How to optimise revenue and growth with dynamic pricing

Dynamic pricing is not a new concept. ‘Happy Hour’ drinks in pubs, the higher price of airline tickets during holiday periods, and cheaper products on Black Friday or Boxing day are just a few examples of old-fashioned (and widely accepted) dynamic pricing.

The question is: how do organisations confidently alter their product’s pricing based on the market environment? Are they able to predict their revenues and maximise this over time? More importantly, how are they finding the right balance between immediate earnings and long-term growth?

These are challenges in many competitive markets. Nowadays many traditional business models (think taxis, or online retailers) are being disrupted by innovative, multifaceted technology applications (e.g. Uber and Amazon). This has facilitated easier access to more products and services by consumers, a greater transparency of the market, and led to fast-action on pricing strategy by smart retailers and service providers.

However, implementing the ‘best’ pricing model is not always easy. Many organisations continue to keep their prices steady, not understanding how dynamic pricing could benefit their organisation. Meanwhile, others follow the wrong dynamic pricing patterns for their product or service. Even highly successful companies like Amazon, Google and Uber have had strategic failures in their pricing algorithms in the past, and have had to refine their algorithm in order to maintain their competitive position in the market.

 

Where did they go wrong?

Offering different prices for the same DVD to different customers caused a lot of anger amongst consumers. More interestingly, the wrong algorithmic pricing set by sellers led to a $100 book being offered for $23.7 million through their recently released ‘buy box’ service. These are just a couple of examples of algorithmic errors from the largest e-commerce company Amazon.

Another example is from Uber. An Illinois woman was charged nearly $1000 for a ride from a Chicago suburb to O’Hare International Airport and back – a trip that would normally cost $120. After all of these trials and errors, however, both companies are now able to apply the optimum pricing algorithms that increases net sales revenue every year, without alienating their customers.

While many of us would think dynamic pricing is all about offering the lowest price in the market, for many of these companies this is not the main driver for price optimisation. For example, Amazon only offers competitive prices on its most popular products; those with highest views and best-selling rates. Overall, only about 30% of Amazon's products have the most competitive price in the market. Yet, many people shop at Amazon because they believe they are being offered the lowest price on all products.

 

Learn from their experiences

While many large organisations are now willing to apply dynamic pricing strategy to boost their revenue, there are some key things that we can learn from the experiences of companies like Amazon and Uber.

Dynamic pricing is not a race towards the lowest price in the market, but about who is making the best pricing decision in the market, at the right time, in the right place. 

Another important aspect of a dynamic pricing strategy is understanding how to keep the balance between earnings and growth. This means considering how much we care about increasing our customers’ lifetime values as well as growing the number of our new customers, and leads to thinking about what is beneficial for the company in the long-term rather than a short-term high-value outcome. 

 

How observable is your market environment?

The overall market environment has a significant impact on whether adopting a dynamic pricing strategy is the right option for you. For some businesses revenue estimation is quite predictable, therefore, employing a simple pricing strategy might be the best solution for optimum growth. For others, however, having a clear vision of how to maximise revenue is next to impossible. The presence of competitors, the customer's demographic impacts, seasonality, product segmentation, shelf life and economic factors are all examples of the driving factors behind adopting a dynamic pricing model to sustain growth. 

Ultimately, it’s important to remember that a dynamic pricing model does not provide the best outcome for all businesses. The best approach is to create your own unique pricing strategy and refine it over time.  Pricing optimisation is not about how fast or drastically you change your price in the market to react to changes, but about how smart you make that decision to drive better business outcomes.

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