
How Similar Matching Gave a Bio Cosmetics Brand Competitive Visibility for the First Time
Competitive visibility (private label)
Zero — completely blind on own-brand products → Equivalent competitors identified for every private-label SKU
Market research time
Hours of manual Google searches weekly → Automated monitoring — price changes visible within the day
Pricing confidence (own products)
Guesswork — fixed coefficients, no market data → Market-informed pricing based on real equivalent prices
A French bio and organic cosmetics company operating on Magento. They are both a distributor of known brands (Avène, Bioderma, Nivea) and a manufacturer of their own private-label bio products — nourishing creams, essential oils, natural treatments. Their catalog contains around 5,000 SKUs split roughly between distributed brands and own products. They sell primarily through their own website, with products indexed on Google Shopping via Google Merchant Center.
The Challenge
The company had two distinct pricing challenges. On distributed branded products (Avène, Bioderma), standard competitive intelligence worked fine — MyMarket identified other sellers carrying the same products and myPricing adjusted prices accordingly. But on their own private-label products, they hit a wall. Since they're the only seller of their brand, no competitor data existed. The product pages on Google Shopping showed their listing alone. Yet the actual market was full of alternatives — L'Oréal, other bio brands, and smaller local manufacturers all sold equivalent products at varying prices. Customers comparing a '50ml bio nourishing cream' would see all of them. The seller was manually searching Google Shopping for generic terms like 'crème nourrissante bio' and scanning results to understand where they stood. Slow, incomplete, and done every week.
Top challenges:
- Private-label products had zero competitive intelligence — no other seller carries their brand
- Manual Google searches for equivalent products were time-consuming and incomplete
- Fixed-coefficient pricing on own products had no connection to the competitive market
The Solution
We deployed MyMatching in similar product mode for their private-label catalog.
What We Configured
Instead of searching for exact product matches (same EAN, same brand), we configured the matching engine to find equivalent products from other brands. The AI analyzes product type, ingredients, certifications (bio, organic), format (cream, oil, serum), size, and price positioning to identify the most relevant competitors. The seller added custom AI instructions specific to their niche: prioritize products with similar organic certifications, exclude products containing certain chemicals their customers avoid, and weight ingredient lists heavily in similarity scoring. The matching engine searches Google Shopping, runs image comparison and semantic text analysis, applies an LLM arbitration pass, then assigns a confidence score to each equivalent match.
The seller is also a manufacturer. Their private-label bio creams and oils had zero competitive data — not because competitors didn't exist, but because no standard matching tool can find them. Similar matching changed how they price their entire own-brand catalog.
Key benefits:
- AI similar matching identifies equivalent competing products from other brands — no manual search required
- Custom AI instructions define what 'similar' means for their specific bio cosmetics niche
- Full catalog coverage: standard matching for distributed brands + similar matching for private label
The Results
Competitive visibility (private label)
Zero — completely blind on own-brand products → Equivalent competitors identified for every private-label SKU
Market research time
Hours of manual Google searches weekly → Automated monitoring — price changes visible within the day
Pricing confidence (own products)
Guesswork — fixed coefficients, no market data → Market-informed pricing based on real equivalent prices
The seller finally had competitive context on their entire private-label catalog. Products that had been priced by gut feeling — a fixed coefficient on production costs — now had market-based positioning. They found products priced below equivalent bio offerings from larger brands — margin left uncaptured. Others sat above the competitive set, which explained lower conversion on those lines. The automated monitoring runs continuously, so when a competitor launches a new equivalent or changes a price, the seller knows within the day. Standard matching on distributed brands plus similar matching on private label gives them full catalog coverage.
Understand this case in video
Not just for cosmetics
Any brand that manufactures or distributes private-label products faces the same blind spot — no competitor data on products only they sell.
- Food brands with own-recipe products that compete on category terms against larger manufacturers
- Fashion brands with private-label lines where 'similar style' defines the competitive set, not brand
- Any manufacturer selling direct-to-consumer who needs to understand how equivalent products are priced in the market
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