Skip to main content
ClyminClymin
Book a Meeting

Solution

Competitor ETAs and surge windows, captured by the minute

Real-time delivery times, slot availability, surge multipliers, and dark-store coverage across quick commerce, food delivery, and ride-hail. The operational signal your competitors are running on.

<2 minp95 surge detection latency
50M+eta records captured daily
99.9%pipeline uptime
Start a free pilotTalk to us

Delivery is the new shelf.

In quick commerce and food delivery, the customer chooses the platform that promises the fastest delivery for their slot. ETA, slot availability, and surge windows decide the basket more than price.

Most ops teams operate blind on competitor delivery.

You know your own ETAs. You guess at competitors. You see them every Monday in a stale report. The 4-hour surge window where your competitor was 30 minutes faster, and you lost 15% of orders, is invisible until churn shows up.

We capture every ETA, every surge, every slot, in every city.

Cycles as low as every 15 minutes per pin code. ETAs in minutes, surge multipliers, slot availability, dark-store coverage, last-mile partner, captured per request, geo-tagged.

ETAs by the minute

Track competitor delivery promises across every city, slot, and time of day. See where you are faster, where you are slower, and where the gaps are widening.

Surge windows and slot availability

Catch surge multipliers, slot blackouts, and demand-driven price changes the moment they appear. Operations teams react inside the surge window, not after.

Dark-store and last-mile coverage

See which dark stores serve which pin codes, which last-mile partners run which lanes, and where competitors have gaps in coverage you can target.

Key insight

In quick commerce, a 2-minute ETA gap costs more than a price gap. Customers do not always notice price. They always notice waiting.

How it works

The extraction pipeline

From target spec to your warehouse, every delivery and ETA record passes through these stages. You see the output. We run everything in between.

01

Target spec

Cities, pin codes, slot windows, cadence, and schema locked from your pilot scope.

02

Source orchestration

App-layer extraction across QC, food delivery, and ride-hail apps in parallel, geo-routed to each city in scope.

03

Capture

Per-pin-code geo-routed sessions, app-layer signed requests, surge-window detection.

04

Validation

Schema, plausible-range checks on ETAs, dark-store consistency, time-window normalization.

05

Delivery

CSV, JSON, REST, or direct push to your warehouse, in your spec.

Coverage

Platforms we monitor

Delivery and ETA monitoring runs against a narrower set of platforms than catalog or pricing work. Each platform exposes ETAs and surge differently, and capture has to happen at pin-code granularity to be useful.

Quick commerce

Blinkit, Zepto, Swiggy Instamart, BigBasket, Dunzo at pin-code level

Food delivery

DoorDash, Uber Eats, Deliveroo, Talabat, Zomato, Swiggy, ShopeeFood menus and ETAs

Ride-hail

Uber, Ola, Grab fares, surges, and slot availability

Marketplace same-day

Amazon, Flipkart, Walmart same-day delivery promise capture

50M+ETA records captured daily across cities and slots

Data landscape

The data we extract

Every ETA, surge multiplier, slot, and dark-store record from every monitored platform, normalized into one delivery-ops schema, delivered on your cadence.

ETA

Promised delivery time, min and max range, distance, express availability

Surge

Surge multiplier, window start, window end estimate, demand level

Coverage

Dark-store ID, serviceable pin codes, last-mile partner

Fees

Delivery fee, currency, free-delivery threshold, express upgrade fees

Slot availability

Current availability, next blackout, full schedule where exposed

Sourcing

Platform, surface, market, city, pin code, capture timestamp

This is a representative sample of the data we extract. We customize every extraction to your exact requirements. If you need a data point not listed here, we will add it to your pipeline.

Sample output

What a single record looks like

This is a representative payload from a real delivery and ETA extraction job. Field names, schema, and delivery format are scoped to your spec at pilot time.

