The airline industry pioneered the practice of dynamic pricing in the 1980s. With the evolution of retail from brick-and-mortar stores to e-commerce, dynamic pricing has quickly become a prominent factor that determines the success of online sales. This pricing strategy, also known as Real Time Pricing, reprices products based on consumer insights, market movements and competitive pricing.
Earlier repricing was done manually, but with the advent of machine learning, this job has been handed over to AI-powered automated bots.
Retail brands heavily rely on artificial intelligence and machine learning to determine the right prices for their products. With the ever-evolving fluctuations in the retail industry, changes in consumer shopping behavior and saturation of the e-commerce market, dynamic pricing has become a necessity.
Not only does it help in plugging revenue leaks, but it also ensures that brands are at par with their competitors. It prompts an accurate pricing strategy based on intelligent consumer insights pulled out from every corner of the web.
Evolution of Pricing
Phase 1 – Pricing as an Ad-hoc activity 1760s
Pricing became an ad hoc activity after the birth of the first industrial revolution. Before the 1760s, traders did not consider pricing to be a specialized activity. But after the revolution, businessmen realized that pricing needs to be an ad-hoc activity, making it the first phase of the pricing process.
Phase 2 – Pricing as a Periodic Activity 1970s
Then came phase two, where pricing became a routine activity. The second industrial revolution shook up the market and heavily impacted business operations. Due to technological inventions and advancements, business owners realized the need for dynamic pricing. By the 1970s, spreadsheets were used to keep track of old records, surges in the market and create assumption-based pricing strategies.
Phase 3 – Pricing as a Key Function 2005
By 2005, pricing became a key function. With the birth of automation and digitization, business owners were able to increase their prices once or twice a day with the use of technological advancements. The digital revolution opened the doors to competitive intelligence, consumer insights, and portfolio pricing. Since intelligence tools, rule engines, and automated management tools enabled business owners to focus on Customer Lifetime Value and Brand-Price Trade-off (BPTO).
Phase 4 – Pricing as a Core Trade Activity 2011
And then came Pricing 4.0! By the year 2011, brands like Amazon and Uber had begun full-fledged usage of Dynamic Pricing. With easy accessibility to big data, brands can swiftly analyze customer behavior and set the best pricing strategies for revenue maximization. Predicting shopping trends with high accuracy has become possible, and with the right application of scientific knowledge, pricing has become the core trade activity.
Advantages of Dynamic Pricing
Horses for Course: Dynamic pricing changes the prices of products based on the customers’ needs and willingness to pay.
Maximize Resource Utilization: Resources like cabs are being used to the fullest due to dynamic pricing
Revenue Maximization: It aids sellers in creating high revenue-generating pricing techniques based on competition intelligence
Ensure Availability till the last minute: Real-time pricing ensures that the product can be sold till the last moment.
Types of Dynamic Pricing
With the advent of Pricing 4.0, companies have quickly started adopting the dynamic pricing strategy. As more and more sellers began adopting the strategy, dynamic pricing began branching into different categories. Let’s understand the different kinds of dynamic pricing strategies.
When sellers set the prices of their products or services based on their competitor’s price, it is known as competitive pricing. Customers today have become hyper-aware, which means they check the prices of each product on multiple platforms before making a purchase. They can increase or decrease their prices with the help of competitive pricing. Any products that have close competitors in the market, like Pepsi & Coca-Cola or Tide & Ariel, need to apply the competitive pricing strategy.
Time-based pricing is when the prices of a product change according to the time of the year; this could be a season, week, or month. For example, the prices of flight or train tickets are higher during the holiday season as compared to a normal week. Another great example of time-based pricing is that of winter wear. The costs of woolen jackets will be higher in the winter, while the prices of refrigerators will be higher during summer.
Segmented pricing is when the prices of a product or service change based on different factors like demographics, price sensitivity of the consumer or any other factor depending on the seller’s product or service. One example of segmented pricing is that some items cost higher in certain geographical locations where high-income groups reside. Another example could be that a product costs less online in comparison to an offline store.
End of Product Life
One of the key advantages of dynamic pricing is that retailers can quickly sell products that are perishable or unusable. For example, a food retailer can drastically decrease the price of a food item that is going to perish. This way all the inventory gets sold out.
With the help of dynamic pricing companies can change their prices according to the season. For example, travel companies increase the prices of their tickets during the holiday season. Winter coats and boots are sold at a higher price during the winters whereas refrigerators are sold at a much lower price. This is possible due to optimum technology of dynamic pricing
Companies that use it on a daily basis…
Dynamic Pricing has been a game changer for brands that optimize their prices in real-time. Amazon, the world’s biggest e-commerce giant, performs millions of price optimizations daily. With the backend support of machine learning, Uber monitors the routes, traffic, demand, weather, and other assorted factors based on which it changes the prices of the rides multiple times a day. Sometimes it changes the price of the same ride just a few minutes after you refresh it. Major League Basketball (MLB) uses dynamic pricing to change the prices of its tickets. Airbnb is another great example of a brand that relies on automated pricing strategies rather than using rudimentary methods to change prices. Google uses real-time pricing to monitor the manual auctioning of keywords.
Impact of Dynamic Pricing in E-commerce
Dynamic Pricing was primarily used by the travel industry but soon penetrated other sectors. E-commerce is one such industry that has flourished due to the optimum usage of real-time pricing. With more and more e-commerce stores mushrooming in every corner of the web, setting agile price optimization strategies has become vital for sellers.
With the help of artificial intelligence and machine learning, brands use smart repricing strategies. Automated pricing tools like BRIO are programmed to gather, identify, analyze and predict accurate pricing with 99% accuracy. The AI-powered intelligent bots crawl through the sellers’ as well as their competitors’ websites and accumulate heaps of historical data. This data is then cleaned, organized and analyzed by the automated system, based on which it provides pricing predictions.
All of this is only possible with the help of artificial intelligence, which is why it is crucial for every retailer to get an AI-Powered Dynamic Pricing Solutions…
The lucrative mechanism of setting effective dynamic pricing strategies helps plug revenue leaks and keep up with the competitive markets. Automated bots backed by artificial intelligence make dynamic pricing SIMPLE, SCALABLE, ACCURATE and QUICK!
They help eliminate manual labor, aid in computing pricing decision in microseconds, reduces customer churn and improves accuracy.
To know more about dynamic pricing and pricing strategies backed by artificial intelligence, book a free demo with us or email our pricing consultants at email@example.com.