E-Commerce Product Mapping

With deeper learning technologies, the "product mapping" procedure includes their characteristics, locates items, costing, and other information across different resources. Product matching is among the most important fundamentals of competitive data. Different product attributes like its title, description, and image are compared to competitor’s goods.

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Some Important Statistics, Facts & Figures

Businesses get motivated to provide cutting-edge solutions to client problems by expanding the e-commerce trends. As per the newest Statista statistics, it is projected that 1.46 billion people have made digital acquisitions in 2015. This number has increased to 2.14 billion during 2021. In 2022, e-commerce is projected to characterize 21% of retail sales worldwide, up from 10% merely five years before. As per predictions, the online market would account for about 25% of retail sales globally by 2025. To offer more advanced services, they include AI or ML tools.

Presently, merchants have become involved in the product matching problem of e-commerce. They use a product mapping system to improve their prices and make that more efficient.

Product Title Matching

Product Title Matching

The title parallel section utilizes machine learning for matching products by gauging how similar their titles are. The method can quickly recognize matching titles even while the comparison strings are extremely different.

Product-Title-Matching

Pricing Comparison

It is familiar to get similar products provided at roughly similar prices. The fact is that one offer standing out may specify that the product is exclusive. It is legal to apply opposite of the rule. The price distribution analysis recognizes similar offerings.

Pricing-Comparison

Image Similarities

The same fundamental idea inspires image similarities and title similarities. Analyzing visual similarities is used for finding similar products. Image similarities is most problematic when there aren't sufficient identified data on the products. Moreover, the viewpoint, brightness, color temperature, and other characteristics of the similar product photos might differ.

Image-Similarities
Extracting-Attributes

Extracting Attributes

The technology begins with different data analysis algorithms and measures the product discrepancy degrees. The product category similarity is the base for any product-matching algorithms. There are small variations between matching goods. Brands, color, dimension, model, quality, etc. are some of the examples.

Product Mapping Types

Matching

Closely matching goods are those having same attributes.

Similar

Similar matching goods are almost equal products but vary to some extent from one another because of some factors, like color.

Matching
Product-Mapping-Methods

Product Mapping Methods

Product mapping comprises product matching via manual, hybrid, and automation procedures. At Actowiz Solutions, we have set a hybrid automation procedure and manual data extraction and mapping to get the improved pricing or listing.

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