THOUGHTS

Dynamic Pricing: What Are the Biggest Challenges?

May 2, 2018

Dynamic pricing has been one of the most lucrative pricing strategies that companies use to mint money. While it is not an entirely new concept, companies have been using it randomly over the years. In laymen terms, dynamic pricing is a strategy in which product prices continuously change, sometimes in a matter of minutes, in response to real-time supply and demand. Examples include Uber for taxi rides that sets its rates based on supply and demand, consumer electronics shop MediaMarkt that has installed electronic price tags to change prices depending on competitor behavior, and the gas station chain Tanq4you that bases its rates on the actual oil price and the weather condition. But in several cases, implementing dynamic pricing may not turn out to be as easy as it sounds. Here are some of the challenges that companies face while implementing dynamic pricing strategies:Request Free Proposal

Data accuracy

Dynamic pricing relies heavily on data, and when pricing is being changed on the basis of hours or even minutes, ensuring that the data driving pricing decisions is accurate is highly critical. While there’s a growing ecosystem of data providers and the techniques by which data is collected and filtered are sure to improve, businesses should refrain from assuming that bad data won’t make it into their systems.

Customer perception

Many consumers are not aware of the fact that retailers resort to dynamic pricing to alter prices on a regular basis, but as it becomes more noticeable thanks to the web, companies must consider the perception issues it raises. A customer who observes that a product can become cheaper or more expensive within minutes might get discouraged at the prospect that they could end up paying more for a product based on little more than what they would pay if they waited longer. Also, there is the possibility that some users will notice dynamic pricing, but won’t quite understand what’s going on, resulting in a reduction of trust.

Algorithm errors

Several instances from the past emphasize on the fact that algorithms are far from perfect and can produce costly errors. As retailers embrace dynamic pricing models which are of course based on algorithms, thought should be given to how mishaps can be minimized and what policies will govern when a mishap results in a significant mistake (e.g., customers being able to purchase a product at a ridiculously low price).

Change in customer behavior

As the existence of dynamic pricing becomes more evident to consumers, companies will need to come to terms with the possibility that it could impact customer behavior. Dynamic pricing undoubtedly has the potential to encourage sales, but is it possible that in some instances it could it impede sales? If customers get a feeling that the price of a product might dip in the very near future, or perhaps even on the same day, this could result in some of them deciding to hold off on a purchase. And as every retailer knows, a delayed purchase is much more likely to become a purchase that never happens or happens somewhere else.


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