Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
 
GeoIp2\Model\City Object
(
    [city:protected] => GeoIp2\Record\City Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [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
                        )

                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [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
                                )

                        )

                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [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
                        )

                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [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:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

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

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [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
                        )

                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

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

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [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
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.110
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

        )

    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [continent] => Array
                (
                    [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
                        )

                )

            [country] => 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
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
                (
                    [code] => 43215
                )

            [registered_country] => 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
                        )

                )

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

                        )

                )

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

        )

)

 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

+1 ▼
  • Home
  • Work
  • Optimizing Inventory & Delivery with Data Scraping – Actowiz Solutions

Case Study: How Actowiz Solutions Helped a U.S. Retailer Optimize Inventory Sync, Delivery Times, and Warehouse Planning

Actowiz Solutions helped a U.S. retailer sync inventory, improve delivery times, and optimize warehouse planning with real-time Amazon & Walmart scraping.

Download Case Studies

✓ Valid

Note: You’ll receive it via email shortly after submitting the form.

Real-Time Regional Insights with Customizable E-commerce Dashboards

Client Overview

  • Client Name: Confidential (U.S.-based mid-sized omnichannel retailer)
  • Industry: Retail – Electronics & Home Goods
  • Location: Operations across Illinois, Indiana, and Michigan
  • Channels: Online store, Amazon Seller Central, Walmart Marketplace, 6 physical stores
  • Duration: 6 months (2024 Q3–Q4)
  • Data Partner: Actowiz Solutions

Business Challenge

The-Client

The client faced three major operational bottlenecks:

1. Inventory sync issues between their online platforms (Amazon, Walmart, internal eCommerce) and physical stores.

2. Unpredictable delivery times leading to low customer satisfaction and frequent returns.

3. Inefficient warehouse utilization, with either overstock or unfulfilled demand in key cities like Chicago and Indianapolis.

They needed a real-time, automated solution to monitor inventory levels and delivery performance across Amazon Fulfillment Centers and Walmart store networks.

Actowiz Solutions Approach

Actowiz Solutions deployed an integrated data scraping system to collect and process:

  • SKU-level inventory data from Amazon.com (FBA) and Walmart.com
  • ZIP-code-based delivery time estimates
  • Warehouse restock timelines
  • Localized stock availability in nearby cities

    • This data was synced via a custom dashboard and API into the client’s ERP and warehouse management systems for automated decision-making.

    Step 1: Inventory Sync with Amazon & Walmart

    We built custom SKU-matching crawlers to extract the following data from Amazon and Walmart daily:

    Platform SKU Stock Status Fulfilled By Price (USD) ETA (ZIP 60601)
    Amazon ELEC-BX101 In Stock Amazon FBA 49.99 1 Day
    Walmart ELEC-BX101 Low in Store Walmart DC 47.99 2 Days
    Amazon HOM-DT230 Out of Stock Merchant N/A N/A

    This real-time feed allowed the client to:

    • Instantly reflect stock-outs or low inventory on their own site.
    • Auto-deactivate products if Walmart or Amazon ran out.
    • Sync availability across Shopify, Amazon Seller Central, and internal POS systems.

    Result:

    Order cancellations dropped by 18%, and cart abandonment due to “out of stock” errors reduced by 23% in 60 days.

    Step 2: Delivery Time Optimization

    By scraping estimated delivery times from Amazon.com and Walmart.com for over 500 ZIP codes in Illinois, Indiana, and Michigan, Actowiz Solutions created a delivery-time intelligence dashboard.

    Sample Delivery Time Dataset:

    Platform SKU ZIP Code Delivery ETA Fulfillment Center Prime Eligible
    Amazon HOM-DT230 60601 2 Days Joliet, IL Yes
    Walmart HOM-DT230 60601 3 Days Store #456 – Cicero No

    Insights uncovered:

    • Amazon’s Joliet, IL FBA warehouse delivered 30% faster than client’s in-house fulfillment.
    • Walmart stores showed delayed dispatch on weekends.

    Using this data, the client:

    • Redirected high-demand SKUs to Amazon FBA to meet Prime delivery expectations.
    • Scheduled same-day dispatch for ZIPs with historically delayed Walmart deliveries.
    • Re-routed orders to alternative fulfillment centers during peak traffic or storms.

    Result:

    Average delivery time reduced from 3.5 days to 1.9 days, and delivery SLA compliance improved by 34%.

    Step 3: Warehouse Planning Using Stock Trends

    Actowiz Solutions implemented stock frequency analysis using scraped historical inventory data for 6 months.

