When Regulation Meets Revenue Management: Why Independent Pricing Intelligence Is Becoming the Standard

Regulation Is Catching Up With Pricing Technology

Over the past year, regulators and courts in North America have begun to look more closely at how pricing algorithms actually work — not just at the prices they produce.

Two developments stand out:

• New antitrust amendments in California explicitly targeting shared pricing algorithms that rely on competitor data.
• An authorized class action in Quebec challenging pricing practices in the hotel booking ecosystem under consumer protection law.

Although these cases emerge from different legal frameworks, they point in the same direction:

pricing systems must demonstrate independence, transparency, and accountability.

California: Antitrust Law Enters the Algorithmic Era

In October 2025, California enacted Assembly Bill 325 (AB 325) and Senate Bill 763 (SB 763), amending the Cartwright Act, the state’s main antitrust statute.

These amendments explicitly address the use of pricing algorithms shared across multiple businesses, particularly when those algorithms:

• Use competitor pricing or commercial terms as inputs
• Influence or recommend pricing in ways that may restrain trade
• Are adopted broadly across a market or segment

Legal analyses make clear that the law is not limited to explicit collusion.

It also captures situations where algorithmic systems effectively coordinate pricing behavior, even indirectly.

Official legal analysis:

The law came into force on January 1, 2026, significantly lowering the threshold for antitrust scrutiny of pricing software and increasing potential penalties.

Quebec: Consumer Protection and Pricing Practices Under Scrutiny

In Quebec, scrutiny is coming from a different angle — consumer protection rather than antitrust — but the implications for pricing systems are just as relevant.

The Superior Court of Québec has authorized a class action titled:

Chafik Mihoubi v. Priceline.com, L.L.C. et al.

The case alleges that certain hotel booking platforms displayed prices in a way that was misleading to consumers, particularly by excluding mandatory fees and taxes from the initially advertised price, in potential violation of the Quebec Consumer Protection Act.

While this case does not directly target RMS algorithms, it reinforces a broader regulatory theme:

Pricing mechanisms, displays, and logic must be defensible, transparent, and fair to end customers.

Official class action summary:

The Common Thread: Accountability in Pricing Logic

Taken together, California and Quebec illustrate a shared regulatory direction:

• Regulators and courts are no longer satisfied with “the algorithm did it”
• Pricing decisions must be independent, explainable, and non-coordinated
• Systems that mechanically react to competitors face increasing legal and reputational risk

This matters deeply for revenue management software (RMS).

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Price Following vs. Pricing Intelligence

Many traditional pricing systems were built on competitive benchmarking:

• Monitor competitors
• React to market price movements
• Adjust rates accordingly

This approach is increasingly fragile in a regulated environment.

By contrast, pricing intelligence focuses on:

• Demand forecasting
• Customer behavior and willingness to pay
• Property-specific data and scenario simulation

The pricing decision is derived internally, not inferred from competitors.

How Pricepoint Aligns With This Regulatory Shift

Pricepoint was built around independent AI-driven pricing strategies, not competitor-led logic.

Key principles:

• Each property and room type operates on its own pricing model
• Competitor data is not required for the system to function
• Optional market signals, when enabled, are treated strictly as non-binding inputs
• Signals are ignored if they do not add value to the property’s own strategy
• No pricing data is ever exchanged between properties

This structure aligns naturally with the intent behind both:

• California’s algorithmic-pricing antitrust amendments
• Quebec’s emphasis on transparent, consumer-fair pricing practices

Pricepoint customers act as price leaders, not price followers.

Regulation as a Market Signal, Not a Constraint

Rather than slowing innovation, these regulatory developments clarify what modern pricing systems should look like.

They reward platforms that:

• Generate prices from real demand signals
• Avoid algorithmic coordination across competitors
• Can clearly explain how prices are produced

In that sense, regulation is not changing the future of pricing — it is confirming it.

Looking Ahead

As scrutiny increases across jurisdictions, hotels and revenue leaders will increasingly ask:

• Is our pricing logic independent?
• Could it be perceived as reactive or coordinated?
• Can we explain and justify our prices to regulators and customers?

Pricing intelligence — not price imitation — is becoming the standard answer.

References (Official & Authoritative)

• California antitrust amendments on algorithmic pricing (AB 325 / SB 763)
• Quebec class action: Chafik Mihoubi v. Priceline.com, L.L.C. et al.

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