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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 ) ) [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] => 216.73.216.141 [prefix_len] => 22 ) ) [continent:protected] => GeoIp2\Record\Continent Object ( [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 ) ) [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array ( [0] => en ) [validAttributes:protected] => Array ( [0] => code [1] => geonameId [2] => names ) ) [country: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 ( [0] => en ) [validAttributes:protected] => Array ( [0] => confidence [1] => geonameId [2] => isInEuropeanUnion [3] => isoCode [4] => names ) ) [locales:protected] => Array ( [0] => en ) [maxmind:protected] => GeoIp2\Record\MaxMind Object ( [record:GeoIp2\Record\AbstractRecord:private] => Array ( ) [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 ( [0] => en ) [validAttributes:protected] => Array ( [0] => confidence [1] => geonameId [2] => isInEuropeanUnion [3] => isoCode [4] => names ) ) [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object ( [record:GeoIp2\Record\AbstractRecord:private] => Array ( ) [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array ( [0] => en ) [validAttributes:protected] => Array ( [0] => confidence [1] => geonameId [2] => isInEuropeanUnion [3] => isoCode [4] => names [5] => type ) ) [traits:protected] => GeoIp2\Record\Traits Object ( [record:GeoIp2\Record\AbstractRecord:private] => Array ( [ip_address] => 216.73.216.141 [prefix_len] => 22 [network] => 216.73.216.0/22 ) [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 ) ) [city:protected] => GeoIp2\Record\City Object ( [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 ) ) [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array ( [0] => en ) [validAttributes:protected] => Array ( [0] => confidence [1] => geonameId [2] => names ) ) [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 ( [0] => en ) [validAttributes:protected] => Array ( [0] => confidence [1] => geonameId [2] => isoCode [3] => names ) ) ) )
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 on how a Q-commerce startup in Japan improved customer experience using web scraping through personalized recommendations and faster deliveries.
Note: You’ll receive it via email shortly after submitting the form.
Our client, a quick commerce (Q-commerce) startup based in Tokyo, Japan, focuses on delivering daily essentials to urban residents. With a rapidly growing customer base, the client aims to differentiate itself in a competitive market by providing an enhanced customer experience, faster delivery times, and personalized product recommendations.
Operating in the densely populated and fast-paced environment of Tokyo, the client recognized the need to enhance its customer experience to stay ahead of competitors. However, two critical issues emerged:
Personalized Recommendations:The client wanted to introduce a recommendation engine to offer tailored product suggestions based on user preferences and past behavior. However, they lacked access to sufficient data to build accurate customer profiles and analyze trends.
Timely Deliveries: Timely deliveries are essential for success in the quick commerce space. Customers expect their orders to arrive quickly, especially in metropolitan areas like Tokyo, where delays can result in dissatisfaction. The client needed insights into peak demand times, competitor delivery performance, and overall logistics optimization.
Without the necessary data, it was nearly impossible for the startup to implement the desired features effectively. The manual process of gathering customer feedback and analyzing competitor delivery times was too slow and insufficient for the dynamic nature of the Q-commerce sector.
To help the client overcome these challenges, Actowiz Solutions deployed a Quick Commerce Data Scraping solution. Using advanced Web Scraping Solutions for Quick Commerce, the client was able to gather valuable data from various competitor platforms, including customer reviews, product preferences, and delivery times. This Quick Commerce Web Data Extraction provided actionable insights to improve both customer satisfaction and operational efficiency.
Actowiz Solutions implemented Automated Data Scraping for Quick Commerce to extract customer feedback and reviews from competitor platforms. By leveraging Data Mining for Quick Commerce, we collected information on what products were popular, what features customers valued the most, and which areas needed improvement. This Quick Commerce Insights Scraping allowed the client to identify gaps in their product offerings and better understand customer preferences. The feedback from reviews was analyzed to identify patterns, such as frequent mentions of certain product categories, delivery issues, and customer service concerns. These insights were key to building a more tailored shopping experience.
In addition to gathering customer insights, Quick Commerce Data Scraping was used to monitor delivery times and logistics strategies from competitors. This involved analyzing peak demand periods, common delivery delays, and competitor shipping policies. With this data, the client could identify which timeframes were most critical for optimizing deliveries, and which logistical improvements could reduce delays. Quick Commerce Market Analysis helped the client benchmark their performance against competitors and gain a clearer understanding of customer expectations regarding delivery speed.
