Bill 104 amends Ontario’s Consumer Protection Act, 2002 and the Consumer Protection Act, 2023 to prohibit the use of “personalized algorithmic pricing” to inform a change in price for an individual consumer. The prohibition is framed as an unfair practice and includes express examples such as electronic shelf labelling systems and price presentations on online platforms that vary by a consumer’s personal data or behaviour.
The measure is narrowly targeted at individualized algorithmic price variation: it defines covered technologies and a broad list of data inputs (from browsing history and device profiles to income, credit history and health status). The bill also updates cross-references in each Act’s enforcement provisions and phases in the law six months after Royal Assent, with a specific timing rule for the 2023 Act amendment.
At a Glance
What It Does
The bill adds a new prohibition in two provincial consumer protection statutes making it an unfair practice to use algorithmic or automated processing to set, recommend, or vary a price for an individual consumer based on data about that consumer. It supplies statutory definitions for “personalized algorithmic pricing”, “electronic shelf labelling system” and “online platform”.
Who It Affects
Retailers that use electronic shelf labels or algorithmic price engines, online marketplaces that present retail prices to consumers, system vendors that supply dynamic-pricing software or ESL hardware, and regulators charged with enforcing unfair practice bans under the Acts. Individual consumers are the protected class.
Why It Matters
This is one of the first provincial-level statutory bans on individualized algorithmic price variation aimed at grocery and retail settings in Canada. It creates a legal duty not to target prices using personal data, shifts compliance burden onto retailers and platform operators, and forces technical and operational changes where prices are updated electronically or online.
More articles like this one.
A weekly email with all the latest developments on this topic.
What This Bill Actually Does
Bill 104 inserts parallel prohibitions into the Consumer Protection Act, 2002 and the Consumer Protection Act, 2023. Both Acts receive three new definitions that frame the rule’s scope: what counts as an electronic shelf labelling system, what counts as an online platform, and what the legislature means by personalized algorithmic pricing.
The pricing definition is intentionally broad: it captures algorithmic or automated use of any consumer data to set, recommend or vary a price offered to an individual, and it lists a wide range of data types that trigger coverage.
The core prohibition says it is an unfair practice to use personalized algorithmic pricing to inform a change in price for an individual consumer. The bill then gives two concrete examples to remove doubt: using an electronic shelf label to present a different price to a consumer based on their personal information, and presenting a different price to a consumer on an online platform for the same reason.
Those examples are illustrative rather than exclusive, meaning other forms of individualized algorithmic price variation are also captured.Mechanically, the amendments also tweak each Act’s enforcement cross-references so that the new sections are included in the existing unfair-practices enforcement framework. The bill specifies commencement: most of the Act comes into force six months after Royal Assent, while the 2023 Act amendment (section 2) comes into force either when a related section of a prior statute comes into force or six months after Royal Assent, whichever is later.
The statute leaves regulatory detail open — the definition anticipates additional categories “prescribed by the regulations,” and it does not create sectoral exemptions or technical compliance rules within the text.
The Five Things You Need to Know
The bill makes it an explicit unfair practice to use algorithmic or automated processing to set, recommend or vary a price for an individual consumer based on data about that consumer.
It adds statutory definitions for “personalized algorithmic pricing,” “electronic shelf labelling system,” and “online platform,” with the pricing definition listing data types such as browsing history, device profiles, inferred willingness to pay, income, pay schedule, credit history, location and health data.
The text gives two illustrative examples that explicitly capture price variation via electronic shelf labels and price presentation on online marketplaces when those changes rely on individual consumer data.
Both the Consumer Protection Act, 2002 and the Consumer Protection Act, 2023 are amended in parallel; each Act’s enforcement cross-references are updated so the new sections fall under existing unfair-practice enforcement mechanisms.
The Act generally comes into force six months after Royal Assent, but the 2023-Act amendment takes effect on the later of that six-month date and the commencement of a previously scheduled related provision, making timing dependent on earlier legislation.
Section-by-Section Breakdown
Every bill we cover gets an analysis of its key sections.
Defines key terms: ESLs, online platforms, and personalized algorithmic pricing
The bill inserts three carefully scoped definitions into the 2002 Act. “Electronic shelf labelling system” is defined by function (displaying and updating prices at or near the product). “Online platform” is defined by marketplace activity. The pricing definition is the operational core: it ties the ban to algorithmic or automated processing and enumerates data categories (from browsing history to health status). That enumeration both guides enforcement and signals the legislature’s intent to capture sensitive categories, while leaving room for regulations to add further attributes.
