Product Matching for Price Comparison
With today’s online retail scale, there is no product matching without proper product-matching software. Product matching itself is the process that identifies products, their attributes, prices, and other features across different resources using deep learning technologies.
One of the most important aspects of competitive data is product matches. Matches are made when attributes of a product (e.g. picture, product title, product description) are compared to products that other retailers sell.
In highly competitive markets consumers judge a product's value based on competitors' prices for the same or equivalent goods. And big industry players apply competition-based pricing strategies to ensure their positioning, long-term competitiveness, and price perception.
Competition-based pricing enables retailers to use smart pricing in order to stand out from other competitors, their assortment, promo, and pricing strategies. For that reason, retailers may use product matchings on an ongoing basis to program finding equivalent products in other web stores and then process data about SKUs’ prices to decrease or increase them in line with the market.
The Types of Matches
When enough attributes are determined to be the same, they are considered a "match" and are collected to be used to compare a retailer with market peers in regard to prices.
Two main types of product matches:
How are matches made? Two main methods:
Manual vs. Automated Matching Accuracy
Together, automatic and manual matching can be used in conjunction as a developed hybrid matching process. Using both manual and automatic matching together can create a large assortment of very accurate product matches.
Why do retailers need product-matching software?
The need for accurate product matching is a challenge retailers can tackle using relevant data and ML to process it. Healthy competitive pricing data and a high-quality dataset are what every retailer needs to make the best use of product matchings and maximize the value for the business. However, there’s no silver bullet. The best way to find a suitable product matching approach is to experiment with manual, code, and ML matchings to understand which specific combination of these approaches aligns best with your business needs and resources.
Importance of product matching in ecommerce:
Understanding assortment overlap
Ensure your catalog has the right amount of differentiation while still meeting parity with competitors
Whether updating prices manually or through automated pricing optimization tools, keep your price position aligned with strategy and sales/margin targets
Inventory/availability – stock status at competitors
Make more informed marketing decisions on price and promotions based on availability in the marketplace
- Create a unified source of product data
How other matching methods can fall short
Several factors can severely impede the product-matching process. The most common issue revolves around the accuracy of matches. Certain industries and categories of products are harder to make accurate matches for than others.
For example, laptops, which are usually always sold with the same product description, picture, and title, have high matching accuracy rates – even with automatic matching, accuracy can be as high as 90%. However, in other categories that are often sold under differing titles, descriptions, and pictures, matching accuracy falls to rates as low as 30% via automatic methods.
The issue of accuracy in regard to matching can severely impact the rest of the pricing process.
If companies are selling 50 thousand products that are priced using competitive data that has a matching accuracy rate of 70%, 15 thousand products are likely to be priced incorrectly. This is why in our product matching process, accuracy is the highest priority when providing businesses with competitive data. Through a combination of manual and automatic matching, Competera’s product matching software provides an accuracy rate of up to 98%.
140,000 data points with an accuracy rate of 98%
Retailers equipped with accurate product matching ecommerce data such as ours can make drastic improvements in their pricing strategy. RDE found out the benefits accurate data has to offer using 140,000 data points from Competera.
80% sales growth in two months
Previously, RDE’s’ in-house product matching process was tedious, required numerous excel sheets, and often needed time-consuming rechecks due to errors. Using Competera’s competitive data, their pricing strategy was optimized according to market demand more accurately, resulting in an 80% metric growth in sales in just two months.
Together, automatic and manual matching can be used in conjunction to create a hybrid matching process. Using both manual and automatic matching together can create a large assortment of very accurate product matches.
Benefits of Product Matching
Product matching provides many advantages in today's data-driven environment where retailers are expected to keep ahead of the curve in real time. It benefits retailers by:
- Organize the listings on a platform for a marketplace
- Find any discrepancies or missing details in the product catalog
- Combine different product data from several sources into a single source
- Compares competitors' product life cycles
- Implement a framework for product data quality to ensure the accuracy of the data
Given its importance, the majority of product matching solutions try to make it accurate but fall short due to human errors that lower the quality of the data. For instance, the majority of sellers disregard Amazon's instructions on how to write product catalog descriptions. The majority of products lack a UPC, and others are unbranded, making it challenging to classify them. Retailers use their own IDs, descriptions, and attribute names in the absence of clear standards.
How Product Matching Changes the Game
Product matching is a challenging process for businesses of all sizes because of the ever-growing wealth of assortment across stores and marketplaces that can be described on the site in different ways, whether mentioning a color, size, and other features or not. Therefore, retailers have to continuously update their dataset and keep it relevant.
The bigger the share of correctly matched products, the better data quality. The opposite can lead to numerous issues from incorrect new prices calculation to negative shopper experiences.
Complete and accurately matched data help retailers keep up their paces and get better results in the following processes:
- 1. data-driven assortment optimization
- 2. fast and effective decision making
- 3. product performance evaluation
- 4. enhanced consumer targeting
- 5. price and promo optimization
Competera for product matching
Competera offers a unique technology blend make pricing process easy and effective.
Our elasticity-based portfolio pricing is driven by demand patterns, non-linear dependencies and products cross impact — calculating 20+ internal and external factors which guarantee gross margin.
No more manual analysis of outdated competitor pricing — our self-learning competitive data platform provides real-time access to all of your competitors’ prices with the matching quality of up to 98% accuracy.
Unlimited scale & usability — our user-friendly dashboards and personalized analytical reports are easy to use for merchants and pricing managers and can be scaled to an unlimited number of products and categories.
Experience the benefits of high-quality matches
Try out Competera’s competitive data to experience how high-quality, accurate product matches could revolutionize your pricing strategy in the retail market