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GeoIp2\Model\City Object
(
    [raw:protected] => Array
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            [city] => Array
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                    [names] => Array
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                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                            [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
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                            [de] => USA
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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                                    [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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                    [ip_address] => 216.73.216.141
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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
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                            [de] => Nordamerika
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                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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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
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
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            [validAttributes:protected] => Array
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                    [0] => confidence
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                    [3] => isoCode
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        )

    [locales:protected] => 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
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [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:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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                    [0] => confidence
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        )

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

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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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] => 216.73.216.141
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
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                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
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                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
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                    [10] => isp
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                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
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                    [19] => staticIpScore
                    [20] => userCount
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        )

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

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

            [validAttributes:protected] => Array
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                    [2] => latitude
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                    [4] => metroCode
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                    [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
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            [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
                                )

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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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)
 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
)
Real-Time Regional Insights with Customizable E-commerce Dashboards

Overview

Japan’s capital, Tokyo, is leading the digital shift in grocery shopping, with a surge in online orders, flash sales, and regional competition. For global retailers and FMCG brands planning to expand into Japan, understanding price behavior, discount patterns, and local consumer trends is essential.

A global food brand approached Actowiz Solutions to create a data-driven market entry strategy for Tokyo’s online grocery segment. Through advanced web scraping of Rakuten and AEON, we delivered real-time, structured insights into pricing, stock levels, and promotions—enabling the client to build a competitive launch plan tailored for Tokyo’s fast-moving grocery space.

Client Profile

  • Type: Global FMCG brand entering the Japanese market
  • Target Market: Tokyo metropolitan area
  • Goal: Use real-time online grocery data to assess pricing, promotion trends, and consumer behavior before launch
  • Challenge: No local price intelligence, limited understanding of competitive positioning on platforms like Rakuten and AEON

Objectives

Key-Challenges

1. Extract real-time grocery product pricing from Rakuten Tokyo and AEON Tokyo

2. Identify top-performing SKUs, brands, and categories by region

3. Track flash sales, stock-outs, and loyalty promotions

4. Use data to shape pricing, discounting, and bundling strategy for Tokyo’s grocery launch

Actowiz Solutions: Scraping Strategy

Target Sites:
  • Rakuten Tokyo (top sellers + food category pages)
  • AEON Tokyo store (regional pricing & private label listings)
Scraped Data Fields:
Field Sample – Rakuten (Tokyo) Sample – AEON (Tokyo)
Product Name Kikkoman Soy Sauce 1L Kikkoman Soy Sauce 1L
Price (JPY) ¥278 ¥268
Discount 10% Off (limited time) Loyalty Card Discount
Stock Status In Stock In Stock
Brand Kikkoman Kikkoman
Promotion Type Flash Sale Member Exclusive
Last Updated Real-Time Real-Time

Process & Tools Used

  • Scrapy + Selenium for structured and JavaScript-heavy pages
  • IP rotation + CAPTCHA handling for smooth data extraction
  • Hourly scraping frequency to capture flash promotions
  • Google Data Studio dashboards for interactive client visualizations
  • Output formats: API | JSON | Excel

Key Insights Uncovered

Key-Challenges
1. Price Sensitivity

Products like instant noodles, bottled teas, and sauces showed price variances up to 8–12% between Rakuten and AEON.

2. Promotion Windows

Flash discounts on Rakuten lasted for as little as 6 hours, while AEON favored longer, weekend-based promotions.

3. Private Label Positioning

AEON private labels were priced 15–20% lower than similar branded items—an important factor in building local pricing strategy.

4. Category Insights

Top-performing grocery categories in Tokyo included:

  • Beverages (bottled teas, coffee cans)
  • Convenience snacks (chips, bento packs)
  • Sauces & condiments (soy, teriyaki, ponzu)

Sample Data Snapshot

Product Rakuten Price AEON Price Price Gap Action Triggered
Calbee Potato Chips 85g ¥138 ¥128 +7.8% Price Adjusted
Ito En Green Tea 500ml ¥115 ¥108 +6.5% Promo Matched
Nissin Udon Bowl ¥198 ¥195 +1.5% No Action
Meiji Milk Chocolate Bar ¥210 ¥198 +6% Repriced

Outcome for the Client

Key-Challenges
✅ Competitive Pricing Strategy

Real-time price comparisons helped the client price key SKUs within ±3% of the local market, ensuring immediate relevance at launch.

✅ Localized Promotion Calendar

By analyzing the timing of Rakuten flash deals and AEON campaigns, the client scheduled competitive offers that aligned with consumer habits.

✅ Product Mix Refinement

Using category-level performance data, the client prioritized 320 SKUs most aligned with Tokyo consumer trends, optimizing inventory.

✅ Smarter Bundling

Bundling recommendations were based on what AEON was promoting (e.g., soy sauce + udon + snacks), helping the client create culturally relevant product packs.

Client Testimonial

“Actowiz Solutions gave us the Tokyo market on a dashboard. Their scraped data revealed exactly how, when, and where we needed to compete—before we even launched.”

— Head of APAC Strategy, Global FMCG Brand

📩 Ready to decode grocery pricing in Tokyo?

Partner with Actowiz Solutions to extract live insights from Rakuten, AEON, and more—before your competitors do.
Contact Us Today!

Conclusion

Breaking into Japan’s grocery market—especially in tech-forward cities like Tokyo—requires precision, speed, and data intelligence. Web scraping platforms like Rakuten and AEON offers companies unmatched access to how consumers behave, what they value, and how competitors move.

Actowiz Solutions helped this global brand eliminate guesswork, craft a data-driven market entry strategy, and hit the ground running in one of the world’s most sophisticated grocery ecosystems.

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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