Hot Content Series: The Magic Word in Marketing: Dynamic Pricing - 2.5 Million Price Changes per day
2.5 million price changes per day are not unusual in some of the largest marketplaces, such as Amazon. A new buzzword that is currently very popular: dynamic pricing. What customers have seen at the gas pumps at gas stations is now part of everyday life in retail and especially in eCommerce. Retailers use dynamic pricing to increase their sales and, consequently, profits. But what is dynamic pricing, how does it work and why does good data quality play a crucial role?
Dynamic Pricing, Smart Pricing, Intelligent Pricing - Many Terms for one Strategy
In a free market economy, prices have always been based on supply and demand. Many retailers calculate their prices based on order size, competitive situation or costs - that has not changed. But what has changed is the speed at which these prices are adjusted. According to a study by PWC, the management consultancy, four out of ten companies adjust their prices at least once a week, but only one in five companies is already calculating them automatically.
There is potential to reduce sales costs through completely automated price and offer calculation by an average of 14 percent. In contrast with the past, retailers have the opportunity to analyze many factors based on data and to include them in the pricing. Online retailers in particular are in a privileged position to be able to access and react to diverse data with the right tools in an agile and efficient manner.
A wide variety of parameters are taken into account: For example, time, seasonal factors, end devices, product life cycle or customer behavior and profitability can influence dynamic pricing. This is based on the price acceptance of the customers, but it enables retailers to optimize revenue, sales and earnings.
It is probably not surprising that this topic is also being discussed controversially and that consumer advocates in particular are always keeping an eye on possible price discrimination towards consumers. The criticism is particularly focused on personalized pricing, which calculates an individual price based on personal data, such as a customer's previous shopping or surfing behavior. An advantage that consumers benefit from on the Internet, however, are comparison portals that allow customers to use fluctuating prices in their favor.
Artificial Intelligence for Intelligent Prices
The prerequisite for the implementation of dynamic pricing is the use of modern pricing tools. In the digital world of eCommerce, this dynamic only works with the help of artificial intelligence. With this technology, algorithms first look for similar products to calculate an initial price. With the help of countless data from various data pools that are included and analyzed, the price can be optimized and displayed autonomously in the online shop in a few seconds. This saves retailers from manually checking and assigning prices. The aim is to optimize the margin for the provider and to achieve an acceptable price for the buyer.
For this, it is necessary for the company to have complete transparency over its product line, its customers and their behavior in order to test the new pricing strategies. In addition, depending on the application, there is an additional individual benefit: AI can support cross-selling and upselling strategies by automatically suggesting additional suitable product suggestions to the customer, possibly in combination with individual discounts.
200 Sales are Nice, 2000 Transactions for the Same Product are Significantly Better
Complete and reliable data and a transparent environment are essential for promising price management. According to the PWC study, the biggest hurdles to dynamic and automated pricing are lack of IT investments and poor data quality. As also described in detail in the article “Hot-Content Series: AI in Retail - or: Sh ** in, Sh ** out”, artificial intelligence - or the algorithms behind it - is only as good as the data basis. Hypotheses and assumptions of such a system become better when there is more data, and above all, more high-quality data, available.
And this is where the challenges often lie for companies. Every business has data, but it is often enclosed in data silos and therefore not accessible. The goal is to break down these silos and to provide the most comprehensive, up-to-date and high-quality database possible, based on which fact-based decisions can be made. With a central database, minubo creates the basic prerequisites for successful AI applications, because only in this way can smart technologies develop their full benefits and thus earn the trust of users.
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