Background: Dynamic Price Optimization
We compiled background information on intelligent dynamic price optimization in omnichannel retail for you. We explain central concepts and approaches and how our AI-based pricing solutions come into play.
We compiled background information on intelligent dynamic price optimization in omnichannel retail for you. We explain central concepts and approaches and how our AI-based pricing solutions come into play.
What is dynamic price optimization?
From rule engine to intelligent pricing
Which approaches does prudsys use for dynamic price optimization?
What does price elasticity mean?
Which pricing factors are particularly relevant?
Why is it important to have a global pricing strategy?
What target KPIs can be optimized with intelligent pricing algorithms?
How are couponing and pricing related?
What is the role of artificial intelligence?
Which opportunities does dynamic price optimization offer for your company?
Dynamic price optimization (also called dynamic pricing) means that you, the retailer, adapt your product prices on a regular basis using an algorithm based on current market need. Prices are then generated automatically or semi-automatically. Your pricing solution also observes all relevant context conditions including demand, stock and competitor’s prices and adapts your item prices to maximize the success of your pricing strategy.
Even the local corner store had “dynamic” prices: for example, bread was marked down in the evening so that it would sell. However, since then four things have changed:
Intelligent pricing helps you set competitive prices on the basis of supply and demand, promote healthy price development and avoid price distortions.
Retailers use system-based, rule-based pricing based on so-called rule engines as a precursor to intelligent pricing. The rule engines statically implement established pricing rules. For example, they set the price based on current competitor prices plus or minus x percent. However, the rules are firm and do not adapt intelligently to changes in the context conditions. They also provide no basis for active pricing and instead react only to external factors such as the competitor’s price. Of course, that can easily lead to price distortions when retailers are constantly underbidding or overbidding each other.
Rule engines are a precursor to intelligent pricing. However, growing product ranges and the increasing speed of market changes mean that rule engines are quickly overwhelmed.
Dynamic pricing solutions, on the other hand, use intelligent algorithms to maximize the KPIs of your pricing strategy. The algorithms adapt thousands of product prices completely automatically to customer behavior as well as to constantly changing market and corporate situations. They react to changes in influencing factors in real time and are constantly learning.
The calculated prices can either be displayed directly in the branch store or in the online shop (keyword: automated pricing) or serve as a template for category management to check the prices once more prior to generating them (keyword: semi-automated or strategic pricing). In reality we often see mixed forms, e.g. automated prices for products with minimal competitive relevance and price recommendations for extremely competitively relevant and price sensitive products.
Read our blog article (in German) if you want to know more about the different “stages of evolution” regarding the automation of pricing processes and types of pricing tools.
Dynamic price optimization methods can be applied to your entire product range. Within your product range, we distinguish between different groups of items, each placing different demands on the respective pricing algorithm.
Item group | Demand | Approach | Use case |
---|---|---|---|
Items with extreme competitive relevance and price sensitive items (focus items) | Maximization of sales, turnover and earnings as well as development of a positive price image | Strategic pricing, semi-automated pricing, price optimization for articles | Increase turnover and earnings with intelligent price optimization |
Items with minimal competitive relevance (basic items) | Automation of pricing processes and maximization of earnings | Strategic pricing, automated pricing, price optimization for articles | Increase turnover and earnings with intelligent price optimization |
Items with minimal competitive relevance and slow-moving items (long tail) | Automation of pricing processes and maximization of earnings | Strategic pricing, automated pricing, price optimization for articles | Optimize the earnings of your long tail products |
Product ranges with equivalent or exchangeable product alternatives | Automation of pricing processes, Promotion of sales and maximization of earnings | Automated pricing, price optimization for articles | Take advantage of cross-price elasticities and maximize your earnings |
Items with limited life cycle (e.g. fresh items in food retailing) or items with quickly deteriorating value (e.g. seasonal items in the fashion business) | Stock optimization and earnings as well as reduction of markdowns | Stock optimization, markdown Pricing | Reduce markdowns for fresh and seasonal items |
To find out more about the different approaches, read the blog article (in German).
