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In demand · Pricing strategy

See how rivals move prices by the hour — and why

Dynamic pricing is now the norm: prices, delivery fees and surges flex with demand, weather and time of day. We capture every move so you can model the algorithm behind it and price with confidence.

Surge & price signal · live Live
Uber Eats
Peak dinner surge · Chicago
+18% delivery
DoorDash
Rainy-hour fee · Seattle
$2.99 → $5.49
Swiggy
Late-night menu price · Delhi
+9%
Deliveroo
Off-peak discount · London
-12%
// Why this matters now

Static price lists lose money in a dynamic market.

When competitors flex prices in real time and you don't even see it, you either leave margin on the table or get undercut. Structured surge data turns guesswork into a pricing model.

24/7Surge and fee changes run around the clock, not on a schedule.
±30%Typical swing between off-peak and surge delivery fees.
Per-hourGranularity teams need to actually model elasticity.
// What you can track

Decode the pricing algorithm behind the screen.

Time-of-day price curves

How item and delivery prices move across the day, week and season.

Surge fee patterns

Delivery and service-fee surges mapped to demand, weather and events.

Price elasticity signals

Track how often and how far rivals move price for each SKU.

Promo-vs-surge interplay

See how discounts and surges are used together to defend the basket.

Geo & zone-level pricing

Compare the same item priced differently by city, zone or store.

Competitor price benchmarks

Always know where you sit versus every rival, in real time.

// Platforms & sources covered
// In-demand countries

Where this is most in demand — and covered live.

Dynamic pricing is most aggressive in these mature delivery markets we cover live:

+ 40 more markets on request — tell us yours.

// How it works

From request to live feed in days.

1

Tell us the targets

Share the competitors, platforms, regions and fields you care about.

2

We build & QA

Anti-block extraction plus two-pass QA, refreshing on your schedule.

3

Feed your stack

JSON, CSV, API, alerts or a live dashboard — with change alerts built in.

// FAQ

Dynamic & surge pricing — your questions.

Can you capture surge and delivery fees, not just item price?

Yes — surge multipliers, delivery and service fees, minimum-order and free-delivery thresholds, all timestamped by location.

How granular is the time data?

Down to hourly (or finer) so you can build genuine time-of-day and day-of-week elasticity models.

Can I see the same item priced by city or zone?

Yes — we capture geo- and zone-level pricing so you can compare identical SKUs across markets.

Which platforms and countries do you support?

Uber Eats, DoorDash, Deliveroo, Swiggy, Zomato, Instacart and more across the USA, UK, India, UAE, Australia, Brazil, Germany and 40+ markets.

How do I receive the data?

JSON, CSV, REST API, scheduled feeds, change alerts or a live dashboard — into Snowflake, BigQuery, S3, BI tools or webhooks.

Get a free sample for "Dynamic & surge pricing" — in 48 hours.

Send us your platforms and markets. We'll return a working sample so you can see the quality before you commit.

Array
(
    [ip] => 208.109.38.66
    [hostname] => 66.38.109.208.host.secureserver.net
    [city] => Phoenix
    [region] => Arizona
    [country] => US
    [loc] => 33.4484,-112.0740
    [org] => AS26496 GoDaddy.com, LLC
    [postal] => 85003
    [timezone] => America/Phoenix
)
Get a Free Food Data Sample

Get a Free Food Data Sample in 48 Hours.

Tell us your platforms, target markets and required fields — we'll map exactly what's possible with food data scraping, recommend the right approach, and send a working sample so you can verify quality before any commitment.

Free pilot — 1,000 records, no credit card
48-72 hour sample turnaround
GDPR-aligned · public data only · NDA on request
5★ rated on Clutch, GoodFirms & Trustpilot
Singapore Office
60 Paya Lebar Rd, #11-22
Paya Lebar Square
Singapore 409051
India Office
202, Nr. Indraprastha Business Park
Makarba, Ahmedabad
Gujarat 380051

Request a strategy call

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