How Similar Matching Gave an Organic Cosmetics Brand Competitive Visibility for the First Time

How Similar Matching Gave an Organic 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

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A French 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 organic 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 organic brands, and smaller local manufacturers all sold equivalent products at varying prices. Customers comparing a '50ml organic 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:

  1. Private-label products had zero competitive intelligence — no other seller carries their brand
  2. Manual Google searches for equivalent products were time-consuming and incomplete
  3. 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, organic certifications, 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 organic 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:

  1. AI similar-product matching identifies equivalent competing products from other brands — no manual search required
  2. Custom AI instructions define what 'similar' means for their specific organic cosmetics niche
  3. Full catalog coverage: standard matching for distributed brands + similar-product 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 for the entire private-label catalog. Products previously priced by gut feeling, using a fixed coefficient on production costs, now had market-based positioning. Some sat below equivalent organic products from larger brands, leaving margin uncaptured. Others were priced above the competitive set, which explained lower conversion. Automated monitoring now flags a new equivalent or price change within the day. Standard matching for distributed brands and similar-product matching for private label provide full catalog coverage.

See this case explained in a 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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