    Insights Derived:

    • SKU ELEC-BX101 ran out at Walmart every Saturday evening, indicating high weekend demand.
    • Amazon restocked SKU HOM-DT230 every Tuesday, enabling predictive planning for Tuesday-Wednesday shipping.
    • 70% of customer complaints came from ZIPs that lacked localized inventory.

    Warehouse Allocation Dashboard View:

    SKU Location Avg Weekly Demand Overstock % Suggested Action
    ELEC-BX101 Chicago IL 1,200 units 5% Keep steady replenishment
    HOM-DT230 Peoria IL 300 units 42% Divert stock to Chicago
    ACC-CBL999 Joliet IL 50 units 3% Move to clearance stock

    Based on these insights, the client revised their warehouse plans:

    • Consolidated underperforming SKUs in 2 of 6 warehouses.
    • Increased forward stocking for high-turnover SKUs in Joliet and Naperville.
    • Automated replenishment triggers based on competitor restock cycles.

    Result:

    Warehouse storage costs dropped by 21%, and order fulfillment rates improved by 26%.

    Key Features Delivered by Actowiz Solutions

    Feature Description
    Amazon & Walmart Scraper Near real-time scraping with SKU/ZIP targeting
    Historical Price & Stock Trends 90-day view for restock pattern detection
    Fulfillment Heatmap Visualization of Amazon/Walmart delivery speeds per ZIP
    ERP/API Integration Seamless feed into internal inventory & WMS systems
    Anomaly Detection Alerts Notifications for unusual price/stock behavior

    Tech Stack Used

    • Python + Scrapy for scalable crawling
    • Rotating proxies + CAPTCHA bypassing
    • PostgreSQL for structured inventory and trend data
    • Power BI / Tableau connectors for data visualization
    • Custom REST API for ERP integration

    Client Feedback

    “Actowiz Solutions transformed our operations. Their scraping engine made our data actionable—we now make restocking decisions in real-time, not weeks later. From delivery SLAs to shelf planning, we’re running smarter than ever”

    — Director of Operations, Midwest Retailer

    Business Impact Summary

    Metric Before After (6 Months)
    Avg Delivery Time 3.5 days 1.9 days
    Inventory Stockouts 12.4% 6.1%
    Order SLA Compliance 61% 95%
    Warehouse Utilization Efficiency 64% 87%
    Cart Abandonment (Stock Issue) 18.7% 5.2%
    Start Your Retail Intelligence Journey
    Contact Us Today!

    Conclusion

    With Actowiz Solution's web scraping and data intelligence tools, the client gained a synchronized inventory, predictive delivery insights, and optimized warehouse workflows across three major U.S. states.

    This case proves how data scraping, when implemented strategically, bridges the operational gap between digital platforms and physical logistics—leading to measurable business outcomes.

    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
    Aug 08, 2025

    Discounted Devotion? Janmashtami Offer Mapping Across Quick Commerce Platforms

    Actowiz Solutions compares Janmashtami offers on puja items & sweets across quick commerce platforms with real-time scraping & price tracking insights.

    thumb

    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.

    thumb

    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.

    thumb

    🇮🇳 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.
    Aug 08, 2025

    Discounted Devotion? Janmashtami Offer Mapping Across Quick Commerce Platforms

    Actowiz Solutions compares Janmashtami offers on puja items & sweets across quick commerce platforms with real-time scraping & price tracking insights.

    Aug 08, 2025

    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
    thumb

    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.

    thumb

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

    Discover how Actowiz Solutions scraped Rakhi gift hamper prices from Q-commerce platforms to reveal real festive discount insights with real-time pricing data.

    thumb

    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.

    Read More
    thumb

    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.

    thumb

    2025 Buying Behavior Trends: Smarter Retail Decisions Backed by Data

    Explore retail buying behavior trends for 2025 with data-driven insights on Gen Z, AI, omnichannel shopping, and smart decisions from Actowiz Solutions.

    thumb

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

    Use real-time price monitoring to benchmark Amazon & Walmart prices, avoid MAP violations, and power your eCommerce intelligence with Actowiz Solutions.

    Read More
    thumb

    🇮🇳 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.
    thumb

    Lazada Grocery App Dataset Analysis - Market Intelligence & Grocery Delivery Trends for American Startups

    Explore Lazada grocery App dataset insights to uncover grocery delivery trends, pricing, and market gaps for American startups entering Southeast Asian markets.
    thumb

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

    Explore Actowiz Solutions' scraped data report on travel price surges in India during Raksha Bandhan & Independence Day 2025. Flight, hotel & booking insights inside.
    Read More