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GeoIp2\Model\City Object
(
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                (
                    [geoname_id] => 4509177
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                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
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                            [zh-CN] => 哥伦布
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
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            [traits] => Array
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    [continent:protected] => GeoIp2\Record\Continent Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [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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                )

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            [validAttributes:protected] => Array
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    [country:protected] => GeoIp2\Record\Country Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [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
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            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
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            [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
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
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                (
                    [ip_address] => 216.73.216.150
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                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
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                    [8] => isHostingProvider
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                    [11] => isPublicProxy
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                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
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                    [19] => staticIpScore
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                )

        )

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

                )

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            [validAttributes:protected] => Array
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        )

    [location:protected] => GeoIp2\Record\Location Object
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            [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
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                )

        )

    [subdivisions:protected] => Array
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            [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
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                    [validAttributes:protected] => Array
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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
)
Navratri Mega Sale Price Tracking

Executive Summary

The Dubai real estate market is currently experiencing a historic surge, with off-plan sales accounting for 62.6% of all transactions in 2025, totaling over AED 293 billion. However, for institutional investors and global brokerages, the market remains highly decentralized. Data on new launches, floor plans, and payment schedules is buried within the individual websites of dozens of developers like Emaar, DAMAC, Sobha, and Nakheel.

Actowiz Solutions was approached by a multinational real estate consultancy to build a unified, real-time data warehouse. The goal was to aggregate and normalize off-plan property data from over 50 developer websites, transforming disparate PDFs and interactive maps into a structured, queryable database.

The Challenge: A Fragmented Digital Landscape

Navratri Mega Sale Price Tracking

In Dubai’s rapid-fire "Launch Culture," a new project can sell out within hours. Our client struggled with three core data issues:

  • Non-Standardized Formats: One developer might list "3-Bedroom Villas" while another lists "Type B Townhouses," making direct comparison impossible without manual intervention.
  • Dynamic Inventory: "Sold Out" or "Limited Units Remaining" statuses change minute-by-minute across 50+ different portals.
  • The Payment Plan Puzzle: Dubai is famous for varied payment structures (e.g., 60/40, 80/20, or post-handover plans).1 Extracting these from embedded images and brochures was a massive technical hurdle.

The Solution: Actowiz Solutions’ Unified Property Scraper

Actowiz Solutions developed a custom Enterprise Web Scraping architecture specifically for the Middle Eastern real estate sector.

A. Multi-Modal Data Extraction

We didn't just scrape text. Our bots were designed to:

  • Extract Brochure Data: Use AI-based OCR (Optical Character Recognition) to pull payment plans and specifications from downloadable PDFs.
  • Monitor "Booking Status": Track interactive site maps on developer portals to detect real-time unit availability.
  • Geo-Tagging: Automatically assign GPS coordinates to projects based on community names (e.g., Dubai South, JVC, Palm Jebel Ali).
B. The "Master SKU" Normalization

To make the data useful, Actowiz developed a normalization engine that converted all disparate developer data into a single Master Property Schema. This ensured that a "Standard Apartment" in Business Bay could be accurately benchmarked against one in Dubai Creek Harbour.

C. High-Frequency Monitoring

Given the volatility of Dubai’s off-plan market, our scrapers were set to run at 4-hour intervals, ensuring the client was alerted to "Sold Out" statuses or new price tranches before the general public.

Sample Data Architecture

Below is a representation of the structured data provided daily by Actowiz Solutions to the consultancy.

Project Name Developer Community Unit Type Starting Price (AED) Payment Plan Handover Date Inventory Status
The Oasis Emaar Dubailand 4BR Villa 8,500,000 80/20 Q4 2028 15 Units Left
Verde Sobha JLT 2BR Apt 2,100,000 60/40 Q2 2027 Sold Out
Damac Casa DAMAC Al Sufouh 1BR Apt 2,500,000 80/20 Q1 2028 40% Remaining
Palm Beach Nakheel Palm Jebel Ali 5BR Villa 18,700,000 70/30 Q4 2027 Launch Soon

Key Insights for the Dubai Market (2025-2026)

By centralizing data through Actowiz Solutions, the client identified several market-moving trends:

  • The Rise of Dubai South: Data showed a 12% increase in developer activity in Dubai South following announcements of expanded airport infrastructure, allowing the client to pivot their investment strategy early.
  • Payment Plan Aggression: Our "Payment Plan Tracker" revealed that mid-tier developers were offering Post-Handover Payment Plans (PHPP) to compete with larger developers, which directly correlated to faster absorption rates in areas like Jumeirah Village Circle (JVC).
  • Price Discrepancy Alerts: The system flagged instances where secondary market "assignments" (resales of off-plan units) were priced lower than the developer's final tranche, providing a lucrative "arbitrage" opportunity for the fund.

Why Actowiz Solutions?

Actowiz Solutions provided a level of precision that off-the-shelf tools could not match:

  • Bypassing JavaScript Heavy Sites: Many Dubai developers use heavy React/Angular sites; our Headless Browser technology ensured full data capture.2
  • Arabic to English Translation: Our NLP models automatically translated project details from Arabic-only marketing materials into English.
  • API Readiness: Data was delivered via a JSON API, allowing the client to feed the information directly into their mobile app for end-customers.

Visualizing the Dubai Skyline Growth

The following image represents the density of off-plan launches tracked by Actowiz Solutions across Dubai's major investment corridors.

Caption: Actowiz Solutions tracks new project launches across 50+ developer portals to provide a 360-degree view of the Dubai skyline's evolution.

Conclusion

In a market as fast-moving as Dubai, relying on manual data entry is a strategic failure. Actowiz Solutions provided the technical backbone for our client to see every new brick, every new price point, and every new payment plan across the entire city. By aggregating data from 50+ developers, we empowered our client to move from "searching for data" to "making decisions."

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

Actowiz Insights Hub

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

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