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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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                            [es] => Norteamérica
                            [fr] => Amérique du Nord
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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                    [longitude] => -83.0061
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            [postal] => Array
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            [registered_country] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
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                            [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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                            [iso_code] => OH
                            [names] => Array
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                                    [de] => Ohio
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                                    [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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            [traits] => Array
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    [continent:protected] => GeoIp2\Record\Continent Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

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

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

            [validAttributes:protected] => Array
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                    [0] => queriesRemaining
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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
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
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            [validAttributes:protected] => Array
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    [traits:protected] => GeoIp2\Record\Traits Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.110
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
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                    [2] => connectionType
                    [3] => domain
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                    [5] => isAnonymous
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                    [8] => isHostingProvider
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                    [10] => isp
                    [11] => isPublicProxy
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                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
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                    [18] => organization
                    [19] => staticIpScore
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                )

        )

    [city:protected] => GeoIp2\Record\City Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [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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            [validAttributes:protected] => Array
                (
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                    [1] => geonameId
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                )

        )

    [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
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                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
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                            [3] => names
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                )

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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 Naver Store Seasonal Sales Analysis – Discount Trends During Korean Chuseok Festival-0

Introduction

In today’s competitive automotive ecosystem, Used Vehicle Market Intelligence plays a vital role in helping dealerships make informed business decisions. Actowiz Solutions partnered with a leading auto dealer network to transform raw vehicle listing data into actionable insights. By leveraging advanced Web Scraping Services, our team extracted high-quality datasets from Carfax to fuel in-depth analysis. This enabled dealers to monitor pricing trends, evaluate competitive positioning, and identify consumer demand patterns across regions. With expertise in Web Crawling Services, Automobile Data Scraping, Car Rental Data Scraping, and Retailer Intelligence, Actowiz Solutions delivered a robust intelligence framework that reshaped decision-making for dealerships across the U.S. The project demonstrates how accurate, timely, and comprehensive market intelligence can help auto dealers thrive in a dynamic, data-driven marketplace.

The Client

Our client is a reputed auto dealer group operating across multiple states in the United States, specializing in both used and certified pre-owned cars. Their goal was to build a data-backed strategy to remain competitive and maximize sales performance. With significant competition in local markets, they needed deeper visibility into the U.S. Automotive Market Insights and a reliable way to benchmark pricing against regional and national trends. The client specifically sought access to Carfax Data Scraping to unlock transparent vehicle history details and enrich their inventory analysis. Since the group operates in diverse regions such as New York and Texas, the ability to track Carfax Used Car Data in New York and monitor Texas Car Listing Market Trends was critical. They turned to Actowiz Solutions to achieve a scalable and sustainable data pipeline capable of powering advanced analytics across multiple dealership operations.

Key Challenges

Key Challenges-01

The client faced significant challenges in acquiring and managing large-scale data from fragmented automotive marketplaces. Traditional market research provided limited depth, often missing real-time pricing shifts and consumer interest signals. The dealership group lacked the internal capability to gather consistent datasets across regions and was unable to perform comprehensive Vehicle Listing Data Analysis. Another concern was the growing intensity of competition in the pre-owned car sector, making it vital to extract U.S. Auto Dealer Market Analysis insights to fine-tune pricing strategies. Without reliable access to Nationwide Automotive Data Intelligence, the client risked losing market share to rivals who were adopting more agile and data-driven models. Additionally, the complexity of integrating historical Carfax data with real-time market feeds hindered the development of Auto Dealer Analytics. To overcome these barriers, the client needed an experienced partner capable of executing complex Automobile Data Scraping initiatives at scale while ensuring accuracy and compliance.

Key Solutions

The-Client

Actowiz Solutions deployed a custom-built data intelligence framework designed specifically for the U.S. used vehicle market. Our approach began with precise Carfax Data Scraping, ensuring access to critical attributes such as mileage, accident history, ownership details, and pricing benchmarks. Leveraging advanced Web Crawling Services, we created automated pipelines that continuously monitored thousands of vehicle listings across regions, with a special focus on Carfax Used Car Data in New York and Texas Car Listing Market Trends. This system enabled comprehensive Vehicle Listing Data Analysis while integrating historical datasets to identify pricing fluctuations and emerging consumer demand. Our intelligence suite also included advanced Auto Dealer Analytics, delivering granular insights into dealer competitiveness, inventory positioning, and promotional strategies. The resulting Nationwide Automotive Data Intelligence empowered the client to make Data-Driven Auto Sales Decisions, aligning their business strategies with real-time market dynamics. Actowiz Solutions’ expertise in Car Rental Data Scraping and Retailer Intelligence further enriched the framework, providing broader cross-industry perspectives. Ultimately, our tailored solutions positioned the client to gain a sustainable competitive edge in the fast-evolving automotive market.

