How to Do Price Comparison and Implement Dynamic Pricing for a Successful E-Commerce

Are you in the e-commerce business and want to stand out? Then, you should know that price comparison and dynamic pricing are essential to success. But what’s the basis of them? The key to successful price comparison and dynamic pricing is product matching algorithms.

Let’s discover how you can sell more by explaining the main approaches to product matching (text semantic similarity and product image similarity), the importance of automatic price updates and how to do them effectively.

Product Matching Algorithms for Price Comparison

We use product matching algorithms to compare products to find the best match for a given customer.

These algorithms take into account factors such as price, quality, features, and more. By taking all of these factors into account, product matching algorithms can help e-commerce businesses provide their customers with the best possible experience.

There are two main approaches to product matching: text-based and image-based.

Text-based approaches rely on the semantic similarity of product descriptions to find matches. Image-based approaches, on the other hand, rely on the similarity of product images. When a product carries a standard identifier such as the EAN, matching becomes much more reliable, and text or image similarity is left for the products where the code is missing.

Keep reading to discover the advantages and disadvantages of these approaches and something more.

Text-Based Approaches

Text-based approaches to product matching are often used in e-commerce because they can be easily integrated into existing systems.

Additionally, text-based approaches tend to be more accurate than image-based approaches. However, text-based approaches also have some drawbacks. For instance, they require a large amount of data to be effective, and they can be slow when dealing with a large number of products.

Image-Based Approaches

Image-based approaches to product matching are less common than text-based approaches, but they have some advantages over their text-based counterparts.

For one thing, image-based approaches can be used with products that don’t have textual descriptions (such as clothing). Additionally, image-based approaches tend to be faster than text-based approaches when dealing with a large number of products. However, image-based approaches also have some drawbacks. They can be less accurate than text-based approaches, and they often require manual labelling of products to work effectively.

The Price Comparison Correct Epilogue: Automatic Price Updates

As we mentioned above, price comparison is essential for the success of an e-commerce business.

To keep up with the competition and ensure that your prices are always competitive, you need to have a system in place for automatically updating your prices. Data scraping is the most common way to do this; by using data scraping, you can automatically collect pricing information from your competitors’ websites and use it to update your prices accordingly.

Today, this loop can be run by AI agents. In WebRobot’s price intelligence vertical, you describe the products and markets you care about, and the agents build scheduled pipelines that collect prices from a self-healing catalogue of sources, match products by EAN and validate the results on real rows before they reach your pricing logic, with human approval on the critical steps. See also price & brand intelligence by EAN.

Product matching algorithms are the basis of price comparison and dynamic pricing logic in e-commerce. There are two main types of product-matching algorithms: text-based and image-based. Text-based algorithms are more common because they’re easier to integrate into existing systems; however, image-based algorithms can be integrated into the process.

Automatic price updates are essential for keeping up with the competition; web scraping is the most common way to do this, and AI agents now make it possible to set it up from a plain-language description. CEO, CTOs, CMOs, and COOs should all be aware of how product matching algorithms work and how they can be used to benefit their business. Thanks for reading!

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