E-commerce & Quick Commerce

Zepto Scraper API

Zepto prices, stock and ETAs by pincode - live visibility into one of the fastest-growing quick-commerce platforms.

From $15/mo · 1,000 free API calls to start · see pricing

BOOK A SCOPING CALL ALL READY APIS
scrapeguys · zepto · sample response
{ "source": "zepto", "query": "amul butter 500g", "pincode": "400053", "price": 285, "mrp": 305, "in_stock": true, "store": "Andheri W", "eta_min": 9 }
What you can extract

Structured, ready to use

  • Prices & discounts
  • Stock by dark store
  • Delivery ETAs
  • Catalog coverage
  • Category rankings
  • Offer & coupon tracking
Example schema
FieldTypeExample
sourcestring"zepto"
querystring"amul butter 500g"
pincodestring"400053"
pricenumber285
mrpnumber305
in_stockbooleantrue
storestring"Andheri W"
eta_minnumber9

The full schema is customized to your workflow on the scoping call.

example request · async jobs API
curl -X POST https://api.scrapeguys.com/v1/jobs \
  -H "X-API-Key: $SCRAPEGUYS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"target": "zepto", "params": {"query": "milk 1l", "pincode": "400053"}}'

Illustrative request - field names and params for your deployment are fixed on the scoping call and documented in your workspace. Full request/response reference: API docs.

Platform notes

What makes Zepto data different

Store-level visibility

Zepto responses carry the serving store alongside price and ETA, which matters because two adjacent pincodes can be served by different stores with different stock and promotions. Brands tracking Zepto without the store dimension routinely misread their own availability.

Promotions switch fast

Zepto's discounts and combo offers rotate quickly and differ by city. Each reading separates MRP, selling price and the active offer, timestamped - so price-versus-Blinkit comparisons are made on the same minute, not across a promotion boundary.

Three-app comparisons need one schema

Most Zepto clients track Blinkit and Instamart too. We normalize all three into one schema - same fields, same pincode panel, same cadence - so a share-of-shelf or price-gap view is a query, not a reconciliation project.

Zepto-specific coverage

Serving-store id attached to every price point, Zepto Pass member vs non-member price pairs, Super Saver bundle pricing, ETA distributions per pincode, and stockout-duration tracking - built around Zepto's store-assignment model.

Use cases

What teams build on this

Pincode-level monitoring

Dark-store availability and delivery ETAs by pincode.

Price & promo tracking

Discounts, bundles and surge behaviour across zones.

Quick-commerce share

Catalog and ranking movement across the QC platforms.

Guides & answers: Quick commerce data Q&A · What is a web scraping API?

How it works

Scoped, built and operated for you

1

Scoping call

Fields, cadence, geography - shaped to your workflow. Docs & samples shared here.

2

We operate it

Anti-bot, proxies, parsing, monitoring - managed and SLA-backed on our side.

3

Clean JSON in

Async job API, BI feed, dashboard or MCP - one schema, your stack.

FAQ

Frequently asked questions

Is data per dark store or per pincode?
Per pincode, with the serving store recorded where exposed - the store dimension explains stock and promo differences that pincode-only views miss.
Can I compare Zepto against Blinkit prices directly?
Yes - same schema, same panel, same timestamps, so price gaps are read within the same collection minute rather than across stale snapshots.
How fast is the refresh?
Priority SKUs intraday, full catalog daily by default - tuned to how fast quick-commerce availability actually decays.
Can you track prices at pincode or dark-store level?
Yes. Price, stock, offers and delivery promise are captured per pincode and dark store, on your cadence - the same SKU is often live in one zone and out of stock in the next, and the feed shows exactly that. Most clients run priority SKUs intraday and the long tail daily.
Do you capture the final payable price including fees?
Yes. Item price, MRP, discounts plus delivery, small-cart and surge fees where shown - the checkout total is the real comparison between quick-commerce apps, not the item price.
How fast can quick-commerce data be refreshed?
Hourly where it matters. Quick-commerce availability decays in hours, so priority SKUs are typically checked multiple times a day; full-catalog sweeps run daily.
How do I get the API documentation and a data sample?
API documentation is public at scrapeguys.com/docs - request format, response schemas, status codes and worked examples. For a sample dataset on your exact targets, book a short scoping call: each deployment is customized to your schema, fields and volumes, and most teams have a sample in hand within a day.
How fast can this go live for us?
A scoped deployment typically goes live as a production API in 48-72 hours. That includes the scraper itself, a wrapper API shaped to your workflow, custom fields added to the response, monitoring and alerting on our side, and a staging key so your team can validate the schema before production traffic starts.
How is the data delivered - do we have to integrate an API?
An API is one option, not a requirement. The same data layer ships as REST JSON APIs with async jobs and webhooks, scheduled exports into Power BI, Looker, Snowflake, BigQuery or Google Sheets, a white-label dashboard your team signs into with zero integration, or MCP tools your AI agents call live. You can mix channels - API for engineering, dashboard for the commercial team - on one deployment.
What happens when the target site changes or a scrape fails?
That is our problem, not yours. Every source is monitored around the clock - layout changes, anti-bot updates and success-rate drops page our engineers before they page you, and your field names stay stable through redesigns because we absorb the change behind the schema. Failed requests are retried automatically, and anything that still fails is not billed: pricing is success-based.

Need Zepto data in production?

A 20-minute scoping call gets you documentation, samples and a timeline - most deployments are live in 48-72 hours.

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