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Amazon Company’s Algorithmic Pricing Analysis Research Paper


Introduction

The term algorithmic pricing refers to a technology-based practice in which the prices of items sold online are set in a way that attracts many potential customers with the aim of maximizing the seller’s profit. The technique applies dynamic pricing algorithms, which rely on four main types of data. First, it depends on the statistical and probabilistic data of potential customers. Second, it relies on the competitors’ prices in which the seller uses the algorithms for the automatic detection of the lowest prices of substitute products currently offered in the market.

The third factor is the personal information of the potential buyers in terms of their demographics and interests. Last is the seller’s business information, which is the target selling point. Amazon is the largest online company in the United States and Europe. It offers a platform for the seller to interact with potential buyers. In this context, the study explores the pricing algorithms used by the Amazon sellers to increase sales volume, improve their ranking and customer feedback.

Description of Algorithmic Pricing

Algorithm pricing provides online business with increased competitivity, however it also has emerging challenges. Poorly applied pricing algorithms could not execute the desired operations. As a result, they can develop unexpected results, especially in a diverse marketplace flooded with other forms of algorithms such as the case of Amazon. At the same time, the collusive strategy applied by the dynamic pricing algorithms causes damage to consumers (Lindner, 2015).

For instance, several individuals have succeeded in using the algorithms to implement a price-fixing strategy. The main challenge is that the regulators and the public do not have the knowledge capacity to control the prevalent behavior of using algorithmic pricing by strangers. However, it is important to understand the strategies employed in the algorithmic pricing in the Amazon market and the extent of the prevalence of their strategies (Taft, 2014). The effective use of the strategies has improved Amazon’s customer experience over the years.

The main aim of using the algorithmic pricing technique is to ensure that products are given priorities in the Amazon landing page. The algorithmic pricing allows sellers to compare their prices with those of their key competitors before setting their prices. That way, they will list their products at prices that will attract a large number of customers. The description of the product, its advantages, and other beneficial details will also act as precipitators of large traffic to an Amazon listed product (Rey, 2015). With a large number of potential buyers, the possibility of increasing their sales volume is high.

The algorithms used for setting prices of individual products in Amazon change frequently and drastically. The math behind the algorithmic pricing is hidden from the public (Taft, 2014). Nevertheless, it has vast effects on the customers’ perceptions and decisions to buy products. The company has more than 300 million customers who actively visit and purchase products from its website. It uses an algorithmic pricing strategy to allow retailers to interact and sell their products to customers.

In this context, the algorithms have been used to shape the marketplace for sellers in Amazon (Lindner, 2015). The use of algorithmic pricing strategy is exhibited on the website through the “Buy Box” button, which pops initially as a recommended purchase. It is the most valuable feature of algorithms in the current internet marketing used on Amazon.

The technology ranks all sellers of a product category in terms of their prices and shipping. Algorithmic pricing appears to be the essence of the customer-centric strategy used in Amazon. As a result, products linked to Amazon have a higher ranking with a huge volume of sales (Rey, 2015). The inclusion of shipping in the product details gives products undesirable ranking. It is essential to note that the algorithm which selects products into the Buy Box button depends on various aspects beyond the pricing. Many customers developed trust in Amazon because it offers products at considerably great prices. In addition, it offers a vast selection of products, excellent customer services, fast and free delivery of the purchased product (Taft, 2014).

The algorithmic pricing technique considers all the above components during the product listing (Lindner, 2015). The algorithmic pricing is customer-centered and it awards the Buy Box button to the seller whose products in that category have the lowest price. It is important that a seller has the listed products in the store and can deliver it when needed. In order to increase their probability of getting the Buy Box for their products, sellers are currently paying Amazon to store and ship their products through a program known as Fulfilled by Amazon (Taft, 2014).

Analysis and Critique

The analysis of Amazon’s algorithmic pricing strategies is based on the concept of the Information Economy. The concept emphasizes the increased use of information to transact business activities. In this context, the primary material to facilitate economic activities is knowledge-based information. The theory of Information Economy promotes the convergence and integration of various communication aspects through data processing technology and information technology to conduct business (Taft, 2014).

Through the IT and internet technology, the emergence of e-commerce in the economic realm has enhanced the application of Information Economy theory. Through e-commerce in platforms such as Amazon, sellers and buyers use digital information to interact and transact businesses. In that sense, knowledge-based information becomes the primary material through which websites such as Amazon promote business operations (Villasenor, 2015).

The analysis of the Amazon pricing techniques using algorithms provides a diverse knowledge of the concept because of two main reasons. First, Amazon is the largest online company in the United States, Europe, and other parts of the world. Second, the company offers specific APIs designed to enhance algorithmic pricing (Lindner, 2015).

The main feature of the pricing algorithms at the Amazon website is the Buy Box feature. It determines the sellers who feature on the landing page of the product. The chosen company becomes the default seller of the product on the Amazon website. In addition, customers use the Buy Box feature to select and add the purchased products to their shopping cart (Taft, 2014). The algorithmic feature relegates the unselected sellers to a separate web page. It plays a critical role in the successful sales at the Amazon, even though the exact feature and weights applied by the Buy Box algorithms are not identified (Dewey, 2015).