{
  "extracted_at": "2026-05-07T14:23:47Z",
  "platform": "blinkit",
  "surface": "app",
  "market": "IN",
  "city": "Bengaluru",
  "pin_code": "560038",
  "request_geo": {
    "lat": 12.9716,
    "lng": 77.6411
  },
  "delivery": {
    "promised_eta_minutes": 14,
    "min_eta_minutes": 12,
    "max_eta_minutes": 18,
    "is_express_available": true
  },
  "surge": {
    "active": true,
    "multiplier": 1.4,
    "window_started_at": "2026-05-07T14:00:00Z",
    "window_ends_at_estimate": "2026-05-07T15:30:00Z"
  },
  "fees": {
    "delivery_fee": 25,
    "currency": "INR",
    "free_delivery_threshold": 199
  },
  "dark_store": {
    "id": "BLK-DARK-BLR-014",
    "name": "Indiranagar 1",
    "distance_km": 1.8
  },
  "slots": {
    "available_now": true,
    "next_blackout_at": null
  }
}

Schema

Field-level reference

Every record conforms to a stable schema. Your engineering team can integrate against this spec before the pilot starts.

extracted_atISO 8601

UTC capture timestamp

2026-05-07T14:23:47Z
platformstring

Source platform name

blinkit
marketISO-3166

Market code

IN
citystring

City of capture

Bengaluru
pin_codestring

Pin code requested

560038
request_geo.lat / lngnumber

Geo of the request origin

12.9716 / 77.6411
delivery.promised_eta_minutesnumber

Headline ETA shown to user

14
delivery.min_eta_minutesnumber

Lower bound of ETA range

12
delivery.max_eta_minutesnumber

Upper bound of ETA range

18
delivery.is_express_availableboolean

Express upgrade offered

true
surge.activeboolean

Surge multiplier currently applied

true
surge.multipliernumber

Surge multiplier (1.0 = no surge)

1.4
surge.window_started_atISO 8601

When surge began

2026-05-07T14:00:00Z
surge.window_ends_at_estimateISO 8601

Platform-estimated end of surge

2026-05-07T15:30:00Z
fees.delivery_feenumber

Delivery charge

25
fees.currencyISO-4217

Currency code

INR
fees.free_delivery_thresholdnumber

Min order for free delivery

199
dark_store.idstring

Source-platform dark-store identifier

BLK-DARK-BLR-014
dark_store.namestring

Dark-store label or area

Indiranagar 1
dark_store.distance_kmnumber

Distance from request geo

1.8
slots.available_nowboolean

Slot available immediately

true
slots.next_blackout_atISO 8601 / null

Next slot blackout window

null

Delivery formats

How you receive the data

You define the format. We handle the rest.

CSV

Daily or hourly drops

Scheduled flat-file delivery. Clean, deduplicated rows with the columns you define.

{}
{}

JSON

Nested or flat schema

Structured JSON files for direct ingestion into your data pipeline or analytics tools.

API

Real-time access

REST API with real-time access to the latest extracted data. Webhook support included.

Direct warehouse

Zero-touch delivery

We push directly to your Snowflake, BigQuery, Redshift, or S3 bucket. Zero manual steps.

Custom setup

Talk to us

Need a different format, frequency, or integration? We build it for you at no extra cost.

Use cases

How teams put delivery and ETA data to work

From pricing teams to category managers to operations leads, here are the most common ways delivery and ETA data drives decisions.

Operations, competitive ETA benchmarking

Compare your ETAs against every competitor, by city, slot, and time of day. Identify where last-mile is the bottleneck and where dark-store density is the constraint.

Network planning, dark-store gap analysis

See where competitors have dark stores you don't, and where you have stores they don't. Plan expansion, lease negotiation, and density investments on real coverage data.

Surge response, pricing and capacity

Catch competitor surge windows the moment they activate. Decide whether to match surge, hold price, or push capacity into the window.

Customer experience, promise reliability

Compare promised ETAs across competitors over time. Spot where competitors consistently outperform you, and where their promises slip.

Category teams, basket attribution

Correlate delivery performance with basket and category share. Understand where slow delivery is costing share and where fast delivery is winning customers.

₹

Leadership, operational scorecard

Monthly board-ready ETA, surge, and coverage reports across cities and competitors. Where we are winning, where we are losing, and how the gap is moving.

Tech specs

What we run at scale

Every delivery and ETA engagement runs against these baseline specs. Your scope can move freshness, throughput, or geo coverage to whatever you need.

