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GeoIp2\Model\City Object
(
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                            [ja] => コロンバス
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                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                            [pt-BR] => EUA
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    [continent:protected] => GeoIp2\Record\Continent Object
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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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                    [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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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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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
                    [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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    [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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        )

    [traits:protected] => GeoIp2\Record\Traits Object
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                    [network] => 216.73.216.0/22
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            [validAttributes:protected] => Array
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                    [8] => isHostingProvider
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                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
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    [city:protected] => GeoIp2\Record\City Object
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                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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    [location:protected] => GeoIp2\Record\Location Object
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                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
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            [validAttributes:protected] => Array
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                    [1] => accuracyRadius
                    [2] => latitude
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                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [code] => 43215
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            [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
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                    [validAttributes:protected] => Array
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)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
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    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)
From London to Seoul – How One UK Retailer Benchmarked Prices on Naver & Coupang-01

Introduction

As Korean consumers become more brand-savvy and price-conscious, foreign retailers entering the market must get one thing right: localized pricing.

A London-based fashion retailer sought to expand to Korea via Coupang and local distributors but lacked visibility into:

  • How similar SKUs were priced locally
  • What Korean blogs said about UK brands
  • Which discount strategies appealed most

They partnered with Actowiz Solutions to build a price benchmarking framework using:

  • Daily Coupang price + promo scraping
  • Naver blog sentiment + SEO tracking
  • A custom dashboard comparing UK and Korea retail pricing

The Challenge

The Challenge-01
1. Global Pricing Misalignment

The brand’s product prices in Korea were 20–30% higher than competitor listings, making them uncompetitive on Coupang.

2. Lack of Cultural-Sentiment Data

UK-based campaigns didn’t resonate. Product descriptions ignored local trends, fabric preferences, and seasonal cues seen in Korean fashion blogs.

3. Missed Promo Windows

They failed to time flash sales with peak interest moments visible on Naver blogs or Q&A forums.

Actowiz Solutions’ Approach

We built a 3-phase benchmarking and localization solution:

Step 1: Coupang Pricing & Review Scraping
From London to Seoul – How One UK Retailer Benchmarked Prices on Naver & Coupang-01

Actowiz monitored 150+ competitor SKUs in categories like:

  • Summer casualwear
  • Office fashion (셔츠, 블레이저)
  • Eco-friendly fabrics

Captured fields included:

  • Daily base price
  • Promo/discount %
  • Number of reviews
  • Star rating
  • Keywords used in reviews
Sample Coupang Scraped Data:
Product Price (KRW) Discount Rating Reviews Tags
Linen Blazer (K Brand) ₩89,000 10% OFF 4.6 1,204 #여름자켓, #린넨블레이저
UK Brand Blazer ₩129,000 - 4.2 421 #영국브랜드, #수입패션
Step 2: Naver Blog & SEO Trend Scraping

We tracked:

  • Keywords like “런던 브랜드”, “수입 패션”, “영국 의류 추천”
  • Blog post sentiment, hashtags, fabric mentions
  • Seasonal color/style preference from influencers
Sample Naver Blog Data:
Date Blog Title Sentiment Keywords Fabric Mentions
2025-05-10 “런던 브랜드 자켓 완전 내 스타일” Positive 영국 패션, 수입자켓 린넨, 코튼
2025-05-12 “가격대가 좀 있어요. 할인 기다릴게요” Neutral 가격비교, 세일예상 폴리에스터
Step 3: UK vs Korea Price Positioning Dashboard

We integrated scraped data to produce:

Key Findings Snapshot

Key Findings Snapshot-01

Graph 1: UK Retail Price vs Coupang Competitor Price

27% average premium pre-launch

Adjusted to ≤8% after Actowiz benchmarking

Graph 2: Naver Keyword Spike vs Review Volume Surge

Top keyword “린넨자켓 추천” aligned with 3-day review spike post campaign

Smart Launch Example

SKU: Linen Summer Blazer

Action:
  • Naver blogs showed trend in “린넨,” “베이지” for early summer
  • Actowiz recommended flash sale w/ Naver influencer push
  • Result:

  • +128% jump in Coupang visits
  • ₩6.5M revenue in 4 days
  • Product review count doubled from 280 to 591
  • Results at a Glance

    Metric Before Actowiz After Actowiz
    Avg Price vs Competitor (Linen SKUs) +29% +8%
    Conversion Rate on Coupang 1.9% 4.5%
    Blog Mentions (per product line) 3–4 25–30
    Naver CTR for Brand Queries 0.7% 2.4%
    Flash Sale Timing Accuracy Low 92% synced

    Client Testimonial

    “We stopped guessing what price to charge in Korea. With Actowiz, we could benchmark, localize, and launch with confidence—and actual demand.”

    — Director, APAC Expansion, UK Fashion Brand

    Conclusion

    Cross-border fashion retail requires more than translations—it demands data-driven alignment across SEO, sentiment, and pricing.

    Actowiz Solutions helped this UK retailer transform raw Korean web data into actionable pricing, content, and campaign insights—bridging the gap between British branding and Korean buying habits.

    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:

    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

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