Q-commerce

Numeric distribution (ND) & product density

Numeric distribution (ND) and product density data, collected across the Q-commerce platforms where your brand and your competitors sell, shows your true reach and assortment depth. Each platform runs its own fast-changing catalog and pricing, so a unified view is hard to build. We build that unified view for you across those platforms.

Enterprise scraping and matching from 5,000+ sources.

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  • Uber Eats
  • Getir
  • Eventim
  • Booking.com
  • Audible
  • Skyscanner
Common problems

Brand reach is spread across many Q-commerce platforms

ND and product density data sits behind CAPTCHA challenges, IP blocking, and constantly changing anti-bot technology, so in-house acquisition keeps skilled staff busy and still produces unreliable datasets. Dedicated specialists in enterprise web scraping, advanced data matching, and proxy management deliver consistent, high-fidelity market intelligence.

Catalogs that vary by platform

Q-commerce moves at breakneck speed across many platforms, each with its own changing product catalog and pricing. Clients struggle to see their own or competitors' true online presence and assortment depth in one accurate view, and often say, "We lack a clear picture of our market position and competitor offerings."

Launch and pricing calls by guesswork

Without reliable ND and product density data, decisions on product launches, inventory allocation, pricing adjustments, and promotional campaigns become guesswork. Market share and revenue potential shrink, and the competitive gap grows in fast-moving Q-commerce markets.

CAPTCHA challenges and IP blocking

Q-commerce platforms run sophisticated, constantly changing anti-bot technologies, including dynamic content rendering, CAPTCHA challenges, and IP blocking. Non-specialist teams that try to extract data consistently, at high frequency and at scale, face a persistent, resource-intensive battle.

Data scientists building ND pipelines

ND and product density pipelines need constant building and maintenance, and that work pulls valuable internal engineering and data science teams away from core business innovation. Highly skilled people spent this way inflate operational costs and slow critical product development.

Our solutions

Brand reach and assortment depth by platform

ND and product density data is scraped from each Q-commerce platform, matched to your products and your competitors', checked by hand, and verified by automated QA.

One view of distribution and density

A curated overview shows your numeric distribution and product density across the relevant Q-commerce platforms, so your strategic teams have market intelligence they can act on.

Assortment calls made on solid data

Accurate, timely data supports informed decisions on pricing, product assortment, and promotional strategies. The effect shows directly in market share expansion and revenue.

Resilient collection from tough sources

Enterprise-grade infrastructure, intelligent proxy rotation, and adaptation to advanced anti-bot technologies keep data collection resilient and reliable, even from the most challenging Q-commerce sources. Collection is backed by a 99.9% uptime SLA.

Analysts free for strategic analysis

Our managed service model takes the whole burden of data acquisition off your hands. Your highly skilled engineering and data science professionals can concentrate on core innovation and strategic analysis.

Other use cases

Other Q-commerce data use cases

Alongside numeric distribution (ND) and product density, our web scraping, data matching, and infrastructure management support the Q-commerce use cases below for enterprise clients.

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Start your ND and product density project

Discuss your unique challenges and strategic objectives with a dedicated Q-commerce data specialist who has deep expertise in numeric distribution (ND) and product density.

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