When was Dynamic Pricing first introduced?

My answer may come as something of a surprise. Given that we’re talking about AI, automation and tech, if you’re familiar with the topic, you might expect me to talk about airlines in the 80s. Yes – that was the rebirth and modernisation of Dynamic Pricing… but, let’s go a little further back than that.

Let me ask: did you know that the price tag was “invented” in the mid-late 1800s? Before that, shopkeepers and merchants were tasked with remembering the prices of their goods, and essentially, bartering. Prior to the price tag, fixed pricing - which could be considered the opposite of Dynamic Pricing - simply didn’t exist. That’s right, Dynamic Pricing was the only game in town. Selling goods and services had a huge “social” component; merchants and customers were both required to be very involved in every transaction.

So then, to answer the question: Dynamic Pricing has, in actuality, been the default mode of pricing for most of human history. It was only in the late 1800s and onwards that fixed pricing took over as the default pricing model. Fixed pricing allowed shopkeepers to sell more products with less effort; think about the advent of the supermarket, for example.

What is Dynamic Pricing like today?

But today, largely thanks to advances in technology, Dynamic Pricing is returning in a big way.  Its re-emergence began in the 1980s, when airline companies set out to reduce the number of empty seats, and ultimately, increase revenue. As the time of take-off grew nearer, airlines would drop fares to try and rebalance supply and demand and sell the maximum number of tickets possible.

Fast forward to 2023 and you’ll find that the core objectives of Dynamic Pricing aren’t much different. Ultimately, Dynamic Pricing is a revenue management tool, used to offer the right price, at the right time, to the right customer. However, advances in technology have made it possible for businesses to offer significantly more “intelligent” pricing that takes into account many more factors that affect what a customer is willing to pay.

Where does Dynamic Pricing work best?

Dynamic pricing works particularly well for inventory that is time-bound. That means airlines, hotels, concert tickets – anything where after a certain moment in time, the price drops to £0. You can’t sell tickets for a flight that left an hour ago!

It works well in these scenarios because it has a clear and compelling value case: if you don’t find the right price; if you don’t balance supply and demand, ultimately, the price of what you’re selling becomes literally zero. So, finding any price that a consumer is willing to pay is, in some ways, unlocking revenue that would have otherwise been lost.

But there are lots of considerations to take into account at this stage – it’s a delicate operation. For instance, you might be worried about discounting too heavily - damaging a business’s long-term pricing strategy - as customers might come to expect lower prices and not buy at the original price. You might be worried about it being unethical; about customers being upset about what are perceived as unfair prices, which could cause damage to your brand. A good example is that of Bruce Springsteen tickets costing $5,000, leaving consumers understandably frustrated at both the ticket seller and the artist. 

This is where AI and humans can work together to achieve the best results. AI - and computers in general - are great at carrying out tasks that require complex calculations, with lots of parameters. They’re able to solve these kinds of numerical problems much, much better than us. However, their focus is narrow. They need revenue managers, pricing analysts - humans, really - to direct them to solve the right problems. Humans must take responsibility for making sure that the outputs are fair, sensitive to any cultural happenings and won’t lead to any reputational damage.

How can AI improve Dynamic Pricing?

Data has been touted as a huge source of value for businesses in every industry. But, many business leaders are yet to see the scale at which data can drive real business results. I believe that we’re on the cusp of one of the biggest transformations in the way that business is done since the beginning of the “digital” age. Why? Because businesses are starting to use AI to unlock the value trapped in their data. And Dynamic Pricing is one of the hottest opportunities for AI innovation. 

With the right fine-tuning, AI can explore millions of possible prices, make predictions about the effectiveness of each price and deliver the one that will maximise revenue – all while accounting for the sensitivities discussed in the previous section. The AI learns by training on data about how customers have responded to prices in the past. 

To give you an idea of what’s possible, we helped Gatwick achieve a 7% uplift in revenue by deploying an AI-powered pricing optimiser. The results can be staggering and achieved quickly, when the right people, processes and technology are in place.

How to implement AI-powered Dynamic Pricing

To help you get started, our Managing Director, John Wyllie has written an article to help you assess how ready your business is to start boosting your bottom line with AI-powered pricing.