icon Published August 2026

The Vertical Deep-Dive Intelligence Series

Category-specific intelligence blueprints for Pet Supplies, Beauty, Alcohol, Pharma OTC, and Home Improvement — retailer coverage, unique data challenges, and category-specific scraping patterns.

EXECUTIVE SUMMARY

Each Vertical Has Unique Data Requirements

Generic scraping approaches fail for specialized verticals. Pet requires nutrition data, beauty needs ingredient lists, alcohol has age gates, pharma has regulatory constraints, and home improvement needs project-based bundling. This whitepaper is 5 vertical blueprints in one document.

5
Vertical blueprints covered — Pet Supplies (Chewy, Petco), Beauty (Sephora, Ulta), Alcohol (Drizly, Total Wine), Pharma OTC (CVS, Walgreens), Home Improvement (Home Depot, Lowe's). Each blueprint includes retailer coverage, unique data fields, and scraping challenges.

Vertical Coverage Overview

  • Pet Supplies: Chewy, Petco, PetSmart, Amazon Pet — subscription pricing, nutritional data, breed-specific filtering
  • Beauty: Sephora, Ulta, Nykaa, Boots — ingredient lists, shade/finish variants, review sentiment
  • Alcohol: Drizly, Total Wine, Dan Murphy's, BWS — vintage year, ABV, ZIP-level availability
  • Pharma OTC: CVS, Walgreens, Boots — dosage forms, ingredient interactions, generic equivalents
  • Home Improvement: Home Depot, Lowe's, B&Q — project bundling, tool + material pairing, contractor pricing
SECTION 1

Pet Supplies — The Chewy Deep Dive

Pet supplies is the fastest-growing e-commerce vertical, with Chewy dominating US market share at 42%. Unique data requirements center on subscription pricing (Autoship), breed/life-stage filtering, and nutritional composition data.

Retailer Market Share Unique Feature Data Complexity
Chewy 42% Autoship pricing Medium
Petco 18% Vital Care membership Medium
Amazon Pet 22% Subscribe & Save High
PetSmart 12% Treats loyalty tier Low
SAMPLE DATA

What Vertical Intelligence Actually Returns

Every Product Data Scrape Vertical Data API call returns structured JSON. Here's what a live response looks like:


// Product Data Scrape — Vertical Data API (Pet Example)
// GET /v1/vertical/pet?retailer=chewy&sku=BLUEB01
{
  "retailer": "chewy",
  "vertical": "pet_supplies",
  "product": {
    "brand": "Blue Buffalo",
    "title": "Life Protection Formula Adult 30lb",
    "category": "dog_food_dry"
  },
  "pricing": {
    "regular": 59.99,
    "autoship": 53.99,
    "autoship_savings_pct": 10.0
  },
  "vertical_specific": {
    "life_stage": "adult",
    "breed_size": ["small", "medium", "large"],
    "crude_protein_pct": 24,
    "grain_free": false,
    "prescription_required": false
  },
  "scraped_at": "2026-04-15T14:22:00Z"
}
                

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Continue reading in the free PDF

Retail Insights Cover pdf
Free resource

Everything you need to know about e-commerce data scraping

A practical guide to getting clean, reliable product, price and stock data from 500+ marketplaces — without building or maintaining scrapers in-house.

  • What's inside

    How price monitoring, digital shelf and brand protection data actually works

  • Why it matters

    Why manual tracking breaks at scale, and what teams gain from a managed feed

  • How to use it

    API, managed scrapers or ready datasets — how to pick the right delivery model

PDF guide 500+ marketplaces covered

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