Brands and retailers across the globe come to us looking for ways to turn mounds of competitive eCommerce data into intelligent, automated technology that helps them outperform the market. It is the holy grail that can make or break a retail business in the current climate. So how does a simple step like matching products with similar attributes fit into the larger picture?
Every retail technology you can think of runs on well-categorized product datasets. The quality of the product data being fed into pricing engines, marketing automation platforms, and inventory management systems is perhaps the most crucial factor setting leading online retailers apart from the rest. They are able to give frictionless experiences to their customers at every stage because of their ability to accurately match and group identical and similar products.
- Run dynamic price changes & automated promotions more efficiently.
- Optimize product assortments with improved competitive insight.
- Avoid costly overstocking mistakes.
- Visibility from improved product targeting translates to better traffic and conversions.
- Access to product lifecycle data across the market helps you measure true product performance.
Product matching, when done right, builds a strong foundation for advanced retail applications. It is, however, becoming an increasingly challenging process thanks to the ever-growing volume of retail data from diverse sources across hundreds of marketplaces. Despite having universal product identifiers (like UPC, GTIN, or ASIN), there still is no standardized taxonomy for listing products on eCommerce websites. This creates enormous complexities when you need to identify and compare products and prices across multiple websites or when your customers are searching for specific product features. Inaccurate matches can lead to overstocking, pricing errors, merchandising blind spots, and a dismal shopper experience.
Your product matching capabilities can impact 3 major aspects of your retail strategy:
Retail dashboards allow you to monitor and compare your products to those featured on your competition’s website by tracking exact and similar product matches. Your stocking and inventory decisions rely on the accuracy of these matches. Dynamic pricing and repricing algorithms estimate pricing benchmarks based on the volume of identified exact matches. An advanced product matching solution can accurately identify matches inconsistent descriptions across websites, as demonstrated in the example below:
Your promotional strategies are based on your visibility into the competitive movements in the market. If your reports present an inaccurate picture of a product’s market performance you could be leaving money on the table or turning away shoppers hoping to snag a good deal.
With consistent accuracy across both similar and exact product matches, you deliver an improved product search and discovery experience to your customers. This translates to an optimum deal-hunting experience for them. Chatbot performance and the quality of product recommendations on eCommerce websites are tied to better product tagging and categorization, which in turn links back to the efficiency of your product similarity engine.
Over time, product matching can help you align your product descriptions and categorizations based on historical search and sales performance and this will undoubtedly enrich your search engine performance. With the increased popularity of Google Shopping and other price comparison applications, having well-grouped products on your website means consumers are more likely to stumble across your products.
A good product matching engine can grant your retail teams access to a unified, accurate, and scalable data source for product and sales. You can build on a structured categorization system that is in alignment with global standards in product taxonomy, making the data powering your retail strategies much more normalized and competitive. This is the building block for your retail data capabilities.
Most generic price matching and product matching solutions available in the market fail to keep up with the sophisticated algorithms and constantly changing layouts and rules on leading eCommerce marketplaces. While they do a fair job of collecting the product data, the underlying quality issues and ‘matching’ capabilities are left unaddressed. These concerns combined with the absence of real-time data refreshes can quickly become a recipe for retail disasters. On the other hand, well-intentioned internal efforts to create matching algorithms rely on manual data aggregation and are rife with human errors and biases. Limits on the scope and scale of competitive product tracking — both exact and similar matches — further narrow the field of vision leading to expensive, labour-intensive yet myopic retail intelligence.
We at Intelligence Node have improvised and perfected our Product Matching solution to deliver real-time, accurately matched product datasets in configurable formats for your retail needs.
The best semantic and NLP technology would only give you half the picture. Most solutions in the market will not be able to turn a positive match for the same shirt tagged as “Long Sleeve” and “Full-Length Sleeve” on different websites. This is where the nuances of ‘exact’ matches and ‘similar’ matches come in. AI-based Image Analytics can help reduce False Positives and False Negatives significantly, making your competitive insights much more accurate.
We achieve our accuracy by combining an attribute-based approach, AI Computer vision that compares digital images, and a configurable approach to ensure we mirror internal benchmarking methodologies. In scenarios where the confidence scores of the machine-driven matches are low, we have a team of Quality Assurance specialists who verify the output. Plus, we refresh our data as frequently as every 10 seconds so the insights you get are truly real-time and actionable!
Our AI-powered algorithms monitor websites around the world to help you find and compare branded or private label competitor products that are close or identical. With attribute standardization, our patented Similarity Engine ensures unbeatable accuracy and consistent matching performance across both private label and branded products. This also means our solution works just as well for soft categories (like beige bed linen or floral perfume) as it does for attribute-rich categories (like smartphones or toothpaste).
Our accuracy and quality claims are backed by contractual SLAs. See what some of our customers have to say about Intelligence Node’s award-winning product matching technology.
Our Product matching solution is designed to close the divide between users seeking insight and technical specialists in need of business context. With our software, users across diverse retail teams can explore data and publish findings in a way that can be accessed on a broad range of platforms. Moreover, our solutions can be easily plugged into your backend system and get up and running in less than a week. We work extra hard to ensure speedy implementation that mirrors your internal benchmarks. Intelligence Node can tailor its matching algorithm to meet your internal criteria for tracking similar products in your category.
Search engines and marketplaces update their algorithms frequently and it’s impossible to keep up, let alone beat them as an in-house business analytics unit. Machine Learning algorithms get smarter as they train with large and varied Big Data sets over time- and ours have been training with global retail data across every sector for almost a decade now! Our APIs are made to be used across diverse teams so your business can harness data for competitive advantage without becoming a slave to data management and large capital investments. Intelligence Node’s Product Matching solution helps you avoid blind spots and expensive mistakes, save costs, and escape decision paralysis.
Find out how your team can leverage our Product Matching solution to achieve unprecedented retail growth and customer satisfaction. with one of our experts today!