pricing strategy

An ecommerce pricing strategy is a set of tactics adopted by businesses to determine and adjust the prices of their products and services. Done well, a good pricing strategy can be a very deep science. It necessitates a thorough understanding of various factors such as customer behaviour, competition, market trends, production cost, and profitability, and the pricing varies too, depending on how these factors change every now and then. 

Today, with the emergence of technologies like AI, machine learning and AR/VR technologies, determining product or service pricing has become faster and more seamless.  

For example, businesses can use chatbots to interact with customers and understand their preferences and buying patterns. They can then use this data to arrive at personalised pricing and promotions, thus increasing their loyalty and overall lifetime value.  

Similarly, businesses can use augmented reality to create an immersive product or service experience for customers, thus justifying the higher costs they may have to shell out for buying that product or service.  

A study by McKinsey reveals that 25% of customers are willing to pay a premium for a product or service that offers superior customer experience. 

There are dynamic pricing engines as well, which use algorithms to adjust prices in real-time based on market conditions, competitor pricing, and other factors. Dynamic pricing can help businesses maximise profits by ensuring that the product or service pricing is always reflective of market conditions and competition. 

7 Ecommerce Pricing Strategies  

There are a number of pricing strategies that businesses can adopt. These are largely based on the specific goals and objectives of the business. Once businesses have cracked the model, it can be a significant contributor to sales, profitability and customer loyalty.

  1. Cost-plus pricing

In this, businesses add a markup to the cost of the product or service to determine the selling price. This is a straightforward and easy-to-calculate method but may not account for market demand and competition.

  1. Dynamic pricing

This involves adjusting prices based on real-time market demand, supply, and competitor pricing. Dynamic pricing requires the use of algorithms and software to analyse data and make adjustments in real-time.

  1. Psychological pricing

This involves setting prices based on consumer psychology and behaviour. For example, using odd pricing, such as setting a price at $19.99 instead of $20. This can make the product appear cheaper and more attractive to consumers. In fact, there’s a study by Marketing Bulletin which proves that products that are priced at US $39 outsell those that are priced at US $34 or US $44.

  1. Bundling pricing

This involves offering products or services as a bundle at a discounted price. This can be a way to increase sales and attract customers who are looking for a deal.

  1. Premium pricing

This involves setting prices higher than competitors to create a perception of higher quality or exclusivity. This strategy can be effective for luxury or high-end products.

  1. Price skimming

This involves setting high prices when a new product is launched and gradually lowering them over time. This can be effective for products with a high level of novelty or demand. For example, a study by Price Intelligently indicates that 90% of SaaS companies use this strategy when launching a new product.

  1. Value-based pricing

This involves setting prices based on the perceived value of the product or service to the customer. This requires a deep understanding of customer needs and preferences.

Cracking Amazon’s Successful Pricing Strategies 

When it comes to anything to do with personalisation, including pricing, Amazon is a great example of a brand that has cracked this strategy by miles.  

A Merit expert says, “Amazon’s pricing strategy is multifaceted and takes into account several key factors, including customer behaviour, competition, and market trends. For example, Amazon uses a dynamic pricing strategy, where prices are adjusted in real-time based on demand and market conditions. This allows the brand to remain competitive and respond quickly to changes in the market.” 

Additionally, Amazon uses a bundling pricing strategy, offering discounted prices when customers purchase multiple items together. This strategy helps to increase the overall value of the customer’s purchase and encourages them to buy more items. 

Amazon also uses a psychological pricing strategy, where prices are set just below a round number, such as $9.99 instead of $10. This pricing strategy has been shown to increase sales, as consumers perceive the price as being more affordable. 

Another key aspect of Amazon’s pricing strategy is its use of personalised pricing. Amazon uses data analytics and machine learning algorithms to analyse customer behaviour and purchasing patterns, allowing it to offer personalised pricing to individual customers. This helps to increase customer loyalty and satisfaction, as customers feel that they are receiving a tailored experience. 

Finally, the brand uses a value-based pricing strategy, where prices are set based on the perceived value of the product or service. For example, Amazon charges a premium price for its Prime membership, which offers benefits such as free shipping and access to exclusive content. 

Merit’s Expertise in Ecommerce Data and Intelligence    

Our state-of-the-art ecommerce data harvesting engine collects raw data and provides actionable insights;  

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Our powerful, new scraper engine can gather massive data sets from multiple sites and geographies in real-time so you can stay informed on customer behaviours and market trends. 

Merit’s eCommerce and retail data engine provides a high degree of confidence in insights generated from analytics – thanks to confidence in the data quality and access to enriched data.  

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