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GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => 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
                        )

                )

            [continent] => Array
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                    [code] => NA
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                        (
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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
                        )

                )

            [country] => Array
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                    [iso_code] => US
                    [names] => Array
                        (
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                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [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
                    [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
                        )

                )

            [subdivisions] => Array
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                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
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                                    [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] => 216.73.216.213
                    [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
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                    [0] => en
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            [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
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            [validAttributes:protected] => Array
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                    [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] => 216.73.216.213
                    [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
)
Navratri Mega Sale Price Tracking

Introduction

Private travel clubs and membership-only booking communities offer exclusive rates to their users. But to prove the value of those exclusive deals, they must show members how their discounted prices compare with public OTA retail rates on platforms such as:

  • Booking.com
  • Expedia
  • Hotels.com
  • Agoda
  • Trip.com

One private travel club approached Actowiz Solutions with a clear requirement:

“We want to show our members a side-by-side comparison between our discounted member rates and the public retail rates on OTAs — automatically, accurately, and in real time.”

This case study explains how Actowiz designed a Retail Rate Comparison API that lets closed user groups highlight their savings and build trust by benchmarking their member pricing against live OTA prices.

Client Background

Navratri Mega Sale Price Tracking

The client operates a closed, invite-only travel membership program. They offer discounted hotel rates through:

  • Direct partnerships
  • Wholesale inventory
  • Negotiated contracts

Their users expect significant savings compared to Booking.com, Expedia, and other OTAs. But the challenge was proving this value within the platform.

To strengthen transparency and trust, the client wanted:

  • Live retail OTA price comparison
  • Property-level and date-specific benchmarking
  • Clean data delivered through API
  • High accuracy and frequency
  • Multi-country support

Key Challenges

3.1 Need for Real-Time Retail Rates

OTA prices change constantly based on:

  • Date
  • Occupancy
  • Cancellation policy
  • Availability
  • Promotions

The client needed fresh daily or on-demand rates.

3.2 Multi-OTA Benchmarking Required

A single OTA comparison wasn’t enough. They needed prices across:

Each OTA structures prices differently, requiring normalization.

3.3 Room-Level Matching

Different OTAs list:

  • Slightly different room names
  • Different inclusions (breakfast / no breakfast)
  • Different tax policies
  • Varying cancellation rules

A mapping logic was required to match equivalent room types.

3.4 “Total Price” Matters — Not Just Nightly Rate

Travelers make decisions based on:

  • Room rate
  • Taxes
  • Resort fees
  • Service charges
  • Extra adult fees
  • Promotions

Actowiz had to compute the out-the-door total price for accurate comparisons.

3.5 White-Label API Integration

The travel club needed:

  • A backend-only solution
  • Clean JSON output
  • Integration into their existing UI
  • No heavy dashboards unless required

Actowiz Solutions – Proposed Architecture

Actowiz designed a Retail Rate Comparison API that:

  • Fetches OTA prices for specified dates
  • Normalizes tax & fee structures
  • Maps room categories
  • Computes total payable price
  • Compares member rates vs retail rates

This powers transparent value demonstration for travel clubs.

Solution Breakdown

5.1 Input Options for the API

The platform can send any of the following:

  • Hotel ID or URL from Booking.com / Expedia / Agoda
  • Check-in & check-out dates
  • Number of guests
  • Room type (optional)
  • Currency preference

The Actowiz API returns:

  • Public OTA retail rates
  • Structured comparison
  • Content metadata
5.2 Multi-OTA Retail Rate Scraping

For each property and date, Actowiz extracts:

  • Base nightly rate
  • Taxes
  • Fees
  • Promotions
  • Refundable / non-refundable price
  • Breakfast inclusion (yes/no)
  • Cancellation rules
  • Availability status

Supported platforms include:

  • Booking.com
  • Expedia
  • Agoda
  • Hotels.com
  • Trip.com
  • Others on request
5.3 Room-Level Normalization

Since OTAs label rooms differently:

  • “Deluxe King Room Sea View”
  • “King Deluxe Oceanfront”
  • “Premium Sea-Facing Room”

Actowiz built a machine-assisted room matching engine that identifies equivalent room types across OTAs.

5.4 Total Out-the-Door Pricing

Actowiz calculates:

Final Price = (Room Rate × Nights) + Taxes + Fees

The output includes both:

  • Nightly rate
  • Total cost

This ensures accurate apples-to-apples comparison.

5.5 API Output Format

The API returns:

  • Per OTA
  • OTA name
  • Total price
  • Price breakdown
  • Room type
  • Cancellation policy
  • Availability
  • Currency
  • Comparison Summary
  • Member price
  • Lowest OTA retail price
  • Savings percentage
  • Savings amount

Example summary:

"You saved 28% compared to public OTA retail rates."

5.6 Update Frequency Options
  • Real-time fetch
  • Hourly
  • Daily
  • On-demand triggers

Sample Output (Illustration)

Member vs OTA Retail Price Comparison
Room Type Member Price Booking.com Expedia Agoda Cheapest Retail Savings
Deluxe Sea View $129 $178 $185 $174 $174 26%
Overwater Villa $399 $512 $498 $525 $498 20%
Garden Bungalow $88 $110 $104 $112 $104 15%

This is exactly the visual story the travel club wanted its members to see.

Business Impact

7.1 Stronger Member Trust & Transparency

Members see:

  • Their exclusive rate
  • Public retail pricing
  • Exact savings

This dramatically increases trust and perceived value.

7.2 Higher Conversion Rates

Clear OTA comparisons drive more bookings:

  • “I’m getting a better deal here.”
  • “Savings are visible and proven.”

This boosted conversions for the client.

7.3 Automated, Scalable Solution

Before Actowiz:

  • They manually checked prices
  • Could not keep up with dynamic changes

After Actowiz:

  • Fully automated
  • Real-time accuracy
  • Unlimited properties & dates
7.4 Ability to Expand Globally

The client extended usage to:

  • Southeast Asia
  • Europe
  • US hotels
  • Middle Eastern resorts

Actowiz supports data from any geographic region.

Why Actowiz for Private Travel Club Price Comparison?

  • Deep OTA scraping expertise
  • Accurate room-level price mapping
  • Global property coverage
  • API-first architecture
  • Support for all major OTAs
  • High scalability
  • Custom pricing models
  • Fast deployment

Actowiz enables closed travel clubs to prove member savings with confidence.

Conclusion

Closed membership travel platforms must demonstrate their value clearly and transparently.

By building an automated multi-OTA retail rate comparison API, Actowiz empowered the client to:

  • Show real savings
  • Build trust
  • Improve retention
  • Increase bookings
  • Scale their travel inventory globally

The system is fully customizable and can power any:

  • Private travel club
  • Wholesale travel platform
  • Closed-user group
  • Staff benefit program
  • Loyalty membership system

Actowiz delivers real-time OTA retail rate intelligence that matches modern travel expectations.

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

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

Actowiz Insights Hub

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