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GeoIp2\Model\City Object
(
    [city:protected] => GeoIp2\Record\City Object
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                    [0] => confidence
                    [1] => geonameId
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 4509177
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                            [en] => Columbus
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                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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        )

    [location:protected] => GeoIp2\Record\Location Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
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                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
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            [validAttributes:protected] => Array
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                    [0] => code
                    [1] => confidence
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [code] => 43215
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    [subdivisions:protected] => Array
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            [0] => GeoIp2\Record\Subdivision Object
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                            [0] => confidence
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                            [2] => isoCode
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                            [0] => en
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                    [record:GeoIp2\Record\AbstractRecord:private] => 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
                                )

                        )

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        )

    [continent:protected] => GeoIp2\Record\Continent Object
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                    [0] => code
                    [1] => geonameId
                    [2] => names
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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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
                            [ja] => 北アメリカ
                            [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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            [validAttributes:protected] => Array
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                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
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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
                            [ja] => アメリカ
                            [pt-BR] => EUA
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                            [zh-CN] => 美国
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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            [validAttributes:protected] => Array
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                    [0] => queriesRemaining
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
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                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [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
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        )

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

            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
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            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
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                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
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                    [13] => isSatelliteProvider
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                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [network] => 216.73.216.0/22
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    [raw:protected] => Array
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                            [de] => Columbus
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                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                )

            [continent] => Array
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                    [geoname_id] => 6255149
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                            [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
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                )

            [country] => Array
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                            [de] => USA
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                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [location] => Array
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                    [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
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
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                        (
                            [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
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                )

            [subdivisions] => Array
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                    [0] => Array
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                            [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
                                )

                        )

                )

            [traits] => Array
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                    [ip_address] => 216.73.216.110
                    [prefix_len] => 22
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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
)

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How Multi-Site Web Scraping Unlocked Hidden Market Trends for Strategic Positioning

Discover how Actowiz Solutions used web scraping to uncover market trends and competitor pricing insights for strategic business decisions.

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Real-Time Regional Insights with Customizable E-commerce Dashboards

Introduction: The Data Gap in Market Strategy

In today’s digital-first landscape, market success depends heavily on real-time intelligence. For one fast-scaling eCommerce client, traditional market research couldn’t keep pace with shifting consumer preferences and competitor strategies. The company approached Actowiz Solutions, a leader in web scraping and data intelligence, to extract actionable insights from 5 competitive platforms.

Client Objective

The-Client

The client needed to:

  • Monitor product listings and specifications across competing platforms
  • Extract real-time competitor pricing
  • Analyze customer reviews to detect sentiment trends
  • Generate weekly trend reports for internal product and pricing teams

Challenges Identified

The-Client
1. Multiple Platforms with Varying Structures

Each target website (including Amazon, Walmart, and niche vertical-specific competitors) had unique HTML/CSS layouts and used dynamic rendering, making uniform data extraction complex.

2. Data Volume and Freshness

With thousands of SKUs and pricing updates occurring daily, speed and frequency were crucial.

3. Review Sentiment Complexity

Extracting not just star ratings but also sentiment-rich insights from unstructured review text was a top priority.

Actowiz Solutions' Web Scraping Strategy

Actowiz deployed a custom scraping pipeline using Python (Scrapy + Selenium) with cloud-based proxy rotation and anti-bot bypass mechanisms to collect real-time data.

Data Sources
  • Amazon (Product data, reviews, price trends)
  • Walmart (Product listings, stock availability)
  • Target (Consumer sentiment and competitive pricing)
  • Two niche industry sites (High-conversion products and upcoming SKUs)
Scraping Frequency
  • Price & product data: Hourly
  • Customer reviews: Daily
  • Sentiment summaries: Weekly reports
Sample Scraped Data Snapshot
Website Product Name Price Avg Rating Stock Review Sentiment
Amazon EcoSmart LED Bulb $14.99 4.5 In Stock Positive
Walmart Philips Hue Light $18.50 4.2 In Stock Mixed
Target GE Smart Bulb $12.99 3.8 Out of Stock Negative
Niche 1 Zigbee Hub $39.99 4.6 In Stock Positive

Data Processing & Intelligence

Once collected, Actowiz transformed the raw HTML into a structured format using:

  • Pandas for tabular conversion
  • NLTK & VADER for review sentiment tagging
  • Power BI for visual dashboards
  • Cloud-based delivery via REST API and scheduled CSV reports

Impact: Market Intelligence to Strategic Positioning

1. Pricing Optimization

The client discovered that 21% of their products were priced at least 8–10% higher than direct competitors. They implemented dynamic pricing, which increased conversion rates by 12.4% within 30 days.