Client Testimonial

“Partnering with Actowiz Solutions has completely transformed the way we approach our dealership strategy. Their expertise in Used Vehicle Market Intelligence and their ability to deliver accurate Carfax-based insights have been invaluable. The integration of regional trends and nationwide analytics allowed us to refine our pricing models and stay ahead of the competition. Their team’s professionalism, responsiveness, and technical skill made them an ideal partner for our data-driven growth.”

— VP of Strategy & Analytics, U.S. Auto Dealer Network

Conclusion

This case study demonstrates how Used Vehicle Market Intelligence powered by Carfax Data Scraping can help dealerships strengthen their competitive positioning. By transforming raw vehicle listing data into meaningful insights, Actowiz Solutions enabled the client to optimize pricing, improve inventory decisions, and uncover new market opportunities. With actionable U.S. Automotive Market Insights and advanced Auto Dealer Analytics, the client successfully adopted a proactive, data-driven approach to sales and marketing. From regional focus points like Carfax Used Car Data in New York to macro-level Nationwide Automotive Data Intelligence, the project highlights the importance of leveraging structured datasets in the automotive retail sector. Actowiz Solutions continues to empower auto dealers with advanced intelligence frameworks, proving that the right mix of technology and strategy can redefine success in the highly competitive used vehicle industry.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape Structure Analyze Visualize

Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

Find Insights Use AI to connect data points and uncover market changes. Meanwhile.

Move Forward Predict demand, price shifts, and future opportunities across geographies.

Industry:

Fintech / Digital Payments

Result

Accurate daily voucher &

cashback visibility across platforms

★★★★★

“Actowiz Solutions helped us automate daily voucher and cashback data collection across PhonePe, Paytm, Flipkart, and Hubble. The API-driven delivery significantly improved offer accuracy and operational efficiency.”

Product Manager, Fintech Platform (India)

✓ Daily voucher & cashback tracking via Push & Pull APIs

Industry:

Coffee / Beverage / D2C

Result

2x Faster

Smarter product targeting

★★★★★

“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

“With Actowiz Solutions' data scraping, we’ve gained a clear edge in tracking product availability and pricing across various platforms. Their service has been a key to improving our market intelligence.”

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

“Actowiz Solutions has greatly helped us monitor product availability from top three Quick Commerce brands. Their real-time data and accurate insights have streamlined our inventory management and decision-making process. Highly recommended!”

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

Trusted by Industry Leaders Worldwide

Real results from real businesses using Actowiz Solutions

★★★★★
'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"
Thomas Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
Product Image
2 min
★★★★★
“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
Product Image
1 min
★★★★★
“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
Product Image
1 min

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

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

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

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & planning

Monitor Prices, Availability & Trends -Live Across Regions

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

✔ Scraped Data: Price Insights Top-selling SKUs

Our Data Drives Impact - Real Client Stories

Blinkit | India (Retail Partner)

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

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

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

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

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

✔ Scraped Data, SKU availability, delivery time

Actowiz Insights Hub

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

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Shopsy Discount Intelligence- Extracting Offer Data for Competitive Benchmarking

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Amazon Action Figure Market Analysis: Sales Trends, Pricing Strategy & Competitive Landscape

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Dewu (Poizon) Sneaker Price Gap Scraping - A Data-Driven Approach to Understanding Global Sneaker Demand

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How Hyperlocal Healthcare Pricing Intelligence Using 1mg Data Solves Medication Cost Challenges for Patients

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Amazon USA Price Scraping API 2026: Buy Box Reclaiming New York Retailers

Track Amazon USA prices and Buy Box shifts in 2026. Help New York retailers reclaim Buy Box share using real-time price scraping API by Actowiz Solutions.

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Shopsy Discount Intelligence- Extracting Offer Data for Competitive Benchmarking

Shopsy Discount Intelligence - Extracting offer data to track competitors, benchmark promotions, and optimize pricing strategies effectively.

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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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Amazon Action Figure Market Analysis: Sales Trends, Pricing Strategy & Competitive Landscape

Amazon Action Figure Market Analysis covering sales trends, pricing, and competitive insights for data-driven growth.

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Mattel Amazon Catalog Analysis: SKU Performance, Pricing Trends & Digital Shelf Insights

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EV Charging Stations vs Gas Stations Analysis in the US - Geographic Coverage, Policy Impact, and Competitive Landscape Insights

In-depth analysis comparing EV charging stations and gas stations in the US, covering coverage, policies, competition, and future growth trends.

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