Everybody knows it: If you want to buy a certain product online and compare the price over several days, yesterday’s price is no longer the same. This dynamic pricing technology is increasingly being used by e-commerce providers because it can significantly improve a retailer’s business.
Dynamic Pricing: Previously
The method of dynamic pricing is not new. For example, many bars lure their guests with happy hour specials by offering selected beverages at lower prices in the early evening than at other times. This pricing strategy takes supply and demand into account. But the expected behaviour of the customers and the situation of the competition also play a decisive role.
Dynamic Pricing: Today
Today, dynamic pricing technology works according to the same principle. However, self-learning algorithms are used that can automatically determine and adjust the price in real time based on current market requirements.
The special thing about dynamic pricing technology is that it is not only oriented to the time of day or the competition, but also to the presumed purchasing power of the customer and other customer-specific features.
Big Data as a driver
The better the retailer knows his customers, the more dynamically he can adjust his prices. Dynamic Pricing therefore has a lot to do with Big Data. Nowadays, a retailer usually has a lot of information about his customers. Dynamic Pricing systems are able to analyze and evaluate this Big Data.
Criteria such as website visits, channels or previous sales are then included in the price determination. If a customer often visits a certain website, a high level of interest is assumed. This means that the product is offered at a high sales price. Or depending on whether the customer is surfing with a mobile phone, tablet or PC, for example, the price for one and the same product can vary.
Strategies based on stock levels are also conceivable: With the help of price reduction optimizations, sales can be specifically accelerated.
Opportunities through Dynamic Pricing
Dynamic pricing offers enormous potential for sales growth, as the retailer can demand exactly the price that the potential customer is willing to pay at that very moment under the current conditions. This results in a price that is tailor-made for this potential customer.
Dynamic pricing would be inconceivable without software. Once the software solution has been set up, the time required for price management can be reduced to a minimum. The tool uses algorithms that automatically calculate and display the price within a range specified by the retailer. The software follows a previously defined strategy: Do I as a retailer want to increase my turnover, maximise my profit, sell certain quantities or take a middle course?
In addition to these basic decisions, the tool must be fed with data (internal, external or historical data). The more high-quality data is made available to the software, the easier it is for the tool to determine the best possible individual price. Price discrimination based on data such as residence, nationality, gender or ethnicity should of course be excluded.
Profit maximisation and long-term customer loyalty
The use of Dynamic Pricing and Big Data Analyses has become indispensable in the digital world. Online merchants can not only maximize their profits, but also bind their customers with intelligent discount promotions. The combination of Dynamic Pricing with Chun Prediction is particularly strong: While Churn Prediction determines the time of action, Dynamic Pricing determines the action.
Dynamic pricing also for small providers
Providers in e-commerce must constantly analyze the search and buying behavior of their customers in order to determine which goods or services are particularly in demand. Large providers such as Amazon change their prices several times a day and take advantage of the transparency and data diversity on the net. Dynamic pricing technology also opens its doors to small providers. This also gives them the opportunity to react to changing market conditions and to assert themselves against many other providers.
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