How to Price Like Amazon | eCommerce Matters Ep. 007
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This episode covers how Amazon approaches pricing, what tips you can implement for your eCommerce business and why making data-driven pricing decisions is key to winning your market.
Hosts: Philip Huthwaite (CEO & Founder of BlackCurve) and Rob Horton (Product Director at BlackCurve).
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Full Episode
Podcast Summary
Lockdown Impact on Pricing
During the discussion, the impact of lockdown on pricing was explored in detail. With restrictions in place and people unable to leave their houses for an extended period, the demand for certain products surged. Items such as home fitness equipment, home office supplies, and entertainment devices became highly sought after. This surge in demand, combined with supply chain disruptions and limited availability, led to price fluctuations in the market.
Anecdotes from the conversation highlighted that some products experienced price increases compared to pre-lockdown levels. However, it was noted that the perceived value of these products remained high, and customers were willing to pay the higher prices due to the unique circumstances of the lockdown. The discussion also acknowledged that stock issues played a role in the pricing dynamics, with limited supplies and increased demand contributing to the higher prices.
Amazon's Pricing Strategy and Market Efficiency
The conversation then shifted to Amazon's pricing strategy and the concept of market efficiency. It was noted that Amazon excels in utilising automated tools to manage their pricing decisions. Unlike other digital platforms that may rely on sporadic pricing adjustments, Amazon constantly engages in price testing and updates to ensure their prices are optimised for market conditions.
The importance of striving towards market efficiency was emphasised, and Amazon's proactive approach to pricing was praised. By frequently assessing the market and leveraging automated tools, Amazon is able to stay ahead of competitors and maximise their revenue. The use of automated tools allows them to rapidly make pricing decisions on a mass scale, ensuring that their prices are constantly adjusted based on demand and other market factors.
Advantages of Automated Pricing and Scale
The advantages of automated pricing were discussed in more detail. It was noted that businesses with a large product portfolio can benefit greatly from implementing automated pricing tools. With thousands of products to manage, manually adjusting prices would be time-consuming and inefficient. Automated tools enable businesses to make pricing decisions rapidly, saving time and effort while ensuring that prices are optimised for each product.
An analogy to robo-investing was used to highlight the benefits of automation. Just as making multiple small bets yields better results than relying on a few large bets, automated pricing allows businesses to make numerous pricing decisions across their product range, improving overall performance. However, it was acknowledged that products with unique characteristics or low sales volume may require additional considerations and may not benefit as much from full automation.
The Importance of Data Quality and Analysis
The conversation emphasised the critical role of data quality in pricing decisions. Accurate and reliable data is essential for making informed pricing decisions and avoiding potential pitfalls. Data preprocessing and cleaning were highlighted as necessary steps to ensure the data used for pricing analysis is of high quality.
The use of competitor data and sales history as key data sets for pricing decisions was discussed. These data sets provide insights into market dynamics, competitor pricing strategies, and product performance. However, it was also noted that Amazon utilises additional data sets to support their pricing decisions. Factors such as weather data, web traffic statistics, and search terms were mentioned as predictive indicators of demand that Amazon incorporates into their pricing algorithms. These additional data sets allow businesses to proactively adjust their prices based on factors beyond immediate competitor pricing and sales history.
Conclusion
In summary, the conversation delved into the impact of lockdown on pricing dynamics, highlighting the surge in demand, limited availability, and price fluctuations for certain products. Amazon's pricing strategy, driven by market efficiency and automated tools, was recognised as a successful approach in the e-commerce industry.
The advantages of automated pricing for businesses with a large product portfolio were discussed, emphasising the efficiency and scalability it provides. However, it was noted that products with unique characteristics or low sales volume may require additional considerations.
The importance of data quality in pricing decisions was emphasised, and the need for data preprocessing and cleaning was highlighted. Competitor data and sales history were identified as fundamental data sets for pricing analysis, while additional data sets such as weather data, web traffic statistics, and search terms were mentioned as predictive indicators of demand that can further enhance pricing strategies.
Overall, the conversation showcased the significance of data-driven approaches in pricing and exemplified Amazon's effective use of data to optimise pricing strategies. By leveraging automated tools and a diverse range of data sets, businesses can make informed pricing decisions and adapt to market conditions effectively.