Dynamic pricing engine for Retail Industry
Dynamic pricing is an automated price-setting system that depends on a number of parameters. It helps retailers set the best prices for their items depending on what their business goals are market changes that have occurred. When dynamic pricing is utilized properly, retailers are able to react to competitors and changes in customer behavior in real-time.
Dynamic Pricing Data Requirements
This strategy relies heavily on qualitative data. Whether it is your rivals’ prices, stocks, and promotions or your own sales, promotions, prices, and costs, every single variable is crucial in order to apply dynamic pricing successfully.
Retailers need to gather an incredible amount of information from a number of different sources. There are a few requirements that must be followed when gathering data:
- Format of data
In order to process data with success so it may be used for dynamic pricing, retailers must save it under a universal format, regardless of where the data is from.
- Product matches
Prior to gathering competitive data, retailers must make sure that their items are matched correctly. If not, even if the data is gathered properly the prices will not match up.
- Data accuracy
Even though computer programs are generally accurate, the data gathered is not guaranteed to be error-free. The program must be analyzed by another program utilizing special algorithms or manually to ensure its accuracy.
- The freshness of data
It could take up to 72 hours to obtain all price points from competitors. As a result, case data may not be as dependable, especially if competitors are changing their prices 3-4 times a day.
- The delivery time of data
The less time that it takes for data to go into the retailer’s ERP system post collection and processing, the easier it is for the retailer to process and analyze the data.
- Data transparency
The quality of the data needs to be clear to the retailer, as they need to be able to see every match, collection, and delivery metric in order to figure out whether or not the data can be used to confidently set prices.
As long as the data has all of these traits, it can be used for dynamic pricing.
Dynamic Pricing in Retail
Although dynamic pricing is not rule-based pricing, it does include rule-based pricing. Dynamic pricing is an intricate system where pricing rules, models, approaches, and strategies collaborate in a complex price management process.
This method uses metrics such as business goals, market insights, and customer data in order to make a set of pricing rules that will boost business efficiency.
If dynamic pricing is done correctly, it helps retailers successfully compete against various rivals at the right price level; setting the prices for local, loyal, or brand new customers that have specific needs while considering competitor prices, stocks, and promotions.
The Advantages of Dynamic Pricing
Dynamic pricing can be done in different ways depending on the industry you are in or your target customers. How it is applied depends on a variety of topics including assortment, customer, rivals, items, and sales history.
The key advantages of dynamic pricing include:
- Direct responses to every market change
- Pricing rules which assist companies in reaching their business goals
- Dynamic pricing works around the clock and carries outpricing very accurately
- Category managers remain in control of their pricing decisions
- Small pricing increments can boost margins significantly
- Based on research by Forrester, dynamic pricing can boost profits by 25%.
However, we can’t stress this enough: in order to receive the best and most accurate results, you need to make sure that you invest in good technology. Otherwise, your prices will not be optimal, causing you to make pricing decisions that won’t positively impact your sales or your company. Also, keep in mind that the point of dynamic pricing is not about finding the highest or the lowest prices for your items. It is used to find the optimal prices, and the best price is most certainly not always the lowest or highest price.
If a retailer’s data is no longer up-to-date, incomplete, or just is not correct, pricing decisions will negatively impact companies and dynamic pricing will not work. However, when data is collected properly, dynamic pricing is useful to retail companies of all sizes, which is why it is one of the top five investment areas. In fact, effective dynamic pricing accounts for a 2-5% sales growth in businesses along with a 5-10% margin increase.
On the other hand, successful dynamic pricing relies on accurate sales prediction and data analysis that is best conducted by machine learning algorithms. Therefore, it is imperative that you find the software you can count on.