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Ride-Hailing • UAE

Real-Time Ride-Hailing & Mobility Data Scraping in the UAE

The UAE is one of the fastest-growing ride-hailing and mobility markets in the Middle East. From Careem and Uber to local taxi fleets and car-sharing operators like ekar and Udrive, competition is fierce, and fares shift dynamically throughout the day. Surge pricing spikes during events, availability varies across emirates, and rental companies adjust daily pricing based on demand.

Actowiz Solutions provides enterprise-grade ride-hailing and mobility data scraping to help UAE businesses, regulators, and consultants access structured, real-time datasets. From Careem surge in Dubai, Uber fares in Abu Dhabi, to car rental rates in Sharjah, our crawlers capture and deliver clean, business-ready intelligence.

Stay ahead of the UAE ride-hailing market with accurate, scalable, and compliant data feeds.

UAE • Nationwide

Top Countries:

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Electronic-D2C-Apple
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Taxi-Aggregator
Taxi-Aggregator-Uber

Why Ride-Hailing Data Matters in the UAE

Discovery & Setup

Careem & Uber dominate ride-hailing across Dubai, Abu Dhabi, and Sharjah.

Discovery & Setup

Taxis (Dubai Taxi, Abu Dhabi Taxi, Sharjah Transport) still manage large volumes.

Discovery & Setup

Car-sharing operators like ekar and Udrive are growing in demand for hourly rentals.

Discovery & Setup

Car rentals (Thrifty, Hertz UAE, Avis, Dollar Rent a Car) set competitive airport and city rates.

Discovery & Setup

Event-driven spikes: Expo 2020, F1 Abu Dhabi, Dubai Shopping Festival cause fare surges.

With ride-hailing data scraping, UAE businesses can:

Discovery & Setup

Benchmark competitor fares in real time.

Discovery & Setup

Detect surge multipliers during events.

Discovery & Setup

Track car availability and wait times by emirate.

Discovery & Setup

Monitor rental rates & fleet occupancy.

Discovery & Setup

Analyze reviews to improve customer experience.

What We Scrape in UAE Ride-Hailing & Mobility

1
Fare Data
Base fare, per-km/per-minute rates, surge multipliers, service fees.
2
Wait Times
Driver ETA by location & neighborhood.
3
Car Availability
Fleet signals for Careem/Uber, Zipcar-style platforms.
4
Car Rentals
Daily/weekly rental rates, add-ons (insurance, GPS, chauffeur).
5
Car Sharing
ekar, Udrive hourly availability, membership costs, fleet mix.
6
Taxi Apps
Dubai Taxi, RTA Hala Taxi (Careem integration), Abu Dhabi Taxi.
7
Geo Insights
City, emirate, and neighborhood-specific trends.
8
Reviews & Ratings
Google Play, App Store, Careem/Uber feedback, Trustpilot.

High-Impact UAE Use Cases

Discovery & Setup

Surge Pricing Tracking

Events like Dubai Expo, New Year’s Eve at Burj Khalifa, and F1 Abu Dhabi push fares 2–5x higher. Scraping surge multipliers helps operators predict demand and regulators ensure fairness.

Example: During F1, Uber fares in Yas Island surged 4x vs 2x in downtown Abu Dhabi. A consultancy used our scraped data to model demand spikes and optimize transport planning.

Discovery & Setup

Competitive Fare Benchmarking

Careem vs Uber vs Dubai Taxi comparisons highlight price gaps.

Example: In Dubai, a Careem GO trip was 18% cheaper than UberX during off-peak hours, but 20% costlier during peak surges. A mobility operator adjusted discounts accordingly.

Discovery & Setup

Driver Wait Time & Availability

ETAs matter in customer experience.

Example: In Sharjah, Uber wait times averaged 6 minutes, while Careem was 3.5 minutes. Our client used this data to optimize deployment, reducing rider drop-offs by 14%.

Discovery & Setup

Car Rentals & Car Sharing

Car-sharing apps like ekar and Udrive attract younger customers, while rentals dominate airports.

Example: Scraping ekar availability in Dubai Marina showed peak demand during weekends. A rental operator repositioned fleet allocation, boosting utilization.

