Click here to get this post in PDF
Talking about price optimization, we need to think about how old the business is and its place in its pricing journey. In this situation, picking the correct price optimization model is crucial for a successful business. Now, let’s check out the advanced price optimization software, which uses Machine Learning (ML), and find out five benefits price optimization models offer to businesses and customers.
Understanding the Price Optimization Model
The Retail Price Optimization model is a smart tool specifically built to understand the change in demand at different prices. The results balance the existing costs, inventory, and the best pricing data. Price optimization models are created to maximize profits and make the most out of pricing.
The Intersection of Price Optimization and Machine Learning (ML)
When discussing advanced pricing, it’s important to include things like ML or Artificial Intelligence (AI). At this point, there are a few main connections between price optimization and ML. Let’s look at a couple of them, namely portfolio pricing optimization and individual product pricing optimization.
Individual Products Pricing Optimization
In simple terms, when we talk about price optimization, ML uses math analysis to predict changes in demand. In such a situation, if a company wants to set a right price and make full use of price optimization, it’s not enough to know the company’s goals only. It’s also vital to know some other factors, including how price changes affect demand.
At this stage, the business looks at specific price points to predict how many items from the inventory shoppers buy at different prices. Moreover, while using ML’s smart and accurate algorithms, retailers can maximize their preferred parameters, such as profits, revenue, and sales volumes. At this stage, this method helps to:
- Replicate the real-life market using ML algorithms and choose certain price points within pre-set ranges.
- Provide more accurate sales volumes and predictors for specific price-changing scenarios based on things like revenues and profits.
- Create a list of current competitors that directly affect your pricing strategy and price points.
Portfolio Pricing Optimization
The following connection between price optimization and ML lies in portfolio pricing. In simple terms, retailers must consider all the relationships between products within a portfolio when starting a price change. In some cases, changing prices can hurt the Key Performance Indicators (KPIs) instead of boosting them.
To maximize the KPIs and understand the connection between products in the portfolio, businesses need to analyze lots of data. Price optimization models supported by ML can help do this with a small chance of mistakes. More specifically, it’s possible to use a so-called different pricing recommendation across chosen products. It helps businesses predict the portfolio’s chosen target, which includes things like profit, revenue, and sales volume.
5 Benefits of Price Optimization Models
Now you know how ML works with price optimization models. But, there’s much more to learn. Without further delay, let’s look at these benefits:
1. Financial gains
2. Working with categories at the same time
3. A high level of automation
4. Guaranteed consistency
5. Faster decision-making
1. Financial gains
In short, properly used price optimization helps businesses to focus on certain business goals and prices, resulting in profits. While customers care about the products themselves and not the price. It means that with a good price optimization strategy, you get the price that creates a win-win situation – customers get a high-value product. Plus, you see a sales increase with an immediate financial benefit.
Take the Michael Kors brand as an example. The company used price optimization to set an initial price for its handbags and smartwatches that sold out at the initial price. Without needing to lower the price, the business accurately predicted what customers wanted and made money from that.
2. Working with categories at the same time
With well-planned and executed price optimization strategies, businesses can automatically start effective pricing strategies. In such a situation, when the method works together with the categories, you get unity and consistency. With this in mind, your pricing strategy will perform the best and help you enter the high-level management of category development.
From a category manager’s viewpoint, price optimization is a great way to simplify the complex category management process. In short, the advanced algorithms process lots of data and present methods that help handle the category management process with the highest efficiency and precision.
3. A high level of automation
Automation itself brings higher efficiency and organization of business processes. In this case, automation can help improve the entire optimization process. In most cases, it removes the need for manual work and removes the chance of human error. As a result, with fewer mistakes, businesses can have more accurate predictions and design business strategies that bring value and boost profits.
Automation helps bring accurate price changes. Take Amazon, for example; the company often adjusts its prices many times. In all cases, the business uses price optimization software with a high level of automation to build the most effective pricing strategies. As a result, it brings mistake-free predictions that make pricing the most effective.
4. Guaranteed consistency
Another important benefit of price optimization comes from the factor of consistency. Basically, businesses don’t need to worry about whether the prices are consistent with the market changes and other factors because price optimization uses smart algorithms to adjust pricing strategies accordingly.
5. Faster decision-making
The last benefit is all about speeding up the decision-making process. Because of the automation, management and executives have more time to make decisions that change business operations. It happens because automation makes processes more efficient, which saves time, effort, and resources.
Conclusion
Retailers can use price optimization to improve sales volumes, keep all the margins healthy, and boost profits. Moreover, making the most of algorithms is a great way to improve data management, speed up decision-making, bring forward automation, guarantee consistency, and get immediate financial gains. After all, price optimization is a method based on advanced algorithms and innovative technologies that makes human error a thing of the past.
You may also like: What type of pricing strategies are used during Black Friday?
