In response to the Competition Bureau Canada’s call for feedback on algorithmic pricing, we submitted the following letter.
See original PDF here.
August 3, 2025
Re: Algorithmic Pricing and Competition
Algorithmic Pricing Needs Greater Transparency and Guardrails
Dear members of the Competition Bureau,
We are Technologists for Democracy, a grassroots advocacy organization based in Toronto. Our position largely concerns the effects of algorithmic pricing from the consumer perspective.
Most consumers – 68% – feel that dynamic pricing unfairly takes advantage of them.1 This is not necessarily because of an inherent unfairness of dynamic pricing, but because most companies operate dynamic pricing through a purely profit-oriented lens focused on the short term. There is little thought given to transparency, company trust, or consumer well-being.
Consumers are particularly vulnerable to downstream effects of algorithmic pricing, especially in markets of essential goods, markets with high barriers to entry and effective monopolies. Without reasonable alternatives, consumers become captive to price increases. Low-income consumers are particularly affected, due to any given purchase constituting a larger portion of their income. Housing is one such essential market – we welcome the Competition Bureau’s current probe into the use of algorithmic pricing for setting rental prices, and would recommend prohibiting the use of algorithmic pricing for housing (recommendation #6 below).
In addition, we believe algorithmic pricing can lead to market inefficiencies. When companies offer personalized dynamic pricing, with different prices for each individual consumer, it becomes difficult for consumers to compare and recommend prices between competitors, and difficult for competitors to efficiently set prices according to the market. We see personalized dynamic pricing as a dangerous opportunity for larger entities to unfairly exploit their market dominance by reducing the information available to their competitors.
To limit the harmful downstream outcomes of algorithmic pricing, our recommendations focus on improving transparency and guardrails surrounding algorithmic pricing. In the same way that nutrition facts labels and ingredient lists allow consumers to make informed decisions before purchasing food, labels on algorithmic pricing would allow consumers to make informed decisions before purchasing digital and digitally-enhanced products and services.
To improve transparency, we support regulation and enforcement which would require that companies clearly disclose:
- Whether or not algorithmic pricing is in effect for a given product or service.
- If algorithmic pricing is in effect, whether the pricing model was developed in-house or is outsourced to a third party.
- If algorithmic pricing is in effect, whether or not AI/machine learning is used for algorithmic pricing, as opposed to a rule-based model.
- If algorithmic pricing is in effect, what data is inputted into the pricing model. For example:
- Consumer data such as location, credit score or demographic profile,
- Inferred data such as consumer emotional state,
- Internal data such as sales counts,
- External data such as competitor prices or current weather,
- Etc.
To ensure enforcement of policies, we support:
- Establishing team(s) and process(es) to handle complaints and appeals for policies related to recommendations in this letter.
In addition to educational regulation, we also support investigations as to the feasibility of:
- Prohibiting personalized, dynamic algorithmic pricing from being used in certain market sectors such as those of essential goods and services (including food, housing, and medication).
- Regulation of prices such as through a Maximum Retail Price policy, effective in countries such as India.
We believe that these suggestions will:
- Improve consumer trust of algorithmic pricing.
- Inform consumers as to what personal data is involved in making a purchase.
- Lower the competitive barrier to entering markets already populated with algorithmic pricing models, while still allowing companies to maintain secrecy of the inner workings of proprietary pricing models.
- Reduce possible harms on consumers and competitors alike by preventing predatory pricing.
- Ensure equal opportunity of access to essential goods and services for consumers.
We urge the Competition Bureau to increase transparency and implement guardrails on the use of algorithmic pricing.
Sincerely,
Khasir Hean
[email removed for privacy]
Henry Wilkinson
[email removed for privacy]
Jenny Zhang
[email removed for privacy]
Cole Anthony Capilongo
[email removed for privacy]
Technologists for Democracy
techfordemocracy.ca
- Gartner Marketing Survey Finds 68% of Consumers Report They Feel Taken Advantage of When Brands Use Dynamic Pricing. December 16, 2024. https://www.gartner.com/en/newsroom/press-releases/2024-12-16-gartner-marketing-survey-finds-68-percent-of-consumers-report-they-feel-taken-advantage-of-when-brands-use-dynamic-pricing ↩︎