<2 min

p95 surge detection latency

50M+

ETA records captured daily

99.9%

Pipeline uptime

300+

Cities monitored

15 min

Minimum extraction cycle

99%+

Records passing validation

Challenges

Why delivery and eta data extraction is hard

If extraction were easy, you would do it yourself. Here is why it is not.

01

ETAs vary by pin code, time, and demand

The same dark store serves 8 pin codes with different ETAs each. Demand changes ETA every 5 minutes. A single ETA snapshot tells you almost nothing.

02

Surge windows are short and high-stakes

Surge multipliers fire and end inside an hour. Detecting them requires per-pin-code polling at high cadence. Most providers sample once a day and miss every surge that mattered.

03

Apps return different ETAs for different sessions

The same request from two phones in the same building can return two different ETAs. Capturing the variance, not just one number, is what operational teams need.

04

Dark-store coverage is hidden

Platforms do not publish dark-store maps. Coverage has to be inferred from pin-code-level extraction across thousands of geos, then triangulated.

05

Geo-routing at scale is the hard part

Capturing per-pin-code data means thousands of parallel geo-routed sessions. Each pin code looks like a different user, in a different location, with a different SIM. Anti-bot systems flag patterns most providers cannot suppress.

06

Building it in-house costs more than the data

Engineers, geo-routing infrastructure, surge-detection logic, monitoring, on-call. Internal projects spend 6 to 12 months and still miss the surge windows that mattered most.

Why us

Why Clymin for delivery and eta

We are not a tool. We are the team you call when the data matters too much to get wrong.

We solve what others can't

Geo-distributed delivery monitoring at pin-code granularity, every 15 minutes, across 300+ cities. Surge detection inside the window, not after. App-layer extraction where the operational signal lives.

We prove it before you pay

Free pilot on your cities, your competitors, your slot windows. Sample data within 1 to 3 days. You evaluate against your own delivery telemetry before any commitment.

You pay only for data delivered

Per record, no setup fees, no per-city charges, no per-platform charges. One metric: cost per record. If we don't deliver, you don't pay.

Your identity stays protected

We do not display client logos or name-drop. Operational intelligence is sensitive. Your competitors should never know you are watching.

100B+

Data points extracted

24/7

Pipeline uptime

Real-time

Data delivery

100K+

Points of interest covered

Proven at enterprise scale. We operate continuous competitive intelligence infrastructure for one of the world's largest quick commerce platforms.

Industries served

Who buys delivery and ETA data

The verticals where delivery and ETA extraction creates the most leverage.

Quick CommerceE-commerce MarketplacesD2C BrandsOmnichannel RetailersTravel OTAsHealthcare

See every surge window and ETA gap before you lose the customer

Tell us your cities, your competitors, your slot windows. Pilot data in 1 to 3 days. No commitment.

Start a Free PilotBook a Meeting

FAQ

Real-Time Delivery & ETA Monitoring data extraction FAQ

Quick commerce (Blinkit, Zepto, Swiggy Instamart, BigBasket, Dunzo), food delivery (DoorDash, Uber Eats, Deliveroo, Zomato, Swiggy, Talabat), ride-hail (Uber, Ola, Grab), and marketplace same-day delivery (Amazon, Flipkart, Walmart).

Pin-code level for quick commerce and food delivery. City and neighborhood for ride-hail. Full lat/lng captured per request.

Yes. p95 detection within 2 minutes of surge activation. For critical windows you flag during pilot, we run continuous polling at sub-minute granularity.

Yes, for QC platforms that expose dark-store identity (Blinkit, Zepto, Swiggy Instamart, BigBasket). Dark-store ID, name, and serviceable pin codes are captured.

The pipeline captures competitor ETAs at pin-code and slot granularity. Your team aligns this against your own delivery telemetry to compute the gap. We can deliver the comparison-ready join if you provide your delivery feed.

Yes. Captured per request, per city, per route: surge multiplier, ETA, fare estimate, route availability, slot blackouts.

CSV, JSON, REST API, or direct push to your data warehouse: BigQuery, Snowflake, Redshift, S3. You define the schema.

We extract publicly available data. We do not extract authenticated user-level data without explicit account ownership. Use of extracted data is the customer's responsibility under their jurisdiction.