What is Dynamic Pricing and How Does AI Affect it

In a world where information spreads at the speed of light, dynamic pricing is the most effective competitive strategy. It allows you to set the ideal prices for each segment of your target audience or even for each particular customer — prices that will drive demand and generate the maximum possible profit for your company. 

In this article, we will explain how the dynamic pricing system works, its advantages over traditional models and the role of artificial intelligence in it.

What is Dynamic Pricing

Dynamic pricing is a marketing strategy that allows businesses to change prices in real time, adapting them to current market conditions, customer needs and key performance indicators. It requires building a powerful analytics system that allows a company to assess its performance, monitor external factors affecting demand and receive customer feedback.

The very definition of dynamic pricing indicates the competitive advantages of a business. Using such a strategy, a business can attract the attention of its target audience with favorable purchase conditions, effectively use market trends, and maximize its profits without negative attitudes from consumers. But there are always disadvantages to consider: you need to involve considerable resources to instantly respond to market fluctuations and change prices accordingly... or use artificial intelligence.

Fixed vs Dynamic Pricing

Fixed pricing involves setting a tight price that is used for a certain period of time and cannot be changed to reflect market fluctuations or changes in consumer preferences. This strategy implements different methods — the price can be tied to production costs, competitors' policies or the level of demand at a particular moment.

When comparing fixed vs dynamic pricing, the latter comes forward due to its flexibility. It allows you to use all opportunities for your business growth, better maintain inventory management and increase customer loyalty. Still, don't completely dismiss fixed pricing as an outdated model. It also has its advantages:

• simplicity and ease of use, especially for small businesses;
• better relations with conservative customers;
• prevention of "price wars" that can lead a company with an insufficient safety margin to bankruptcy;
• lower resource costs for maintaining the analytics system;
• creating an image of a premium brand that does not waste time on trifles in the competition. 

Role of AI in Dynamic Pricing

AI-based dynamic pricing algorithms may seem very complex, but in reality, it all boils down to a simple mathematical model. The price depends on the demand for a particular product — higher sales mean a smaller share of fixed expenses in the production cost and higher profits. In turn, sales depend on numerous factors, such as current trends, competitors' actions, company reputation, consumer sentiment, etc. The analysis of these factors is associated with difficulties, as it is necessary to identify the relationship between specific indicators and determine their direction and strength. This is the stage of dynamic pricing where AI is applied.

Unlike the human mind, machine learning models are not limited to superficial hypotheses. Thanks to their high computing power, they can check the relationships between all available indicators in the database, even when it comes to hundreds or thousands of variables. By identifying all mathematically significant relationships, they weave them into a complex calculations web that allows them to predict demand levels with 80% to 95% accuracy. 

Moreover, dynamic pricing models based on artificial intelligence can adjust their calculations in real time. Every new indicator in the database, such as another purchase, price changes in competitors' stores and new search engine trends, improves the accuracy of the result.

Although the use of artificial intelligence is a huge step forward compared to traditional hypotheses in analytics, it still has its limitations:

• Sensitivity to errors in raw, unprocessed data. Errors can be related to improper data collection or using limited time periods, such as specific seasons or periods of trendy demand. The accuracy of AI forecasts depends on the quality of the database content.
• Inability to understand the context. Increased prices of competitors may be related to product line updates, and increased sales may be due to the release of a viral video that is not relevant to a particular company. This context is very difficult to describe in numbers what AI can understand, so people should interfere.
• Conflicts with consumers and businesses. Frequent and irregular price fluctuations can be annoying for customers, worsen the company’s reputation, lead to protests from partners, and provoke a "price race" with competitors. Therefore, any dynamic pricing model based on AI requires manual adjustments, such as limiting the frequency of price changes. 

Benefits of Dynamic Pricing with AI

The main advantages of using artificial intelligence are efficiency and productivity. Even the largest analytics service cannot perform billions of calculations within an hour and test all possible hypotheses. At the same time, AI maintenance is cheaper than creating a separate company unit and allocating additional workplaces. This is a double benefit for the company. And this is not the only advantage! Let's take a closer look at what else can be gained from the implementation of artificial intelligence.

1. Increase in income

According to McKinsey statistics, dynamic pricing marketing increases a company's revenue by an average of 5%. This increase does not require significant investments, so a major part of it goes to the business profit.

2. Increase competitiveness

According to the Boston Consulting Group, companies that used dynamic pricing in e-commerce were 70% more likely to achieve their strategic goals in a highly competitive environment. The participants of the study gained a total of $100 million in additional profit.

