![\"History](\"https:\/\/www.teamly.com\/blog\/wp-content\/uploads\/2022\/01\/History-of-dynamic-pricing-algorithms.png\")
<\/p>\nWell-implemented dynamic pricing algorithms have the potential to increase your profits by double-figure percentages. The bigger the company and the more products, the bigger the impact.<\/p>\n
Recent technological advances have made dynamic pricing more accessible and, therefore, more widely deployed than ever before. But it\u2019s not without risks. As much as these strategies can boost revenue and profits, dynamic pricing algorithms can also stain your reputation, alienate customers and cut down your market share.<\/p>\n
In this article we explore everything about pricing algorithms, from how they work and the rewards of successful implementation, to different pricing strategies and the potential risks. It\u2019s a lucrative and controversial approach\u2014whether or not to take the gamble will be up to you.<\/p>\n
<\/p>\n
It wasn\u2019t so long ago that universally fixed prices were a novel concept. For most of human history, transactions have been a combination of haggling and inventing prices on the spot\u2014if there was an advantage to be taken, good business people took it!<\/p>\n
But gradually the world became a much smaller place. Stable and global currencies emerged, consistent and precise manufacturing grew and most industries introduced prices that were fixed, regardless of circumstances and customers. This remains the dominant pricing strategy for most companies today.<\/p>\n
However, despite that, we\u2019re all still familiar with dynamic pricing. Consider air travel and hotel bookings: everyone knows that the price you see right now is always subject to change. That\u2019s why we try to book flights far in advance, before the cheaper seats get booked up. By the same token, some vacationers wait until the last minute, hoping that airlines or hotels will drop cut-throat prices to fill voids\u2014looking to get something rather than nothing.<\/p>\n
Variable pricing has been a mainstay in these areas for decades. What\u2019s changed is the technology and the number of players in the game. Amazon is known to adjust product prices (across millions of items) multiple times per hour. More famously, Uber (and other ride-sharing services) use dynamic pricing strategies which can make the price of trips absolutely unpredictable; Uber\u2019s \u201csurge\u201d pricing has been known to fly up 500% or higher during peak demand.<\/p>\n
What we\u2019re seeing now is an adoption of algorithmic pricing across the broader retail and services industries. To name a few types of business now employing dynamic pricing:<\/p>\n
While this strategically occasionally comes under fire\u2014for example when Uber\u2019s algorithms skyrocket prices<\/a> during crisis events\u2014it\u2019s impossible to deny that, implemented carefully, dynamic pricing algorithms work.<\/p>\n The foundational goal of dynamic pricing is to increase a company\u2019s gross profit compared to manual pricing. An extremely basic example might be a retailer that sells IT equipment. It\u2019s currently selling its computer keyboards at $25; the pricing algorithms find that today, the company\u2019s biggest competitor is selling the same keyboard at $35. Your product is automatically repriced at $30, increasing your margin while allowing the customer to save money compared to the competition.<\/p>\n For larger companies, these sorts of micro-adjustments can happen frequently across thousands of products. With advanced algorithms, these changes can be substantial and arise from less-tangible sources. For example, if the new release of Lonely Planet says Iceland is the best vacation country in the world, the algorithms pick up on this buzz and increase the cost of flights to Iceland accordingly.<\/p>\n This ability to consider explicit and implicit dependencies is a key factor behind the power of dynamic pricing. Dynamic pricing allows businesses to simultaneously capture sales they would otherwise miss (for example, by lowering prices during low-demand) and increase margins.<\/p>\n \u201cPrice fairness\u201d is at the core of customer loyalty. If a company uses dynamic pricing to create \u201cunfair\u201d prices or is seen to be extorting customers (for example, when retailers blew up the price of soap and hand sanitizer in the middle of 2020) it reflects horrendously on the brand.<\/p>\n By taking an omnichannel approach to pricing with dynamic algorithms, companies can understand what\u2019s driving customers, what their concerns or motivations are, what their perceptions are and much more by assessing various touch points simultaneously. Powerful algorithms can consolidate all of this data along with market data to build optimum pricing\u2014and then push these prices to thousands or millions of SKUs simultaneously and as frequently as needed.<\/p>\n This allows companies to deliver optimum prices for both profit and for managing the customer\u2019s perception of the brand.<\/p>\n Companies delivering top-class omnichannel experiences also align regional online prices with those offered in brick-and-mortar stores, demonstrating a consistent value that many brands struggle to maintain. Leveraging this increase in consumer understanding can improve customer trust and satisfaction while still leveraging the financial benefits of dynamic algorithms.<\/p>\n The goal of dynamic pricing is to provide the most profitable price for all your products, based on a wide range of factors, in real-time.<\/p>\n Dynamic pricing algorithms are generally powered by machine learning and artificial intelligence technologies. While these are hugely complex, we can say that these technologies ingest massive amounts of data and use it to calculate the best possible price. This data starts with historical sales & demand data for every SKU, and extends to everything from pricing factors (like procurement costs, competitor prices, marketing spend, and demand cannibalization) to non-pricing factors such as global events or trending opinions.<\/p>\n And these algorithms are working 24 hours a day, sometimes updating prices multiple times per hour across millions of SKUs. Clearly it\u2019s a task that would be impossible (or at least prohibitively expensive and far less effective) with a manual team.<\/p>\n While most of us don\u2019t think about it in these terms, time-based pricing is becoming more and more prevalent in western society. As a rule, this correlates with demand. With ride-sharing for example, the prices are always highest during commuting hours or when bars are closing.<\/p>\n![\"Benefits](\"https:\/\/www.teamly.com\/blog\/wp-content\/uploads\/2022\/01\/Benefits-of-dynamic-pricing-over-traditional-pricing.png\")
<\/p>\n<\/span>Benefits of dynamic pricing over traditional pricing<\/span><\/h2>\n
Maximizing profits<\/h3>\n
Understanding consumer behaviors<\/h3>\n
![\"How](\"https:\/\/www.teamly.com\/blog\/wp-content\/uploads\/2022\/01\/How-does-dynamic-pricing-work.png\")
<\/p>\n<\/span>How does dynamic pricing work?<\/span><\/h2>\n
Examples of dynamic pricing strategies<\/h3>\n
Time-Based<\/h4>\n
![\"Winning](\"https:\/\/www.teamly.com\/blog\/wp-content\/uploads\/2022\/01\/Winning-strategy-for-dynamic-pricing.png\")
<\/p>\n![\"The](\"https:\/\/www.teamly.com\/blog\/wp-content\/uploads\/2022\/01\/The-risks-of-algorithmic-pricing.png\")
<\/p>\n![\"Uncontrolled](\"https:\/\/www.teamly.com\/blog\/wp-content\/uploads\/2022\/01\/Uncontrolled-pricing.png\")
<\/p>\n