 25-30%.

AI companies 26 - 50 with different pricing models

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Closelooknet Lens: Spotting the ripple effects

The Challenges of Success-Based Pricing

Success-based billing sounds excellent, but a deep dive reveals it is complex. Attribution becomes tricky; success can lie in the eye of the beholder, and customers may wonder, "Did our team drive the outcome, or was it the product or something in between?" And if the latter, how do we divide and properly bill the “success cake”?

To solve the problem, Intercom’s Fin agent charges $0.99 per resolution. To avoid attribution issues, Intercom tracks “hard resolutions” (confirmed by the customer) and “soft resolutions” (when the customer exits the conversation without reopening it in 24 hours).

SaaS Valuation Metrics: A Closer Look at Revenue Multiples

The transition to success-based pricing will profoundly affect public and private SaaS company valuations.

In Software as a Service (SaaS), revenue multiples have become the go-to metric for valuation. This approach, which uses projected revenue for the upcoming 12 months, has emerged as a crucial shorthand framework for assessing SaaS businesses.

Why Revenue Multiples?

The preference for revenue multiples in SaaS valuations stems from several factors:

1. Profitability Challenges: Many SaaS companies are not yet profitable or generating significant free cash flow (FCF).

2. Industry-Wide Comparability: Revenue multiples offer a standardized metric for comparing companies across the SaaS sector.

3. Long-Term Potential: The SaaS model is built on the premise that early growth will translate into profits as the business matures.

Calculation Method

The revenue multiple is often calculated using the formula: Revenue Multiple = Enterprise Value Next Twelve Months NTM Revenue Revenue Multiple = Next Twelve Months NTM Revenue Enterprise Value​ Where Enterprise Value = Market Capitalization + Debt - Cash.

Current Market Insights

The SaaS market currently shows the following MetricValue: Overall Median Multiple 5.6x, Top 5 Median Multiple 16.7x, 10-year Treasury Yield 4.25%

These figures highlight the significant premium placed on top-performing companies vis-a-vis slow and unstable growers.

Implications and Considerations

While revenue multiples offer a straightforward valuation method, it's important to note their limitations. Discounted Cash Flow (DCF) models, often used in other sectors, become challenging in SaaS due to the need for long-term assumptions.

The wide valuation gap between the overall median and the top-tier multiples in Saas companies underscores the stock market’s differentiation between high-growth, market-leading companies and the broader SaaS sector.

This disparity reflects investors' willingness to pay a premium for companies demonstrating exceptional growth and market positioning.

SaaS Financial Metrics: Unpacking the Rule of 40 and GM Adjusted Payback

While revenue multiples provide a valuable benchmark for SaaS valuations, investors and analysts should consider them as part of a broader evaluation framework, considering factors such as growth rates, market position, and potential for future profitability.

In the SaaS industry, two key metrics have gained prominence for evaluating company performance and efficiency: the Rule of 40 and the Gross Margin (GM) Adjusted Payback.

These metrics provide valuable insights into a company's growth, profitability, and sales efficiency.

Rule of 40

The Rule of 40 is a performance metric that combines a company's growth rate and profitability. It's usually calculated as:

Rule of 40 = Revenue Growth Rate + Free Cash Flow Margin Rule of 40 = Revenue Growth Rate + Free Cash Flow Margin

This metric is typically calculated using the Last Twelve Months (LTM) and Next Twelve Months (NTM) data for growth rates and margins.

The Free Cash Flow (FCF) is determined by FCF = Cash Flow from Operations − Capital Expenditures FCF = Cash Flow from Operations − Capital Expenditures.

A score of 40 or higher is generally considered excellent, indicating a healthy balance between growth and profitability. Recently, the Rule of 40 was replaced by the Rule of 30 to reflect slower growth in the SaaS sector.

Also, the growth part has become more important than the profitability part as quite a few XaaS companies have seen annual revenue growth deteriorating in 2023 and 2024 to the high teen level, comparable more to the large megacap companies than to hypergrowth companies making their high multiples unsustainable.

GM Adjusted Payback

The GM Adjusted Payback period is a measure of sales efficiency, calculated as GM Adjusted Payback months = Previous Quarter S MNet New ARR in Quarter × Gross Margin × 12GM Adjusted Payback months = Net New ARR in Quarter × Gross MarginPrevious Quarter S M ​ ×12 Where:

• S&M: Sales and Marketing expenses

• ARR: Annual Recurring Revenue

This metric reveals how long it takes for a SaaS business to recover its fully burdened Customer Acquisition Cost (CAC) on a gross profit basis.

Calculation Challenges

For public companies that don't report net new ARR, an implied ARR metric is often used: Implied ARR = Quarterly Subscription Revenue × 4 Implied ARR = Quarterly Subscription Revenue × 4 Net new ARR is then calculated as Net New ARR = Current Quarter ARR − Previous Quarter ARRNet New ARR = Current Quarter ARR − Previous Quarter ARR.

Implications for SaaS Analysis

These metrics offer valuable insights into the following:

1. Growth vs. Profitability: The Rule of 40 (30) helps balance the trade-off between rapid growth and profitability.

2. Sales Efficiency: GM Adjusted Payback period indicates how quickly a company can recoup its customer acquisition costs.

3. Comparative Analysis: These standardized metrics allow for easier comparison across SaaS companies.

By utilizing these metrics, investors and analysts can better understand a SaaS company's financial health and operational efficiency. Considering these metrics alongside other financial and operational indicators is crucial for a holistic evaluation.