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The Battle Between Dynamic Pricing And The Bots That Will Defeat Them | D!gitalist Magazine

In a frequently cited example, dynamic pricing is used, with great effect, in the airline industry. Before we take a look at this, it’s worth recapping a few things about the industry’s economics. In its most recent forecast, the International Air Transport Association (IATA), projects industry-wide, net post-tax profits rising from $12.9 billion in 2013 to $18.7 billion in 2014. For context, IATA’s 2014 forecast would be the most profitable year the industry had experienced over the last 15 years – with the second-highest year being 2010 with $17.3 billion in revenue.

To some, this may appear to be a sizeable profit. But for a $745 billion industry that is notoriously cyclical, it represents a profit margin of only 2.5%. And from the IATA’s perspective, this is a fragile margin amid a risky business environment. With fuel accounting for anywhere between 29%–51% of operating costs across the industry, the number of flying passengers (known as load factor) is a key metric to follow. In its adoption of dynamic pricing, the industry has embraced a view that pricing for customers is fluid within regulatory constraints, enabling them to maximize profits to stay on the right side of profitability.

What about the store environment? A large European retailer thinks that dynamic pricing could help it move perishable goods. The ideal scenario requires that fresh meat and fish is sold based on demand so the last filet of salmon, for example, is sold exactly five minutes before the store closes. This approach has an impact on inventory, profitability, and society, and a goal to avoid destruction of produce.

There are many benefits when it comes to dynamic pricing for retailers and enterprises. But for every action, there is an equal and opposite reaction. In the airfare war, there’s Hopper – a price-prediction algorithm that serves to answer one question: Should I buy my flight now, or should I wait? The company achieved capability by archiving billions of airfare records to build out an algorithm that predicts when to buy a ticket. Sounds like a familiar topic, right?

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The Battle Between Dynamic Pricing And The Bots That Will Defeat Them.

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