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GeoIp2\Model\City Object
(
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                            [ja] => コロンバス
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    [continent:protected] => GeoIp2\Record\Continent Object
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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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                            [fr] => États Unis
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                            [pt-BR] => EUA
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                            [zh-CN] => 美国
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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            [validAttributes:protected] => Array
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    [registeredCountry:protected] => GeoIp2\Record\Country Object
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [zh-CN] => 美国
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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
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                    [network] => 216.73.216.0/22
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            [validAttributes:protected] => Array
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                    [8] => isHostingProvider
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                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
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                    [20] => userCount
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        )

    [city:protected] => GeoIp2\Record\City Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [names] => Array
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                            [de] => Columbus
                            [en] => Columbus
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                            [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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            [validAttributes:protected] => Array
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    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
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                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
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            [validAttributes:protected] => Array
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                    [1] => accuracyRadius
                    [2] => latitude
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                    [4] => metroCode
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                    [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
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    [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
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                            [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
)
Real-Time Regional Insights with Customizable E-commerce Dashboards

Introduction

In 2025, the Indian calendar presents a rare phenomenon: two major holidays—Raksha Bandhan (August 8) and Independence Day (August 15)—fall on consecutive Fridays, effectively creating two long weekends in the first half of August. This unique overlap fuels a surge in short vacations, weekend getaways, and domestic travel bookings.

But how do such long weekends impact travel prices? Are travelers benefiting from discounts, or are brands capitalizing on demand with sharp price hikes?

Actowiz Solutions, a leader in travel price intelligence and real-time data scraping, set out to analyze the pricing behavior around these dates using its proprietary OTA scraping APIs and airfare tracking tools. The findings from this study offer rich insights for airlines, hotels, travel agents, and tourism boards to optimize pricing strategies, improve ad targeting, and boost booking conversions during festive seasons.

Case Study Objective

  • Track flight and hotel price fluctuations around Raksha Bandhan and Independence Day 2025.
  • Identify patterns in last-minute surges and early bird discounts.
  • Provide actionable insights for businesses in the travel ecosystem.
  • Showcase how Actowiz Solutions empowers stakeholders with real-time travel scraping.

Scraping Methodology

To deliver timely and relevant insights, Actowiz deployed targeted scraping campaigns across the following platforms:

1. Flight Sources
  • Airline portals: IndiGo, Vistara, Air India, Akasa Air.
  • OTA platforms: MakeMyTrip, Goibibo, Yatra.
2. Hotel Booking SFources
  • Aggregators: Booking.com, Agoda, Airbnb, OYO.
  • Filters: Location, star rating, room availability, price changes.
3. Routes & Destinations
  • Airfare: Delhi → Goa, Mumbai → Udaipur, Bengaluru → Kochi.
  • Hotels: Goa (Baga Beach) & Manali (Budget & mid-range stays).
4. Timeline
  • Scraping Period: July 25 – August 20, 2025.
  • Frequency: Twice daily (8 AM and 6 PM), simulating consumer browsing windows.

Airfare Trends – Raksha Bandhan Window

Let’s begin with the Raksha Bandhan long weekend from August 8 (Friday) to August 10 (Sunday). Travelers were mostly booking between August 6–7 (mid-week) for departures and returning by August 10.

Sample Data – Airfare Price Trends
Date Delhi to Goa Mumbai to Udaipur Bengaluru to Kochi
Aug 6 (Wed) ₹3,400 ₹2,800 ₹2,700
Aug 7 (Thu) ₹6,200 ₹4,500 ₹4,600
Aug 8 (Fri) ₹7,800 ₹6,900 ₹5,200
Aug 9 (Sat) ₹6,100 ₹5,300 ₹4,400
Aug 10 (Sun) ₹4,900 ₹3,900 ₹3,200
Aug 11 (Mon) ₹3,700 ₹3,100 ₹3,000
Aug 12 (Tue) ₹3,200 ₹2,900 ₹2,800
Key Observations
  • Fare Spike on Aug 8: A 129% increase was recorded in the Delhi–Goa sector, peaking on Raksha Bandhan morning.
  • Last-Minute Premium: Flights booked less than 24 hours before departure (Aug 7 evening – Aug 8 morning) saw the steepest increases.
  • Post-Weekend Correction: Prices normalized by Aug 11–12 across all routes.

Hotel Surge – Goa’s Coastal Hotspots

Beach destinations like Goa saw major demand spikes, especially around Baga Beach and Calangute.

