Demystifying Algorithmic Pricing: A Timeless Business Strategy in a Modern Disguise

In March 2024, the US Department of Justice and the US Federal Trade Commission raised concerns about algorithmic pricing, suggesting it could lead to illegal price fixing. Similarly, the European Union has issued guidelines on algorithmic pricing , emphasizing the potential risks of anti-competitive practices and advocating for transparency. China has introduced detailed regulations focusing on algorithmic recommendation systems to prevent economic harms and ensure user autonomy. In Australia, the Australian Competition and Consumer Commission (ACCC) has also expressed concerns about the competitive impacts of algorithmic pricing. These regulations highlight the importance of understanding and addressing these concerns within various industries, including hotel, supermarkets, retail, restaurants, fitness centers, and other sectors that set prices.

Understanding Algorithmic Pricing: A Historical Perspective

Recently, "algorithmic pricing" and “dynamic pricing” have become buzzwords, often evoking images of complex AI and mathematical models that unsettle consumers and regulators. However, the core principles behind this modern tool are as old as commerce itself. An algorithm is simply a set of rules guiding decision-making, from simple observations to sophisticated models, aimed at helping managers make better decisions.

How Do You Set Your Prices?

If you're like most revenue managers and pricing managers, you probably look at your forecast, past and recent performance, sales pace, local events, and competitor prices. Depending on your company, you might also consider recommendations from your revenue management or pricing system, plus other sources of competitive and market information. You likely meet with colleagues regularly to discuss pricing strategies. Your revenue management system may provide pricing recommendations, or if you use Excel or a more manual system, you might follow rules for when to open and close lower rates. Does this mean you’re doing algorithmic pricing? The answer is YES! Remember, all an algorithm is is a rule or set of rules for making decisions.

Historical Context of Pricing Strategies

Dynamic pricing isn’t new. Merchants in ancient markets adjusted prices for goods based on supply and demand. A fishmonger raising prices as stocks dwindled or a merchant adjusting grain prices during a drought were practicing early forms of algorithmic pricing. These methods aimed to optimize profitability based on market conditions.

Simple Doesn’t Mean Ineffective

I once had a first-year undergrad at Cornell who was fascinated by the 'stock market'-like pricing in bars near financial districts. He asked how they decided which price to charge. I suggested they likely used a simple Excel spreadsheet with IF() statements to raise prices when sales hit a certain level. He looked at me like I had told him that there wasn’t a Santa Claus and he told me that it must be more complex, involving advanced economic models. I told him to come back in a few years; he might see that simple tools often suffice in real-world settings. Similarly, early revenue management tools in various industries started as basic spreadsheet models before evolving into sophisticated software solutions.

Evolution from Manual to Automated

As businesses grew and markets became more complex, the need for efficient decision-making increased. Tools evolved from mental calculations to written ledgers, then to calculators and Excel spreadsheets, and eventually to sophisticated software. Each technological advance offered greater precision and speed, but the underlying strategies remained consistent.

Understanding Modern Algorithmic Pricing

Today, algorithmic pricing may involve software that analyzes vast datasets to adjust prices in real-time. These systems fundamentally perform the same task as their historical counterparts—balancing supply and demand through pricing adjustments. The key difference is their ability to process information at an unprecedented scale and speed. However, it's important to understand where algorithmic pricing could potentially cross the line into price collusion.

Media Influence and Public Perception

Media often portrays algorithmic pricing as a shadowy force with unchecked power over consumers, creating a sense of mistrust. This misrepresentation tends to focus on the mechanics of these tools rather than their intended purpose. A more balanced narrative would highlight that algorithmic pricing is a natural progression of market practices and emphasize the importance of transparency in their deployment.

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Addressing Concerns with Management, Owners, and Legal Departments

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As a revenue and pricing manager, you need to assure your senior management, owners, and legal departments that using algorithmic pricing is both ethical and effective. Emphasize that these tools are designed to optimize pricing based on real-time data, ensuring competitive rates without colluding with competitors. Highlight the benefits of increased revenue and efficiency and ensure transparency in how these systems operate. Engaging the legal department early can help ensure that your practices comply with regulatory standards and avoid any legal pitfalls.?

Conclusion

Algorithmic pricing is not a radical departure from traditional business practices but a modern extension of them. By framing it within its historical context and emphasizing the continuity of market principles, revenue managers across various industries can demystify this concept and build trust with general managers, owners, and legal departments. As we navigate the digital landscape, let’s remember that while the tools have changed, the goals of commerce remain the same. Stay tuned for the next article, where we'll explore the fine line between pricing intelligence and price collusion, and how your business can navigate these complexities effectively.

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