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Actowiz Metrics Now Live!
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Actowiz Metrics Now Live!
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Actowiz Metrics Now Live!
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Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
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Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
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Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
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Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
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Actowiz Metrics Now Live!
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GeoIp2\Model\City Object
(
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                            [pt-BR] => Columbus
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            [traits] => Array
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    [continent:protected] => GeoIp2\Record\Continent Object
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                            [fr] => Amérique du Nord
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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    [country:protected] => GeoIp2\Record\Country Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [iso_code] => US
                    [names] => Array
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                            [de] => USA
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                            [pt-BR] => EUA
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                            [zh-CN] => 美国
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        )

    [locales:protected] => Array
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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                )

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

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

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            [validAttributes:protected] => Array
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [ip_address] => 216.73.216.155
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
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                    [15] => mobileCountryCode
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                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
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                            [en] => Columbus
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                            [fr] => Columbus
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                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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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
                (
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                    [latitude] => 39.9625
                    [longitude] => -83.0061
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                    [time_zone] => America/New_York
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            [validAttributes:protected] => Array
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        )

    [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
        (
            [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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                            [0] => en
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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
)
Case-Study-Enhancing-Betting-Predictions-with-Real-Time-ESPNcricinfo-Data-Scraping-Solutions

Introduction

In the rapidly evolving world of Q-commerce, pricing agility and real-time insights can make or break sales performance. As fashion e-commerce brands face constant competition and fluctuating market dynamics, leveraging advanced tools to monitor pricing and competitor behavior has become critical. Actowiz Solutions partnered with a leading online fashion retailer to implement a robust Real-Time Competitive Monitoring solution that enabled intelligent, data-driven decisions. This system transformed how the client approached price positioning, campaign timing, and product visibility, ultimately optimizing their strategy for greater sales performance in the quick-commerce landscape.

The Client

The client is a prominent name in the online fashion retail industry, selling trendy apparel and accessories across top Q-commerce and marketplace platforms. Known for its fast-moving inventory and competitive pricing, the brand was seeking better insights into market trends, competitor strategies, and real-time shifts in consumer engagement. Despite a strong product portfolio and presence on multiple platforms, the brand lacked an integrated solution to track competitor prices and their own product performance. They turned to Actowiz Solutions for an end-to-end Real-Time Competitive Monitoring system tailored to the fashion e-commerce ecosystem.

Key Challenges

Key-Challenges

The client’s primary challenge was the absence of visibility into competitor pricing and promotions, which impacted their ability to react quickly and maintain a competitive edge. Frequent manual audits were time-consuming and prone to delays, making it difficult to execute Continuous Price Optimization or manage Dynamic Pricing for Fashion Retail. Additionally, they lacked granular insights into their product performance metrics across platforms, especially in terms of E-commerce Share of Search Tracking and Real-Time Market Share Analysis . Their team also struggled to differentiate between Sponsored vs Organic Listings Tracking, limiting the effectiveness of their advertising spend. This lack of clarity affected their Fashion Retail Competitive Intelligence and inhibited effective Conversion Rate Optimization E-commerce efforts. Without actionable data, their strategies were reactive rather than proactive, affecting both visibility and margins in an increasingly aggressive market.

Key Solutions

Key-Solutions

Actowiz Solutions deployed a customized Real-Time Competitive Monitoring system that integrated data from all relevant Q-commerce platforms in one unified dashboard. This tool provided continuous updates on competitor pricing, enabling swift and informed pricing decisions. Our system supported automated Competitor Price Monitoring and allowed the brand to adapt pricing in real-time based on market trends. We introduced E-commerce Visibility Improvement tools, helping the client understand how often their products appeared in top search results. Detailed performance metrics made it easy to identify gaps in visibility and fix them with strategic listings optimization. Additionally, our solution offered insights into Fashion E-commerce Optimization trends, enabling the client to align their inventory and promotional tactics with what was currently resonating in the market. Enhanced tracking of Sponsored vs Organic Listings further helped refine their ad strategies, while advanced analytics supported decisions for maximizing Conversion Rate Optimization E-commerce efforts.

Client Testimonial

"Actowiz Solutions’ Real-Time Competitive Monitoring transformed how we manage pricing and promotions across Q-commerce platforms. The clarity and speed we gained have been game-changers. Our visibility improved significantly, and our teams are now empowered to respond to market changes instantly. We finally have a competitive intelligence system that gives us the control we need in such a dynamic space."

—Head of Digital Strategy

Conclusion

The implementation of Actowiz Solutions' Real-Time Competitive Monitoring platform gave the client a strategic advantage in the fast-paced Q-commerce sector. By enabling real-time insights, better pricing decisions, and performance tracking, the brand successfully optimized its operations for growth. With tools for Fashion Retail Competitive Intelligence , visibility enhancement, and data-backed pricing strategy, they turned challenges into opportunities. This case highlights the immense value of real-time data in navigating modern fashion e-commerce.

Ready to dominate the digital shelf with competitive insights? Contact Actowiz Solutions to build your real-time monitoring system today.

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
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                )

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                        (
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                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

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                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

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                            [ru] => США
                            [zh-CN] => 美国
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                                    [fr] => Ohio
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                                    [pt-BR] => Ohio
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    [continent:protected] => GeoIp2\Record\Continent Object
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                            [ja] => 北アメリカ
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                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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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
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                            [pt-BR] => EUA
                            [ru] => США
                            [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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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 6252001
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                            [de] => USA
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [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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        )

    [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
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                    [11] => isPublicProxy
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                    [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
                (
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                    [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
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                    [validAttributes:protected] => Array
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                            [0] => confidence
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                            [2] => isoCode
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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
)

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

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.
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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
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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
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1 min

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

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

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

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & planning

Monitor Prices, Availability & Trends -Live Across Regions

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

✔ Scraped Data: Price Insights Top-selling SKUs

Our Data Drives Impact - Real Client Stories

Blinkit | India (Retail Partner)

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

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

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

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

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

✔ Scraped Data, SKU availability, delivery time

Actowiz Insights Hub

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

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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

Geo-based real-time grocery pricing scraping for Costco and Walmart in Houston. Boost retail intelligence with Actowiz Solutions data APIs.

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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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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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Feb 18, 2026

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

Geo-based real-time grocery pricing scraping for Costco and Walmart in Houston. Boost retail intelligence with Actowiz Solutions data APIs.

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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.