With the digitalization boom, dynamic pricing gained much more prominence in the business world. And the inception of technological innovations made the adoption of multiple dynamic pricing methods an inevitable phenomenon. Brands were able to maximize their profits by plugging revenue leaks that were caused due to incorrect pricing. It also enabled them to improve their operational efficiency, increase product assortments and create satisfactory customer shopping experiences.

Smart, dynamic pricing boosted the sales momentum and opened another pricing dimension. Companies and brands like Uber, Amazon, Airbnb and Google latched onto this new pricing strategy and saw tremendous boosts in their sales. And pricing managers could design high-revenue yielding pricing strategies that were only possible with the support of dynamic pricing.

In today’s blog, we are going to understand two of the most widely used dynamic smart pricing strategies – Rule Based Pricing and AI-Powered Pricing. Upon analyzing the pros and cons of the two, companies will be able to pick the right one for their business. 

Rule-Based Pricing

Rule-based pricing is a dynamic pricing strategy that sets specific rules based on which prices are constantly optimized. These are usually ‘If and Then’ statements fixed by pricing managers. For example, if the competitors’ price goes up by 6%, then the product price should be increased by 8%. Other rules include rounding off prices from 0.5 or 0.9 to 5% or 10%. 

This dynamic pricing strategy is often used by e-commerce websites, the airline industry and the foods and beverages industries. Even though it is a dynamic pricing strategy, it uses the basic rules of static pricing.

One great example of a rule-based pricing dynamic pricing solution is BRIO. This AI-powered pricing tool comprises of 3 modules – 

  • Module 1 uses competitive intelligence 
  • Module 2 focuses on rule-based pricing strategies
  • Module 3 This uses Artificial Intelligence to design agile pricing strategies.

With just a few clicks, retailers can set the rules, and the prices of their products will be changed according to them. This machine does nearly 5 BILLION optimizations daily and refreshes the prices every 10 minutes. The rules are set, and all retailers have to do is feed the correct prices into the system, and it will optimize the prices accordingly.

Rule-based pricing strategy helps pricing managers control their dynamic prices. These rules are already set in the automated machine-learning tools. Now that we have understood a rule-based pricing strategy let’s look at its pros and cons.

Pros 

  • Rule-based pricing is one of the simplest dynamic pricing strategies. It minimizes errors and helps pricing managers make better pricing decisions.
  • This dynamic pricing strategy enables experts to make use of their pricing experience in a controlled manner.
  • Strategies designed by humans can be directly coded in the system.

Cons

  • Since the rules are preset, the machine can only change the prices when there is much more scope for generating revenue with a different strategy.
  • It cannot study data and change prices according to market fluctuations or a change in customer behavior.
  • The rules can become outdated and must be updated according to market fluctuations.
  • Price changes are much slower than an AI-powered pricing strategy.

Which Industries Should Use Rule-Based Dynamic Pricing?

Industries that do not see massively aggressive market fluctuations should apply rule-based dynamic pricing strategies. The best example would be luxury brands, which usually have a much more stable market. Also, if a pricing manager is highly experienced and is confident enough to set fixed rules that will bring in higher revenue, they should go for rule-based pricing. But with today’s technological advancements, machines are becoming much more proficient and should be utilized for tasks like pricing. Machine learning and artificial intelligence are able to study market movements with speed and accuracy, thus allowing companies to make swift changes in their prices. Companies whose competitive prices don’t change often should go for Rule-Based Dynamic pricing. If a company sees fast market movements, then this type of pricing strategy is not for them.

Now that there is absolute clarity about Rule-based pricing, we shall dive deep into understanding pricing powered by artificial intelligence.

AI-Powered Pricing

Artificial Intelligence has taken dynamic pricing to another level. Its machine learning algorithm gathers, identifies, analyzes, and computes the data and sets prices accordingly. The machine is so articulately programmed that it prompts predictive and prescriptive prices to generate maximum revenue. These prices are decided purely by the machine and do not require any human intervention. It studies customer behavior, market fluctuations and competitor prices and changes the prices up to 3-4 times a day.

That is why sometimes when you create a cart on any E-commerce website and do not complete the purchase, you will find that the price of the cart has decreased. This also happens when you are using Uber to book a cab. As soon as you refresh the page, the price changes and depending on the time of the day, it either goes up or down.

Artificial Intelligence and machine learning enable companies to change prices at the speed of light. Once the machine is programmed with highly intuitive codes, it becomes more capable than a human. One such example is that of Viaje.ai. This AI-powered tool for the travel industry priced and SOLD a ticket for $24 at $121, a feat that is unfathomable for the human mind. The cognitive abilities of an AI-powered tool are unimaginable. After analyzing the data at the granular level, the machine uses its own intellect to provide the RIGHT PRICES.

After comprehending the complexities of an AI-tool, we realize how it has simplified the mammoth task of pricing. Here are the pros and cons of AI-powered Pricing.

Pros 

  • AI-powered pricing strategy requires next to NO human intervention
  • It helps pricing managers save time
  • This strategy eliminates manual efforts 
  • It also reduces the operational costs of large pricing teams
  • Allows companies to scale their business
  • Speeds up the pricing process and al
  • Seasonality effects get auto-considered 

Cons

  • If the machine is not well programmed, it can set extremely low or high prices
  • Some companies do not have the technology to integrate artificial intelligence into their systems.

Which Industries Should Use AI-Powered Dynamic Pricing?

The travel industry sees extreme fluctuations in the market and requires AI-powered pricing tools that help companies keep track of the market and optimize the prices accordingly. 

E-commerce companies like Amazon, Walmart and Best Buy are already using AI-powered algorithms for smart repricing. This means retailers already have a tried and tested method ready to be executed. FMCG brands should also take complete advantage of artificial intelligence when it comes to pricing. 

Even though the airline industry pioneered dynamic pricing, it is unable to use AI-powered pricing. This is because airlines need technological backup to integrate machine learning and artificial intelligence into their systems. This is why we at Sciative are working rigorously to build a system that can be easily integrated into the ticketing system of any airline. Thus enabling the aviation industry to take advantage of AI-powered dynamic pricing.

In Conclusion…

If a company has the technological backing, then it must definitely integrate with an AI-powered pricing tool. And if they don’t, they must strive to upgrade their technological systems to ones supporting artificial intelligence. Retailers with an assortment of hair and beauty products and fashion and FMCG products should use the AI-powered pricing strategy. Companies providing ticketing services in the travel industry should definitely go for an AI strategy as it studies the constant fluctuations in the market and changes the prices accordingly. 

At the same time, rule-based pricing should be ideally used by luxury brands that are quite stringent about their pricing policies and do not require constantly changing prices. 

To know more about AI-powered pricing solutions, book a free demo with us or email our pricing consultants at ayesha@sciative.com.

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