Discovery & Setup

Geo-Specific Demand Analytics

Mobility demand varies across emirates.

Example: Dubai Downtown saw a 2.5x surge during DSF, while Sharjah stayed flat. This helped operators allocate drivers where demand was highest.

Discovery & Setup

Review & Sentiment Analytics

Reviews reveal service issues like driver cancellations, surge complaints, or app glitches.

Example: Scraping 20,000 Careem app reviews revealed “delayed refunds” as a top issue. The client fixed refund workflows, improving NPS by 21%.

Compliance & Delivery

No personal data

only public listings & fares.

99.9% accuracy

multi-layer QA.

Formats

CSV, JSON, Excel, API feeds.

Delivery

live, hourly, daily.

Support

SLA-backed uptime, 24/7 monitoring.

Industries We Serve in UAE Mobility

Discovery & Setup

Ride-Hailing Platforms

Careem, Uber UAE, startups.

Discovery & Setup

Car Rental Companies

Hertz UAE, Thrifty, Avis, Dollar.

Discovery & Setup

Car-Sharing Operators

ekar, Udrive.

Discovery & Setup

Regulators & RTA Boards

Transport compliance & monitoring.

Discovery & Setup

Consulting & Market Research Firms

UAE mobility insights datasets.

Discovery & Setup

Investors & Analysts

Market forecasting and ROI analysis.

Sample Data Outputs

Date Emirate Platform Route_start Route_end Base_fare Surge_multiplier Wait_time Car_type Rental_rate Availability Review_rating Review_text
05-09-2025 Dubai Careem Downtown Dubai Dubai Marina 25 1.2 5 min Sedan 0 High 4.5 Smooth ride, quick arrival
06-09-2025 Abu Dhabi Uber Corniche Yas Island 30 1.5 8 min SUV 0 Medium 4.7 Comfortable car, bit pricey
05-09-2025 Sharjah Udrive Al Majaz University City 15 1 10 min Hatchback 50 Low 4 Affordable but older car
05-09-2025 Ajman Careem City Center Ajman Beach 18 1 6 min Mini 0 Medium 4.2 Good value for short trips

