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GeoIp2\Model\City Object
(
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            [city] => Array
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                    [names] => Array
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                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                            [es] => Norteamérica
                            [fr] => Amérique du Nord
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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            [country] => Array
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                            [fr] => États Unis
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                            [pt-BR] => EUA
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                            [zh-CN] => 美国
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                    [longitude] => -83.0061
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                            [es] => Estados Unidos
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

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                )

            [traits] => Array
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                    [prefix_len] => 22
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        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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        )

    [locales:protected] => Array
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        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.160
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
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            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
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                            [0] => confidence
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                            [2] => isoCode
                            [3] => names
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)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)
Travel • USA

Real-Time Travel & Hospitality Web Scraping in the USA

The USA is the world’s largest and most competitive travel market, with thousands of hotels, airlines, and OTAs competing for traveler attention every day. Room rates, airline fares, and OTA promotions change hourly, making real-time data critical for staying ahead.

Actowiz Solutions provides enterprise-grade travel data scraping services across the USA. From New York hotels and Las Vegas resorts to airline fare tracking and ride-hailing surge monitoring, our crawlers deliver structured, reliable datasets that power smarter business decisions.

Whether you are a hotel chain, OTA, airline, vacation rental operator, or travel consultant, we help you monitor competitors, optimize pricing, and improve traveler experiences with ready-to-use data delivered via CSV, Excel, JSON, or APIs.

Lead with travel intelligence in the USA’s dynamic market.

USA • Nationwide

Top Countries:

USA UK Germany Japan India France Canada Australia UK Germany Japan India France Canada Australia UK Germany Japan India France Canada Australia
UK Germany Japan India France Canada Australia UK Germany Japan India France Canada Australia UK Germany Japan India France Canada Australia

Create your own

B2B-B2C-Marketplace-amazon
B2B-B2C-Marketplace-IndiaMART
B2C-Marketplace-Amazon
B2C-Marketplace-Flipkart
D2C-Marketplace-Nykaa
D2C-Marketplace-Walmar
Electronic-D2C-Apple
Electronic-D2C-boAt
Fashion-Marketplace-Farfetch
Fashion-Marketplace-Myntra
FMCG-Marketplace-Boxed
FMCG-Marketplace-Udaan
Food-Delivery-Swiggy
Food-Delivery-Uber-Eats
Quick Commerce-Blinkit
Quick Commerce-GoPuff
Social-Commerce-Meesho
Social-Commerce-Poshmark
Taxi-Aggregator
Taxi-Aggregator-Uber

Why USA Travel Data Scraping is Essential

Discovery & Setup

Hotels in NYC, Miami, Los Angeles, Chicago, and Las Vegas change prices by the minute.

Discovery & Setup

Airlines like American, Delta, United, and Southwest adjust fares dynamically based on routes and demand.

Discovery & Setup

OTAs (Expedia, Priceline, Kayak, Booking.com) compete with aggressive deals and bundles.

Discovery & Setup

Vacation rentals (Airbnb, Vrbo) dominate urban and leisure segments.

Discovery & Setup

Ride-hailing (Uber, Lyft) and car rentals surge during events and holidays.

What We Scrape in USA Travel Industry

1
Hotel Data Scraping USA
Room rates, taxes, surcharges, amenities, loyalty discounts.
Cancellation policies, promotions, occupancy signals.
2
OTA Scraping USA
Expedia, Booking.com, Priceline, Hotels.com, Kayak.
Promotions, cross-channel rates, ad visibility.
3
Airline Fare Scraping USA
Fares from American, Delta, United, Southwest, Alaska, JetBlue.
Surcharges, baggage, ancillaries, loyalty tiers.
4
Vacation Rental Scraping USA
Airbnb, Vrbo, HomeAway, Sonder, local sites.
Listing rates, reviews, seasonal occupancy.
5
Ride-Hailing & Car Rental Scraping USA
Uber, Lyft → surge fares, ETA, wait times.
Hertz, Avis, Enterprise → daily rates, availability, insurance add-ons.
6
Review & Sentiment Scraping USA
TripAdvisor, Yelp, Google Reviews, OTA ratings.
Star ratings, review sentiment, traveler type segmentation.

High-Impact USA Travel Use Cases

Discovery & Setup

Hotel Rate Intelligence

Hotels in cities like New York, Miami, Las Vegas, San Francisco face constant competition. Scraping provides daily benchmarks of room rates, taxes, and packages across OTAs.

