Wipro Consumer Care enters India’s pet nutrition market with Snuggles

Wipro Consumer Care and Lighting has launched Snuggles, a pet nutrition brand positioned on human-grade ingredients, complete nutrition and accessible pricing, entering India’s Rs 5,500-crore pet food market.

— Source publishedWed, 26 Aug, 2026, 12:32 IST·First seen Wed, 26 Aug, 2026, 12:39 IST·Source The Hindu BusinessLine

What happened

Wipro Consumer Care and Lighting entered India’s Rs 5,500-crore pet food market by launching Snuggles, a pet nutrition brand positioned around human-grade

Key facts

  • Rs 5,500 crore pet food market
  • 67% of pet parents are first-time pet owners

Why this matters

Wipro’s Snuggles launch signals strategic interest in pet care as a scalable adjacency, potentially creating partnership, acquisition and distribution opportunities across nutrition, veterinary services and pet retail.

What to watch

  • Snuggles SKU range, pack sizes and price-per-kilogram versus Pedigree, Drools, Purepet and Himalaya Healthy Pet Food.
  • Distribution footprint in general trade, pet specialty retail, e-commerce and quick-commerce within the first two quarters.
  • Evidence of repeat purchase, subscription offers, ratings and review volumes on major marketplaces.
  • Veterinarian, breeder or animal-welfare partnerships supporting nutrition and safety credibility.
  • Incumbent responses including price promotions, entry packs, regional launches or expanded human-grade claims.
  • Whether Wipro adds cat food, treats, supplements or grooming products within 12-18 months.
  • Launch trial-sized packs and price ladders aimed at first-time packaged-food buyers.
  • Prioritize general trade and distributor activation beyond metro pet stores to leverage Wipro's FMCG reach.
  • Build trust through veterinary partnerships, ingredient transparency, feeding guides and palatability claims.
  • Expand from core dog nutrition into treats, supplements and cat-food SKUs after validating repeat purchase.
  • Use e-commerce and quick-commerce data to identify high-repeat geographies and optimize assortment.