Geo Coverage – UAE

FAQs – Ride-Hailing & Mobility UAE

We cover all the leading ride-hailing and mobility platforms in the UAE. This includes Careem and Uber UAE for on-demand rides, ekar and Udrive for car sharing, and traditional car rental companies such as Hertz UAE, Thrifty, Avis, Budget, and Dollar Rent a Car. We also scrape taxi booking apps like Dubai Taxi (via Hala Taxi/RTA integration) and Abu Dhabi Taxi. In addition, we can extract public reviews and ratings from sources like the App Store, Google Play, and Google Maps. If your business requires niche or city-specific mobility apps, we can configure custom crawlers to capture those as well. This ensures a comprehensive mobility dataset that reflects fares, surge multipliers, wait times, car availability, and rental trends across Dubai, Abu Dhabi, Sharjah, and beyond.
Yes. Surge pricing is one of the most important factors in UAE ride-hailing. Prices rise sharply during major events like the Formula 1 Grand Prix in Abu Dhabi, New Year’s Eve celebrations near Burj Khalifa, Dubai Shopping Festival, Gitex, and concerts at Expo City. Our real-time crawlers fetch Uber and Careem fare data multiple times per hour, capturing the base fare, surge multiplier, distance/time rates, and any additional charges. By analyzing these data points, businesses can predict demand spikes, design smarter promotions, and allocate drivers more efficiently. Regulators and consultants also use this intelligence to evaluate fare fairness. For example, during Expo 2020, we scraped surge pricing in Dubai Marina vs Downtown Dubai, showing a 3x increase in Marina while Downtown saw a 2x rise.
Absolutely. Ride-hailing trends differ significantly between emirates. In Dubai, areas like Marina, Business Bay, Downtown, JBR, and Deira all show distinct fare and wait time behaviors. In Abu Dhabi, zones like Yas Island, Saadiyat, Corniche, and Khalifa City are hotspots for surge pricing, especially during cultural or sporting events. In Sharjah, demand is more concentrated around University City, Al Majaz, and Al Nahda. We provide emirate-level and neighborhood-level breakdowns that let clients compare pricing, ETAs, and availability side by side. This helps mobility operators and car-sharing companies optimize fleet distribution, target promotions, and plan coverage for high-demand areas.
Yes. Along with fare data, we capture estimated wait times (ETAs) and driver availability where it is displayed publicly. These metrics are valuable because they reveal supply-demand gaps in different areas. For example, in Downtown Dubai, Careem ETAs might average 2–3 minutes, while in Sharjah University City, the wait may be 6–7 minutes. An operator can use this data to improve deployment, reducing cancellations and abandoned rides. In one case, a consulting firm used our scraped ETAs to identify underserved zones in Abu Dhabi, then advised its client to add more drivers in those neighborhoods, reducing rider wait times by 18% and improving customer satisfaction.
Yes. We scrape car-sharing platforms like ekar and Udrive, capturing hourly availability, membership fees, trip rules, and fleet mix (sedans, SUVs, electric cars). For car rental companies (Hertz, Avis, Thrifty, Budget, Dollar UAE), we track daily and weekly rates, add-ons (insurance, child seats, GPS), and airport vs. city pricing. Many of our clients use this data to benchmark their pricing against competitors, identify gaps between car sharing and rentals, and optimize fleet allocation. For example, scraping Udrive’s availability in Dubai Marina revealed weekend demand spikes, which helped a rental operator reposition its fleet to capitalize on short-term bookings.
We maintain 99.9% accuracy through multi-layer quality checks. Every dataset undergoes validation to ensure fields like fare, surge multiplier, and ETA are correctly captured. We run schema checks, range checks, and deduplication to avoid errors. Automated retry systems re-run failed scrapes to maintain continuity, especially during high-demand times when apps are under heavy load. Our clients receive error reports, run logs, and row counts so they can trust the reliability of the dataset. For instance, when we scraped 50,000 Careem rides in Dubai over a month, our QA workflows ensured every record was tied to the correct route, time, and pricing category.
Ride-hailing and mobility apps often have advanced security measures, but our crawlers are designed to manage them. We use rotating residential proxies, headless browsers, device fingerprinting, and human-like browsing patterns (random clicks, delays, and scrolls) to reduce detection risks. Our parsers are AI-driven and auto-adjust if an app changes its design or layout. From a compliance perspective, we only scrape publicly available data and avoid personal or sensitive information (PII). We respect platform guidelines where applicable and can align our scraping cadence with your legal team’s recommendations. For UAE-specific projects, we ensure all data is compliant with local standards.
Yes, depending on platform visibility. We can provide historical backfills for fares, rentals, or reviews where archives are available. In other cases, we begin forward data collection, building a custom dataset for future use. Many UAE clients request event-tagged time series (Expo 2020, F1 Abu Dhabi, Ramadan nights, Dubai Shopping Festival) to study fare surges, rental demand, and car-sharing trends during specific periods. For example, we scraped Uber and Careem surge pricing during New Year’s Eve at Burj Khalifa over three years, creating a benchmark dataset that helped clients forecast demand and plan driver incentives.
We deliver in all common formats: CSV, Excel, JSON, and Parquet. Delivery methods include secure API feeds, cloud storage (AWS S3, Google Cloud, Azure), and SFTP transfers. Frequency depends on your requirements: live streams, every 15 minutes, hourly, daily, or weekly. We can also integrate with popular BI tools like Power BI, Tableau, Looker, and Google Data Studio, so your team can view dashboards instantly. One Dubai client integrated our Uber surge data feed into Tableau, creating heatmaps of surge multipliers by neighborhood, which guided both marketing promotions and fleet management.
Starting a pilot is straightforward:
  • Define Scope → Identify which apps (Careem, Uber, ekar, etc.), emirates, routes, and fields (fares, surge, ETAs, rentals) you need.
  • Get a Free Sample → We provide a short dataset (e.g., 100 Careem rides in Dubai or 50 ekar availabilities in Sharjah).
  • Pilot Phase (2–4 weeks) → We run crawlers at limited scale to validate accuracy, formats, and cadence.
  • Scale Up → Move to full production with hourly/daily scrapes, SLA-backed delivery, and 24/7 support.
Most clients begin with Dubai and Abu Dhabi pilots (airport routes, city center demand) and later expand to Sharjah, Ras Al Khaimah, and Fujairah. This phased approach ensures accuracy, compliance, and ROI from day one.