  • Impact: Hotels adjust pricing dynamically, OTAs ensure rate parity, investors track occupancy.
  • Example: A chain of 30 hotels in Florida scraped competitors on Expedia and Booking, increased ADR by 9% in a quarter.
Discovery & Setup

OTA Competitive Benchmarking

OTAs in the US fight for visibility. Scraping shows cross-OTA discrepancies, ranking positions, and deals.

  • Impact: Detect undercutting, optimize campaigns, negotiate parity with hotels.
  • Example: A mid-tier OTA benchmarked competitors’ rates and boosted visibility in Google Travel by 14%.
Discovery & Setup

Airline Fare Tracking

US airlines run revenue management systems that adjust fares every few minutes. Scraping delivers competitive fare intelligence across routes.

  • Impact: OTAs improve booking funnels, airlines spot competitive pricing trends.
  • Example: An OTA tracked 500K monthly fares, predicted discount windows, grew bookings by 12%.
Discovery & Setup

Vacation Rental Analysis

Airbnb and Vrbo dominate USA rentals. Scraping helps monitor listings, reviews, seasonal demand (e.g., Aspen in winter, Miami in summer).

  • Impact: Investors analyze ROI, property managers adjust pricing.
  • Example: A real-estate firm scraped Airbnb NYC data, identified profitable neighborhoods, boosted returns by 18%.
Discovery & Setup

Ride-Hailing & Car Rental Intelligence

Events like Super Bowl, Coachella, CES drive surge fares. Scraping helps predict pricing.

  • Impact: Travel apps integrate Uber/Lyft data, car rental firms monitor competitors.
  • Example: A startup integrated live Uber surge data into travel packages → 20% higher booking conversion.
Discovery & Setup

Review Sentiment Analytics

US travelers rely heavily on reviews. Scraping extracts customer voice from TripAdvisor, Yelp, Google.

  • Impact: Hotels detect pain points (housekeeping, Wi-Fi), OTAs optimize filters.
  • Example: A Las Vegas casino hotel scraped reviews, fixed check-in delays, raised NPS by 15%.
Discovery & Setup

Travel Deals & Package Intelligence

Deals from OTAs, airlines, and aggregators drive US traveler choices.

  • Impact: Benchmark packages, spot gaps, launch competitive bundles.
  • Example: A California OTA analyzed rivals’ summer deals, redesigned offers, bookings rose 22%.

Compliance, Scale & Delivery

No personal data

only public information.

Accuracy

99.9% accuracy with multi-layer QA.

Delivery

CSV, JSON, Excel, APIs.

Frequency

live, hourly, daily, weekly.

Support

SLA-backed uptime, 24/7 support.

Industries We Serve in USA Travel

Discovery & Setup

Hotels & Resorts

National and boutique chains.

Discovery & Setup

OTAs

Global and local US-focused platforms.

Discovery & Setup

Airlines

Full-service and low-cost carriers.

Discovery & Setup

Vacation Rentals

Investors, property managers, platforms.

Discovery & Setup

Tourism Boards

State and city-level tourism data.

Discovery & Setup

Market Researchers

Consumer travel behavior datasets.

Discovery & Setup

Investors

Travel & hospitality investment signals.

Sample USA Travel Data Schema

date city source hotel_name ota room_type rate tax discount availability review_rating airline route fare baggage_policy surge_flag ride_eta
2025-09-05 Chicago Expedia Holiday Inn Express Hotels.com Deluxe 280.66 43.57 13% Sold Out 4.7 Delta MIA-ORD 336.55 1 Free Bag Yes 8 min
2025-09-04 New York Booking.com Holiday Inn Express Expedia Standard 301.97 38.4 11% Limited 4.6 Delta NYC-LAX 311.3 2 Bags Included Yes 5 min
2025-09-03 New York Hotels.com Marriott Downtown Expedia Suite 167.23 24.29 9% Available 3.6 Delta MIA-ORD 519.79 2 Bags Included No 11 min
2025-09-02 Chicago Booking.com Holiday Inn Express Booking.com Deluxe 274.7 29.15 8% Sold Out 4.8 Delta NYC-LAX 566.73 1 Free Bag Yes 15 min

Geo Coverage – USA

We cover all 50 states and major cities, including:

FAQs – USA Travel Data Scraping

We can scrape data from almost every major public travel platform in the USA. This includes:
  • Hotels & Resorts: Hilton, Marriott, Hyatt, Wyndham, IHG, Choice Hotels, MGM Resorts, Caesars Entertainment.
  • OTAs (Online Travel Agencies): Expedia, Priceline, Booking.com, Hotels.com, Kayak, Orbitz, Travelocity.
  • Airlines: American Airlines, Delta, United, Southwest, Alaska Airlines, JetBlue, Spirit.
  • Vacation Rentals: Airbnb, Vrbo, HomeAway, Sonder.
  • Ride-Hailing & Mobility: Uber, Lyft, Zipcar, regional taxi apps.
  • Review Sites: TripAdvisor, Yelp, Google Reviews.
If you need niche sources, like city tourism boards, boutique hotel sites, or local state-level operators, we can customize crawlers for those too.
Yes. Airline fares in the USA change multiple times per day, especially on competitive routes like New York–Los Angeles or Chicago–Miami. Our live crawlers track fares directly from airlines and OTAs:
  • Base fare, surcharges, and taxes.
  • Baggage policies and seat class upgrades.
  • Loyalty discounts and promo codes.
  • Ancillary services (meals, seat selection, Wi-Fi).
For OTAs, this ensures fare parity monitoring, and for airlines, it enables competitive benchmarking. Corporate travel teams use this data to identify low-fare windows and optimize booking schedules. Delivery can be real-time via APIs or scheduled reports.
Travel sites often use anti-bot protections. We deploy adaptive crawling strategies:
  • Rotating residential & mobile proxies across US states.
  • Headless browsers (like Puppeteer/Playwright) for realistic behavior.
  • Dynamic fingerprinting (changing user-agents, click paths).
  • Retry logic with fallback IPs for stability.
If sites change layout (which OTAs often do), our AI-based parsers auto-adjust to avoid downtime. This ensures continuous scraping at scale without disruptions, even during peak booking seasons like summer holidays or Thanksgiving.
Yes. Many US clients want historical hotel rates or flight fare trends for forecasting. Depending on the source:
  • Hotels & OTAs: If listings are archived publicly, we can backfill several months.
  • Airlines: Limited archives, but we can build datasets moving forward.
  • Reviews: We can capture years of historical customer feedback from TripAdvisor, Yelp, and Google.
Clients use historical data to analyze seasonality trends (Christmas, Labor Day, July 4th) or event-driven spikes (Super Bowl, CES in Las Vegas). This helps in forecasting demand and optimizing yield management.
Absolutely. Review scraping in the USA is powerful for understanding customer experience. We extract review text, star ratings, reviewer type, and timestamps from sources like TripAdvisor, Yelp, Google Reviews, and Booking.com. Using NLP (Natural Language Processing), we categorize reviews into positive, negative, or neutral sentiment. Example use cases:
  • Hotels in New York: Detect recurring complaints (e.g., “slow check-in” or “small rooms”).
  • Airlines like Delta or United: Spot pain points such as “lost baggage” or “delayed flights.”
  • Restaurants & Rentals: Identify strengths/weaknesses by city (e.g., “clean Airbnb” in Miami).
This allows US businesses to improve service, boost ratings, and increase loyalty.
We deliver data in all industry-standard formats:
  • CSV & Excel → simple reports for business teams.
  • JSON & Parquet → flexible feeds for data engineers.
  • APIs → live integrations with OTAs, airlines, and BI tools.
  • Cloud Delivery → secure S3/GCS/Azure buckets.
Some US clients prefer dashboard integrations where we connect travel data directly into Power BI, Tableau, or Looker for real-time visualization.
Accuracy is critical. We guarantee 99.9% accuracy by running:
  • Field-level validation (room rate matches correct room/date).
  • Schema checks (no missing values in critical fields).
  • Deduplication (avoid repeated records).
  • Automated QA with human spot-checks.
For example, when scraping 100,000 hotel rates from Expedia, our QA ensures each rate is mapped to the correct property, location, and room type. If any errors slip, crawlers are auto-retried. This prevents pricing mistakes that could cost travel companies millions.
Yes. USA travel data scraping can be granular at city and even neighborhood level.
  • New York City: Manhattan hotels, JFK/LGA flight fares, Uber surge in Brooklyn.
  • Los Angeles: LAX fares, Hollywood hotels, Airbnb in Venice Beach.
  • Miami & Orlando: Resorts, Disney travel packages, cruise rates.
  • Las Vegas: Casino resorts, OTA deals, show tickets.
  • Chicago, Boston, Seattle, Dallas, Denver: Business travel hubs.
This geo-specific intelligence helps OTAs, hotels, and tourism boards create localized marketing campaigns and dynamic pricing models.
Yes. Many US travel companies use dashboards for decision-making. We can feed scraped data into:
  • Power BI, Tableau, Looker → for interactive dashboards.
  • Custom dashboards built by internal teams.
  • Google Data Studio → lightweight visualization for executives.
For example, a San Francisco OTA integrated daily hotel price heatmaps into Tableau, comparing competitor prices in Los Angeles, Las Vegas, and New York. Airlines can track fare volatility charts by route. Dashboards allow real-time travel insights at scale.
Starting is simple:
  • Requirement Sharing → Tell us which sites, fields, frequency, and cities you need.
  • Free Sample → We deliver a test dataset (e.g., 100 NYC hotels, 50 routes).
  • Pilot (2–4 weeks) → Limited-scale scraping to refine logic and formats.
  • Full Scale → Move to hourly/daily crawlers with SLAs and dedicated support.
Most US clients start with hotel benchmarking in NYC or airline fare monitoring on key routes. Once validated, they expand into multi-city, multi-platform scraping.