Price elasticity indicates how demand for an item changes when the price varies. It may be derived from the price-sales function.
prudsys enriches the calculation with further factors, which are relevant for each article, e.g. competitor’s prices, relevant attributes of the article as well as real-time and historic transaction and sales data. The prudsys pricing solutions calculate complex sales functions for each item and at any given time (keyword: real time). Intelligent algorithms then derive the price which is most in line with the market at that actual time.
You can read about the factors that influence price and sales under the key word pricing factors.
Prices depend on a number of factors. The following factors have emerged as particularly relevant from our experience with numerous projects:
The quantity makes it clear: effective price optimization can no longer be managed manually in a volatile competitive environment.
You will have the most success with dynamic price optimization if you have defined a differentiated pricing strategy that defines and prioritizes exact target KPIs both globally and for the various item groups. Based on your KPIs we select the algorithms to optimize your prices. Of course, during implementation the KPIs serve as parameters for the success of the pricing method.
We would be pleased to assist you with strategy development. We analyze your historical sales data, calculate the complex sales function of your items, define common item groups and analyze the extent of the contribution individual items make to your turnover and earnings.
Intelligent pricing algorithms optimize your prices, maximizing the success of the KPIs previously defined in your strategy. For example, pricing solutions optimize the following KPIs:
Our specialists would be happy to set up an appointment with you to go over which dynamic price optimization methods would best suit your pricing strategy.
A personalized coupon is a customer-specific discount calculated by the self-learning decisioning model of the prudsys RDE on the basis of the sales function. Intelligent couponing, that relies on artificial intelligence (AI), is increasingly the method of choice when it comes to increasing purchase frequency and customer retention.
Why? Static discounts and coupons as we still frequently find in our mailboxes result in customers becoming habituated and reducing your earnings. For example, with such coupons and discounts, even customers who would have bought without the discount still get a discount or they get a (too) high discount even when they would have purchased at a lower discount. The goal, therefore, is to use your resources more strategically while keeping an eye on your margin.
Combine individual product recommendations with attractive discounts and increase purchase frequency as well as customer satisfaction.
In addition, with intelligent couponing you also benefit from cross-selling and up-selling potential. For example, generate discounts for your customers for products that they have never purchased from you but that would match their purchase behavior. Find out more about couponing in our use case.
In an age of big data, digitalization and a highly dynamic market, it is no longer possible for humans to adequately control the variety of influencing factors on the price. This is where artificial intelligence in the form of self-learning algorithms comes into play. These algorithms calculate the optimal price completely automatically for any item at any time. That doesn’t mean that your prices change on a second by second basis. You determine the frequency of the price adaptations for your sales channels. Thanks to real-time calculation, you always have the optimal price for your products when you adapt your prices.
The AI takes over the calculation: What is the fair market price of an item taking into account all of the pricing factors as regards optimizing your KPIs? Your category management sets the framework and dictates to the algorithms what to do.
If you would like to know more about the math behind our pricing solutions, we recommend pages 15 to 18 of our Whitepaper on Dynamic Pricing.
With dynamic pricing you can optimize your individual KPIs that you have defined in your pricing strategy. For example, you can increase your earnings, earn more gross profit per item, strengthen your price image on the market and expand your market share. You avoid price distortions and offer your customers prices in keeping with the market at all times.
At the same time, automated pricing and price setting relieves your category management division. This gives you more resources to take even better care of your focus items and elementary strategic tasks for which you have had too little time during the day to day business.
Our pricing solutions automate the pricing processes for your entire product range, taking into account all relevant pricing factors. Our intelligent algorithms calculate fair market prices, even for extremely large product ranges in real time. This task could not be completed manually. Your pricing strategy and the KPIs defined in it determine what algorithms are used. They automatically generate the prices for you directly to your sales channels or send price suggestions to category management for checking. This way you have more freedom for other important strategic tasks and ensure your competitiveness in a highly dynamic market environment.
If you wish to dive deeper into the topic of dynamic prizing, we recommend our free white paper to you. Find out what you as a retailer may gain by using dynamic prize optimization and which retail use cases are promising. The white paper also explains the technical basics of dynamic pricing and addresses central issues of customer protection.
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