Case Study

Industry:

Travel & Ride-Hailing – UAE

Result

Up to 28% Reduction in Ride-Hailing Fare Volatility & 35% Faster Travel Insights for UAE Businesses

★★★★★

“Actowiz Solutions helped us track surge fares, taxi pricing, and rental availability across Careem, Uber, Ekar, and Udrive in Dubai, Abu Dhabi, and Sharjah. With real-time ride-hailing and mobility data scraping insights, we reduced fare volatility by 28%, improved price-matching algorithms, and enabled faster reporting—achieving a 35% boost in UAE travel trend analysis and better forecasting during peak demand events.”

Head of Operations , UAE Mobility Sector

✓ 28% reduction in ride-hailing fare volatility

✓ 35% faster market insights and reporting

✓ Improved demand forecasting during surge-pricing events

Organic Tattva 1 01
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                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.155
                    [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] => 216.73.216.155
                    [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
)

Start Your Project

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Additional Trust Elements

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🔒 "Your data is secure with us. NDA available."

💬 "Average Response Time: Under 12 hours"

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

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Real results from real businesses using Actowiz Solutions

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Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
Product Image
2 min
★★★★★
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Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
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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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Blog
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Feb 19, 2026

Scraping Aqualite UK with Python - BeautifulSoup vs Selenium - Choosing the Right Approach for Data Extraction

Scraping Aqualite UK with Python - BeautifulSoup vs Selenium compares speed, accuracy, and scalability to choose the best scraping method.

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Costco Walmart Grocery Pricing Scraping – Geo-Based Real-Time Houston

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Amazon Sports And Fitness Market Analysis - Key Insights From Our Analysis Of 1896 Products

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Scraping Aqualite UK with Python - BeautifulSoup vs Selenium - Choosing the Right Approach for Data Extraction

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How Pedidosya Food Data Extraction Covers All Cities and Categories for Smarter Market Insights

Boost insights with Pedidosya Food Data Extraction. Access all cities and categories to track trends, menus, and customer preferences efficiently.

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Feb 17, 2026

How to Solve Stock and Pricing Challenges with Zara Price & Inventory Monitoring with AI-Based Web Scraping

Track Zara product prices and stock efficiently with Zara Price & Inventory Monitoring with AI-Based Web Scraping, ensuring accurate, real-time retail insights.

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Costco Walmart Grocery Pricing Scraping – Geo-Based Real-Time Houston

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Apartments.com Inventory Scraping Houston 2026 – Lead Generation for Real Estate

Houston apartment inventory scraping from Apartments.com for 2026. Generate verified rental leads with structured data and real-time insights by Actowiz Solutions.

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How We Solved Real-Time Competitive Monitoring Challenges with AI-Based Zara Fashion Product Scraping for a Retail Client

AI-powered Zara product scraping enabled real-time competitive insights, automated tracking, and improved pricing decisions for our retail client.

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Comparing Medicine Prices in Mumbai vs Delhi Using Real-Time 1mg Data

Comparing medicine prices in Mumbai vs Delhi using real-time 1mg data to analyze price differences, availability, and savings across cities.

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Amazon Sports And Fitness Market Analysis - Key Insights From Our Analysis Of 1896 Products

Amazon Sports And Fitness Market Analysis covering pricing trends, competition insights, and key findings from 1896 products.

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Gap vs American Eagle Data Scraping – The Financial Giant vs. The Physical Leader Divide

Gap vs American Eagle Data Scraping reveals e-commerce trends, sales performance, and market gaps between the financial giant and physical leader.

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Sephora vs Ulta Beauty Data Scraping Comparison - Extracting Prices, Ratings & Trends at Scale

In-depth research report comparing Sephora and Ulta Beauty data scraping, analyzing prices, ratings, product trends, and competitive insights at scale.