3. Improve loyalty indicators

Another benefit of dynamic pricing is the ability to win customers’ hearts. Quaxar's surveys show that over 70% of customers have a positive attitude towards personalized pricing. Personalized discounts motivate them to make repeat purchases and recommend the brand to their friends. The Claspo team is actively working on creating dynamic pop-ups that will display individual prices to site visitors in real time. So, subscribe to our newsletter to be the first to know about our innovative update. In the meantime, use our powerful targeting to personalize your pop-ups based on your audience's previous interactions with your brand on different channels and get the first excellent results!

5 Best Examples of Dynamic Pricing Using AI

Dynamic pricing strategies generate tens of billions of dollars in revenue globally. And artificial intelligence plays a vital role in this, making them as efficient as possible. This can be proved by considering several examples. 

1. Amazon

The company was among the first to use both dynamic pricing and artificial intelligence. Every day, it sets new prices for products in the marketplace more than 2.5 million times. According to DZone, this increases its profit by 25%. In addition to regular revaluations, Amazon actively uses promotional codes and special offers. 

2. Uber

This is another example of dynamic pricing based on a very complex AI model that takes into account hundreds of factors. Prices for taxi services in this company can vary depending on the number of cars in the area, demand for taxi services, the presence of competitors nearby and even the weather. Uber has also been accused of having hidden algorithms that raise prices when the smartphone battery is low, although this fact has not been proven. This strategy resulted in an 83% increase in the company's revenue.

3. Delta Airlines

One of the world's largest airlines determines the price per flight mile depending on several factors, including the number of competitors on the route, the average waiting time at the airport and possible flight delays. This allows them to find a balance between revenue and customer loyalty. The transition to dynamic pricing allowed Delta Airlines to increase its profits by 8% compared to the old pricing model.

The peculiarity of this example is that the company does not hide the mechanism of such a system and actively listens to its customers. 

4. Airbnb

This short-term rental service is also a notable example of dynamic pricing. It sets recommended rates based on the seasonal demand, prices of nearby neighbors, dates of various events and even the forecasted air temperature. According to the company's representatives, this approach increases the conversion rate by 4 times and increases profits by 5% on average. At the same time, Airbnb only recommends the use of pricing automation tools. It does not insist on their use — users are free to choose.

5. Tampa Electric

Another interesting example is Tampa Electric. This utility company relies on physical devices in its dynamic pricing strategy. It receives data from digital meters, thermostats, electronic controllers of heavy equipment, etc., then raises prices for those who use energy uneconomically during peak demand hours and lowers them for consumers who turn on appliances at the right time. It's not about profit but the opportunity to save up to 87% on utility bills.

Dynamic Pricing AI Tools

Artificial intelligence for dynamic pricing does not necessarily mean a billion-dollar supercomputer that only giant companies like Amazon can afford. Commercial AI can be represented by publicly available web services with inexpensive subscriptions. We will talk about popular tools for dynamic pricing.

1. PriceFX

This service offers solutions of any level — from analytics and recommendations to full automation and feedback collection. PriceFX offers ready-made AI models for various industries such as e-commerce, car sales and service, agriculture and even oil production.

According to the company, its software reduces the time to update prices by 90% and increases the conversion rate by 25% on average. 

2. Vendavo

A complex solution for dynamic pricing and analytics that allows you to prioritize strategic goals. You can focus on maximizing profits, winning the competition or customer loyalty. Vendavo is primarily focused on the B2B segment, but developers are ready to work with B2C companies to create personalized products for them.

3. Competera

This dynamic pricing service emphasizes analyzing market conditions and studying competitors' activities. It is suitable for working in "tight" segments where the slightest price fluctuations can significantly change the level of demand. Competera has many ready-made solutions for integration with popular software. 

Conclusion

Dynamic pricing is a modern marketing strategy that is effective in competing, attracting customers and improving financial results. It has been used for many years by the world's largest companies, including Uber, Airbnb and Amazon. However, it can also be successfully implemented by small and medium-sized businesses by connecting web services based on artificial intelligence.

While we at Claspo are still working on the dynamic capabilities of our best site widgets, you can already use them in conjunction with the specified AI tools. For example, suppose your AI has predicted the demand for a particular product in the coming weeks. In that case, you can create a pop-up with a special price for it in a few minutes in our simple editor and place it on your website during the specified period to maximize profits. Meanwhile, you can start with our free plan and get the first results without spending a penny.