Case Study

Industry:

Travel & Hospitality – USA

Result

Up to 27% Boost in Direct Bookings & Fare Optimization

★★★★★

“Actowiz Solutions helped us monitor hotel room rates, airline fares, and ride-hailing surge patterns across Expedia, Booking.com, Airbnb, Delta, and Uber in New York, Miami, and Los Angeles. Their real-time pricing, availability, and review insights allowed us to adjust promotions instantly—leading to a 27% increase in direct hotel bookings, 18% better flight fare competitiveness, and 9% higher customer satisfaction scores.”

Head of Revenue Strategy , USA Travel Brand

✓ 27% uplift in direct hotel bookings

✓ 18% improved airline fare competitiveness

✓ 9% higher customer satisfaction

Organic Tattva 1 01
GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
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                    [geoname_id] => 4509177
                    [names] => Array
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                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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            [continent] => Array
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                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                            [ru] => США
                            [zh-CN] => 美国
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                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
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                    [code] => 43215
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            [registered_country] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
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                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [subdivisions] => Array
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                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.160
                    [prefix_len] => 22
                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.160
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

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From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape Structure Analyze Visualize

Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

Find Insights Use AI to connect data points and uncover market changes. Meanwhile.

Move Forward Predict demand, price shifts, and future opportunities across geographies.

Industry:

Coffee / Beverage / D2C

Result

2x Faster

Smarter product targeting

★★★★★

“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

“With Actowiz Solutions' data scraping, we’ve gained a clear edge in tracking product availability and pricing across various platforms. Their service has been a key to improving our market intelligence.”

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

“Actowiz Solutions has greatly helped us monitor product availability from top three Quick Commerce brands. Their real-time data and accurate insights have streamlined our inventory management and decision-making process. Highly recommended!”

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

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Real results from real businesses using Actowiz Solutions

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'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"
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Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
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Iulen Ibanez
CEO / Datacy.es
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★★★★★
“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”
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Febbin Chacko
-Fin, Small Business Owner
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1 min

See Actowiz in Action – Real-Time Scraping Dashboard + Success Insights

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

Price Drop + 12 min
in 6 hrs across Lel.6

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & planning

Monitor Prices, Availability & Trends -Live Across Regions

Actowiz's real-time scraping dashboard helps you monitor stock levels, delivery times, and price drops across Blinkit, Amazon: Zepto & more.

✔ Scraped Data: Price Insights Top-selling SKUs

Our Data Drives Impact - Real Client Stories

Blinkit | India (Retail Partner)

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

With hourly price monitoring, we aligned promotions with competitors, drove 17%

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

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Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place

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Sep 17, 2025

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how brands Extract Amazon Festive Sale Apparel Discounts Data to achieve 80% faster deal detection across 12 top categories.

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reveals how brands Extract Festive Sale Data from Amazon, Flipkart & Reliance with 90% flash-sale alerts and 50+ brands analyzed.

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Web Scraping Services in UAE – Historical Navratri Sales Data – 2020–2025 Discount Trends

Explore Historical Navratri Sales Data from 2020–2025 to track discounts, flash sales, and consumer trends across Amazon, Flipkart, and Myntra.

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Myntra vs Ajio Navratri discount scraping 2025

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