Sample Data – Hotel Pricing (Goa)
Hotel Name Location Normal Price Surge Price (Aug 7–9) Surge %
Seaside Inn Goa ₹2,600 ₹4,200 +61.5%
Ocean Breeze Goa ₹3,200 ₹5,100 +59.3%
Casa Bella Goa ₹2,500 ₹3,900 +56%
Key Observations
  • Most budget hotels offered no discounts, instead increasing rates by over 55–60%.
  • Some hotels listed "Only 2 rooms left" badges, signaling real-time inventory scarcity.
  • Highest bookings were on August 7 evening, indicating last-minute travel plans.

Independence Day Effect – Flight Surge Continues

The second long weekend began on August 15 (Friday), with travelers departing between Aug 14–15 and returning by Aug 18 (Monday).

Sample Data – Bengaluru → Kochi (Flight Prices)
Date Avg. Fare (₹) Surge from Base
Aug 13 ₹2,800 +4%
Aug 14 ₹4,600 +64%
Aug 15 ₹5,200 +85%
Aug 16 ₹4,400 +57%
Aug 17 ₹3,200 +14%
Key Observations
  • Fare spike was highest on August 15 (Independence Day), with limited seat availability.
  • Return flights remained expensive till August 17 (Sunday evening).
  • Many routes saw "sold out" tags by August 13, validating the trend of early booking.

Hill Stations – Discounted to Surging

Interestingly, hill station hotels—particularly in Manali—used a "pre-surge discount model" to attract early travelers.

Sample Data – Hotel Pricing (Manali)
Hotel Name Normal Price Surge Price (Aug 15) Early Bird Price (Aug 12–13) Discount %
Himalayan Inn ₹2,500 ₹3,100 ₹2,000 20%
Snowline Stay ₹2,200 ₹2,800 ₹1,800 18.1%
Key Observations
  • Hotels offered discounts 3–5 days before Independence Day to lock bookings.
  • Those who booked around Aug 10–12 saved ~20% on accommodation.
  • By Aug 14–15, rates surged back due to high demand from Tier-2 city travelers.

The Actowiz Advantage – Real-Time Travel Scraping

The-Client

All these insights were made possible using Actowiz Solutions’ Travel Scraping Suite, which includes:

1. Flight Fare Scraping API
  • Tracks fare by route, carrier, and device type (desktop/mobile).
  • Supports surge detection logic (e.g., +40% in 24 hours triggers an alert).
  • Exports to CSV or integrates into CRMs for travel companies.
2. Hotel Rate Monitoring Tools
  • Scrapes pricing by star rating, amenities, and cancellation policy.
  • Detects scarcity messages ("only 1 left!", "price drop today!").
  • Enables alerts when competitors change prices or promotions.
3. Travel Intelligence Dashboard
  • Interactive dashboard showing fare & hotel trends over time.
  • Filters by region, holiday, OTA vs. direct rates.
  • Best for sales, pricing, and marketing teams at OTAs or hotel groups.

Business Benefits

Actowiz’s data provided real business value to partners:

Client Type Benefit
Airlines Improved revenue management with surge forecasting
Hotel Chains Filled 20% more rooms with early discount alerts
Travel Agencies Targeted ad campaigns using price-drop signals
Tourism Boards Identified peak routes to promote alternate cities

Conclusion – Surge or Discount?

The-Client

Let’s answer the big question: Was August 2025 a price surge season or a discount window?

Raksha Bandhan (Aug 8):
  • Verdict: Price Surge
  • Flights surged up to 129%; hotels saw 55–65% hikes.
Independence Day (Aug 15):
  • Verdict: Mixed (Early Discounts + Late Surge)
  • Hotels offered early bird deals (~20% off), followed by surge pricing closer to the date.

Client Testimonial

"Actowiz Solutions gave us real-time visibility into airfare and hotel trends during Raksha Bandhan & Independence Day 2025. Their insights helped us adjust pricing, run timely campaigns, and boost bookings across key routes."

— Revenue Manager, Leading OTA

Final Takeaway

The twin festivals of Raksha Bandhan and Independence Day created a volatile travel pricing environment, where the early bird truly caught the deal. Using Actowiz Solutions’ scraping technology and dashboards, travel companies gained the upper hand—anticipating consumer movement, responding to demand in real time, and optimizing pricing strategies.

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:

Fintech / Digital Payments

Result

Accurate daily voucher &

cashback visibility across platforms

★★★★★

“Actowiz Solutions helped us automate daily voucher and cashback data collection across PhonePe, Paytm, Flipkart, and Hubble. The API-driven delivery significantly improved offer accuracy and operational efficiency.”

Product Manager, Fintech Platform (India)

✓ Daily voucher & cashback tracking via Push & Pull APIs

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

Trusted by Industry Leaders Worldwide

Real results from real businesses using Actowiz Solutions

★★★★★
'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"
Thomas Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
Product Image
2 min
★★★★★
“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
Product Image
1 min
★★★★★
“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!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
Product Image
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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