Creates an unfair-practice prohibition on individualized algorithmic price changes
Section 16.1 declares it an unfair practice to use personalized algorithmic pricing to inform a change in price for an individual consumer. The bill then lists two examples — differing prices via ESLs and differing online platform prices — to make the practical reach clear. Because the prohibition is framed as an unfair practice, it plugs into the Act’s existing enforcement architecture (inspection, orders, penalties) rather than creating a stand-alone enforcement mechanism.
Parallel changes to the 2023 Act to ensure consistent coverage across statutes
The bill reproduces the same definitions and prohibition in the Consumer Protection Act, 2023, creating symmetry between the two Acts. Parallel language means businesses operating under rules from either statute face the same substantive ban. The amendment also updates the 2023 Act’s enforcement cross-reference so regulators can treat violations under the new section as unfair practices subject to existing remedies.
Delayed coming-into-force with special timing for the 2023 amendment
The Act mostly comes into force six months after Royal Assent. However, the clause for the 2023 Act amendment becomes effective on the later of that six-month date and the commencement of a particular section of an earlier statute, which creates dependency on prior legislative timing. Practically, this staggers implementation and may create a brief window where businesses covered by one Act but not the other must track staggered obligations.
Formal short title
The Act’s short title is the Fair Grocery Prices Act, 2026. While ceremonial, the title signals the legislative focus on grocery pricing and retail markets and may guide future regulatory or enforcement prioritization.
This bill is one of many.
Codify tracks hundreds of bills on this topic across all five countries.
Explore this topic in Codify Search →Who Benefits and Who Bears the Cost
Every bill creates winners and losers. Here's who stands to gain and who bears the cost.
Who Benefits
- Low-income and vulnerable shoppers — the prohibition targets practices that could have singled out people on social assistance, irregular pay schedules or lower incomes for higher prices, reducing the risk of exploitative individualized price discrimination.
- Price-comparison and consumer advocacy groups — a statutory ban on individualized algorithmic price variation preserves the meaningfulness of advertised prices and simplifies monitoring for unfair pricing behaviour.
- Independent grocers and small retailers who do not—or choose not to—use individualized algorithmic pricing — they gain a level playing field against competitors who might otherwise personalize prices using customer data.
Who Bears the Cost
- Large grocery chains and retailers using dynamic pricing engines — they must change pricing algorithms, modify or reconfigure ESL systems, and absorb compliance and auditing costs or remove individualized features.
- Online marketplaces and third‑party sellers that tailor prices to individual visitors — they will need to alter price-presentation logic, update platform terms and potentially redesign personalization services.
- Software and ESL hardware vendors — vendors will face demand for compliance features, audit trails and configuration options to prevent prohibited individualized price changes, at development and deployment cost.
Key Issues
The Core Tension
The central tension is between protecting consumers from covert, data-driven price discrimination and preserving commercial flexibility to use algorithmic pricing for legitimate competitive or efficiency reasons; the bill errs on the side of consumer protection but leaves enforcement and narrow exemptions unresolved, forcing regulators to balance anti‑discrimination goals against the economic value of dynamic pricing.
The bill’s broad definition of “personalized algorithmic pricing” intentionally sweeps in many data types and any algorithmic processing, but the statutory text leaves operational detail to regulations and enforcement practice. That raises practical questions: how will regulators detect and prove the causal link between a specific consumer’s data and a particular price change, especially where algorithms use opaque models or where prices are set at group or segment levels rather than strictly per individual?
The examples (ESLs and online platform price presentation) clarify intent, but businesses can reengineer pricing systems to operate on micro-segments or contextual signals that are not clearly tied to an identified individual, potentially evading the prohibition.
There are also unresolved interface issues with other legal regimes. The bill flags sensitive categories such as health status and credit history, which intersect with privacy law (provincial and federal) and human rights protections, but it does not address data access, retention, or audit protocols: regulators will need technical expertise and investigatory powers to review algorithmic logs.
Finally, the prohibition treats individualized algorithmic pricing as an unfair practice without creating tailored exemptions for common, non-discriminatory dynamic pricing (for example, time-of-day discounts, inventory-driven markdowns, or geographically based pricing), leaving ambiguity over which non-personalized dynamic mechanisms remain permissible.
There's more to this law than the bill.
Codify Laws traces every connection across the legislative lifecycle.