For that reason, it is important to develop a comprehensive understanding of Amazon’s Buy Box algorithm. Companies that sell their products on Amazon can choose this dynamic pricing strategy to make the best use of the website. That way, they increase their chances of being given the first priorities by the algorithms. In order to understand the pricing algorithms used by Amazon, it is important to treat the target price of every product differently (Villasenor, 2015).

In order to provide a comparative examination of the business practices between sellers who use algorithms and those who do not use them, it is essential to assess the four seller level features (Taft, 2014). These include the products’ lifespan, the size of inventory, feedback level, and ranking of the products on the seller page. In terms of the product lifespan, the analysis is done based on the first time a product is offered in Amazon to the last time it is withdrawn from the website (Villasenor, 2015).

Sellers who use algorithms to attract customers to their products take longer periods than those who do not use algorithms. It explains why the seller who uses the algorithmic pricing technique in Amazon realizes high sales volume. Therefore, a longer lifespan of their products and services implies they have larger inventories (Rey, 2015).

Notably, algorithmic sellers sell a smaller number of unique products, which means these companies specialize in relatively fewer products. It can be argued that they focus on products they can get in bulk at wholesale prices (Vanni, 2016). Customers who buy products from Amazon rate their sellers based on Amazon’s 0-5 scale. In addition, they provide feedback through a feedback platform ranging from zero to 100 for a seller on the New Offer page.

Sellers with insufficient feed are not displayed in the sellers’ statistics. Sellers who use algorithmic pricing have higher cumulative positive feedback compared to the non-algorithmic pricing users. The former has significant advantages in terms of feedback compared to the latter (Villasenor, 2015).

Customers who use algorithmic pricing to win the Buy Box many times create a self-fulfilling cycle. The platform seems to give sellers an opportunity to reach customers. Once they have won the Buy Box, they will accumulate higher sales than their competitors. In addition, they will still keep the Buy Box because of the ongoing higher sales and more customer feedback (Rey, 2015). The sellers can then decide to increase their prices and that might not affect their sales.

That aspect is unfavorable for the new sellers who might want to use algorithmic pricing to be listed and win the Buy Box. The observation explains why algorithm sellers charge their products higher. Once they have acquired a large number of customers, they will use the Buy Box they had won to retain them. As a result, customers still buy more products of the old sellers in Amazon than those of new companies selling at lower prices (Taft, 2014).

Conclusion

An algorithmic pricing strategy is an effective approach in stiff completion where many companies offer the same products. It helps the seller to set the prices of products to values that will be reasonable to customers. Although it can help a seller to increase sales volume, algorithmic pricing can be a disaster when everyone is using it. Certain sellers can lower prices to unreasonable values with the sole objective of diverting customers’ attention from the substitute products. Because of the inadequate security of the algorithmic system, untrusted users might manipulate the algorithms to create prices, which favor their products only.

To ensure the appropriate use of algorithmic pricing strategy in Amazon, certain issues need to be addressed. Amazon must set and control standard prices for every product category so that the lowest or the highest price is not extremely different from the set prices. That way, every seller will have a fair competition ground. In this sense, customers will rely on the sellers’ information apart from prices to choose products and services. Setting standard prices with small fluctuation margins using the algorithmic pricing system will protect customers who will now base their decisions on quality and selling tips other than prices.

References

Dewey, C. (2015). What you don’t know about Internet algorithms is hurting you. And you probably don’t know very much!. The Washington Post, 5(89). Web.

Lindner, M. (2015). Global e-commerce set to grow by 25 % in 2015. Internet retailer, 500(197). Web.

Rey, D. J. (2015). . CNB, 2(1). Web.

Taft, D. K. (2014). . eWeek, 5(27). Web.

Vanni, O. (2016). The truth behind pricing algorithms in the Amazon’s marketplaces. BostInno, 5(1). Web.

Villasenor, J. (2015). In defense of algorithms. Future Tense, 1(3). Web.

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IvyPanda. (2020, October 3). Amazon Company's Algorithmic Pricing Analysis. Retrieved from https://ivypanda.com/essays/amazon-companys-algorithmic-pricing-analysis/

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"Amazon Company's Algorithmic Pricing Analysis." IvyPanda, 3 Oct. 2020, ivypanda.com/essays/amazon-companys-algorithmic-pricing-analysis/.

1. IvyPanda. "Amazon Company's Algorithmic Pricing Analysis." October 3, 2020. https://ivypanda.com/essays/amazon-companys-algorithmic-pricing-analysis/.


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IvyPanda. "Amazon Company's Algorithmic Pricing Analysis." October 3, 2020. https://ivypanda.com/essays/amazon-companys-algorithmic-pricing-analysis/.

References

IvyPanda. 2020. "Amazon Company's Algorithmic Pricing Analysis." October 3, 2020. https://ivypanda.com/essays/amazon-companys-algorithmic-pricing-analysis/.

References

IvyPanda. (2020) 'Amazon Company's Algorithmic Pricing Analysis'. 3 October.

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