2. SKU Alignment

Using scraped competitor product data, the client identified 12 high-velocity SKUs they weren’t offering. These were added to their catalog, resulting in a 17% increase in sales for the new product line.

3. Sentiment Trends on Reviews

Actowiz’s sentiment analysis of 25,000+ reviews revealed that “packaging issues” and “late delivery” were trending negatives for a top competitor. The client used this insight to prioritize faster shipping and eco-packaging—leading to a 9% boost in repeat purchases.

Visual Snapshot: Review Sentiment Breakdown

Sentiment Category Percentage
Positive 62%
Mixed 18%
Negative 20%

Most frequently mentioned keywords in reviews: “value for money,” “delivery delay,” “packaging damage”

Strategic Dashboard: Weekly KPI Insights

  • Top Competitor Pricing Variance (vs Client Median):
    • Amazon: -6.4%
    • Walmart: -8.9%
    • Niche Site 1: -3.1%
  • Weekly SKU Monitoring:
    • 2,500+ tracked products
    • 85% data accuracy within the first scrape cycle
    • 1.2 million records processed monthly

Technology Stack

Component Tools Used
Scraping Engine Python, Scrapy, Selenium
Proxy Handling Luminati, Bright Data
Review Sentiment NLTK, TextBlob, VADER
Data Delivery REST API, Amazon S3
Visualization Power BI, Excel Dashboards

Client Testimonial

“Actowiz Solutions didn’t just give us data—they gave us market vision. Their scraping strategy helped us course-correct product pricing and stay three steps ahead of competitors.”

– VP, Product Strategy (Client)

Interested in similar insights for your brand?

Contact Actowiz Solutions today to build your custom market intelligence engine powered by robust, scalable web scraping.
Contact Us Today!

Conclusion: The Power of Web Scraping in Market Strategy

This project proves that multi-site web scraping isn’t just a data collection task—it’s a strategic imperative. With Actowiz Solutions, the client turned fragmented online data into a competitive roadmap.

As markets become more dynamic, businesses that invest in data scraping for competitor pricing, product intelligence, and customer sentiment will always gain the edge.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape → Structure → Analyze → Visualize
Explore Solutions Get a Custom Demo

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.

Ecommerce
Q-Commerce
Travel & OTA
Food Delivery
Real Estate
Social Media
Trusted by Global Leaders – Secured by International Standards

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 & palniring

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 inights Top-slling SKUs

Request Demo Access icon

Our Data Drives Impact - Real Client Stories

Blinkit | India (Relail Partner)

"Actow's helped us reduce out of ststack 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

"Actow's helped us reduce out of ststack 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

All
Blog
Case Studies
Infographics
Report
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Discounted Devotion? Janmashtami Offer Mapping Across Quick Commerce Platforms

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Grocery Discount Trends from Toters, JOKR, and Getir – Regional Analysis

Explore Toters, JOKR & Getir grocery discounts across regions—data insights, trends, and strategic analysis by Actowiz Solutions.

Aug 07, 2025

How to Track Weekly Flipkart Electronics Prices for Smarter Pricing Decisions & Competitive Edge?

Track weekly Flipkart electronics prices to stay competitive, adjust pricing smartly, and make data-driven decisions that boost visibility and conversions.

Read More
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Track Janmashtami Quick Commerce Banner Leaders – Dairy, Mithai & Puja Brands Insights

Discover which dairy, mithai & puja brands led Janmashtami quick commerce banners with Actowiz Solutions’ visibility scores & festive promotions insights.

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Price Tracking of Rakhi Gift Hampers – Did Discounts Really Deliver Value?

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Real-Time Ride Fare Comparison: Uber vs DiDi vs Bolt Across 7 Countries

Compare Uber, DiDi & Bolt ride fares across 7 countries with real-time scraping insights. Discover surge patterns, price differences & platform efficiency globally.

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India's Holiday Travel Surge Raksha Bandhan to Independence Day 2025

Explore India's holiday travel trends during the 2025 festive season—from Raksha Bandhan to Independence Day. Discover top destinations, travel tips, and booking insights.

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2025 Buying Behavior Trends: Smarter Retail Decisions Backed by Data

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Real-Time Price Monitoring & Benchmarking on Amazon & Walmart for Smarter eCommerce

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🇮🇳 India: Independence Day Sale Price Mapping – Flipkart vs Amazon

Actowiz Solutions compares Flipkart & Amazon prices during India’s Independence Day Sale 2025. Discover top deals, price drops & brand discount trends.
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Lazada Grocery App Dataset Analysis - Market Intelligence & Grocery Delivery Trends for American Startups

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Raksha Bandhan & Independence Day 2025: How Holiday Travel Surges Impacted Flight and Hotel Pricing in India

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