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Exploring dynamic pricing using DecisionRules
Dynamic pricing is a strategy that uses variable prices instead of fixed ones. Dynamic pricing concept, as such stands unsurprisingly in opposition to what we might call Static pricing. With static pricing a fixed price might stay for a very long time, even if it is no longer competitive, until someone comes and changes it. With dynamic pricing, it is possible to adjust prices continuously and automatically, based on many different factors. This allows you to always keep the prices of your product relevant and competitive. Please note, Dynamic Pricing is different from the concept of what we would call Personalized Pricing, which is a strategy that uses clients' data to set the prices and could be considered, at the very least, controversial or even dangerous for the customer's trust.
Why dynamic pricing?
As with many things today, the idea of dynamic pricing came along with the evolution of the internet. At first, the static pricing, the strategy very much present in brick & mortar stores, was sufficient, but as more and more people became accustomed to shopping online the demands on price change velocity rose sharply mainly due to the following two reasons:
Availability of comparison
It became very easy for a regular customer to compare prices of a particular product in many different stores with minimal effort. Now we even have a website specifically designed for this purpose, therefore a majority of customers will have done at least a nominal amount of comparisons pricing.
Frequent market fluctuations
As the availability of comparisons emerged, more frequent price fluctuations across the market have emerged. Many companies are now watching market prices, demand, stock, and other factors and setting their prices based on them daily. This now makes keeping competitive prices even more difficult than before, doing so manually might now be impossible.
Implementing dynamic pricing in DecisionRules
We want to show you how you might be able to tackle the problem of dynamic pricing using DecisionRules to
- Create and manage different pricing strategies
- Leverage the information you have about the pricing of your competition
- Use data gathered using data scraping services
- Adjust your pricing strategy based on any variables as you see fit
For this purpose, we have created a dynamic pricing model to showcase one of the possible solutions.
Specific Pricing strategies
Dynamic pricing might be considered a blanket term for many particular pricing strategies that share some similarities. As there are an infinite number of possible variables based on which we might create our prices, there are also infinite possible pricing strategies to choose from. For your model, we will choose a subset of the most common strategies that are implemented and do not require terabytes of data and an analyst for each product's performance. The model is designed in a way in which creating a new strategy is as simple as creating a simple table, therefore should you want to experiment with your own more complex rules, the model will allow you to do so easily.
The implemented strategies are:
Cost-Plus
This is one of the simplest strategies, which tries to price items as low as possible, while still retaining a preset margin. It takes into account your total cost and to create a final price it adds your predefined margin, in order to create the lowest feasible price
Competition Matching
A big draw to dynamic pricing is the possibility of keeping your prices competitive. This strategy allows you to match the current prices of your selected competitors; you no longer have to manually reset prices whenever a competitor's product goes on sale
Relative Positioning
Similarly to Competition Matching, this strategy allows you to follow the prices of your competitors but remainlower or higher by a set percentage. This is a strategy for products for which you do not want to follow competitor’s prices exactly because you either want to be cheaper or your product has other advantages, that allow you to maintain a higher price
Absolute Positioning
Similar to Relative Positioning, but the price difference is a preset value, not a percentage
Goal oriented
If you want to sell a certain amount of products over a period of time, this will be your strategy of choice. The strategy is designed to look at your goal sales for the product and lower the price periodically, should it be selling too slowly to reach your goal
Change oriented
This is a strategy that compares the sales of a product over the previous period and the current one. It tries to increase the sales or maintain the current level of sales by adjusting the price according to the development of the current sales curve.
Stock oriented
A strategy that takes into account how many units of an item are in stock. A typical use for it might be to lower the price of an item that you have overstocked or increase the price of an item that is close to being sold out.
For any of your products, you can choose a fitting strategy that would align with your goals.
Smart Rounding
An undisputed part of modern pricing is the rounding (up ro down) of prices. Surely you have heard of how an item that is priced at $19.99 feels much more like a $10 item to a customer than a $20 one, regardless of being just one cent shy of it. In our model, we offer you an option to use several rounding features
- Setting prices to the nearest .99
- Setting up the number of significant digits - 19999.99 does not look as appealing, 19900 might be a better option for you
- Setting up which number the prices can end in - After calculation, a $3.13 price of either 3.15 or 3.19 might look better
- Choosing whether to allow lowering the calculated price to reach a “better looking” price
Conclusion
This article serves as an introduction to the concept of dynamic pricing as such, and an overview of several basic strategies contained within it. In the following article, we will describe how this pricing model can be implemented in DecisionRules, how to use it for your own applications, and which alterations you might want to make to the model to help it fit your needs.