One of the key aspects of the solution was the implementation of Real- time Data Scraping for Quick Commerce. This enabled the client to continuously monitor changes in customer preferences, product demand, and competitor pricing strategies. By utilizing Web Scraping Solutions for Quick Commerce, the client was able to receive up-to-the- minute updates that informed their dynamic decision-making process, ensuring they could respond quickly to market shifts.
The data collected through Quick Commerce Data Extraction allowed the client to implement several key changes that significantly improved their customer experience and business outcomes.
By analyzing customer preferences and purchase patterns from competitor platforms, the client was able to build a highly effective recommendation engine. This engine used historical data and real-time inputs to offer personalized product suggestions to customers based on their previous purchases, browsing history, and preferences gleaned from reviews.
This personalization resulted in a 25% increase in repeat purchases, as customers were more likely to find products that suited their tastes and needs. The Quick Commerce Product Scraping allowed the client to stay on top of emerging product trends, ensuring that their recommendations remained relevant and up-to-date.
One of the critical factors in Q-commerce is delivery speed. Customers expect their orders to be fulfilled quickly, especially in a fast-paced city like Tokyo. By using data gathered through Quick Commerce Competitive Analysis, the client was able to optimize their delivery routes and times based on insights into peak demand periods and competitor performance. The data showed when and where delays were likely to occur, enabling the client to make adjustments in real-time.
As a result, the average delivery time was reduced by 10 minutes, improving customer satisfaction and boosting overall operational efficiency. Quick Commerce Market Analysis and competitor data mining played a crucial role in making these logistical improvements.
Improving the customer experience through personalized recommendations and faster deliveries led to higher retention rates. Customers who experienced timely deliveries and received relevant product suggestions were more likely to leave positive reviews and return for future purchases. The combination of Data Scraping for Quick Commerce and Automated Data Scraping for Quick Commerce provided the client with the necessary tools to enhance loyalty.
Additionally, positive reviews and word-of-mouth recommendations increased, helping the client build a strong reputation in a highly competitive market. The insights gained through Quick Commerce Insights Scraping allowed the client to maintain their customer- centric approach, which proved invaluable in a rapidly evolving sector.
The use of Web Scraping Solutions for Quick Commerce allowed the client to transform their operations and achieve significant business gains. Below are some of the key benefits:
Real-time Data for Actionable Insights: By implementing Real- time Data Scraping for Quick Commerce, the client was able to react quickly to market changes, stay ahead of competitors, and continuously improve the customer experience.
Automated Data Collection: Manual data collection was no longer necessary, saving the client time and resources. Scraping Services for Quick Commerce automated the entire process, ensuring continuous data flow without the risk of human error.
Improved Product Recommendations: With Quick Commerce Product Scraping, the client could analyze customer preferences in real-time and provide personalized product recommendations, leading to higher customer satisfaction and increased repeat purchases.
Faster Deliveries: Data-driven insights helped the client optimize their delivery logistics, reducing delivery times and enhancing overall customer experience.
Stronger Competitive Position: The use of Quick Commerce Competitive Analysis allowed the client to benchmark their performance against competitors and make necessary adjustments to stay competitive in the market.
This case study demonstrates how Actowiz Solutions used Quick Commerce Web Scraping to help a Q-commerce startup in Japan enhance their customer experience. By implementing Quick Commerce Data Collection Services, the client was able to gather valuable data from competitor platforms and use it to build a more personalized shopping experience while improving operational efficiency.
The combination of personalized recommendations, faster deliveries, and increased customer loyalty allowed the client to thrive in a competitive market. The data-driven approach powered by Quick Commerce Data Extraction not only boosted revenue and repeat purchases but also established the client as a leading Q-commerce platform in Tokyo.
In the fast-evolving Q-commerce landscape, Web Scraping Solutions for Quick Commerce can be a game-changer for businesses looking to gain a competitive edge, improve customer satisfaction, and enhance operational efficiency. Actowiz Solutions continues to provide comprehensive data scraping services tailored to the needs of the Q- commerce sector, ensuring that businesses can make data-backed decisions in real time.
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
Real Estate
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×
Organic Grocery / FMCG
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
Quick Commerce
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
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
Beverage / D2C
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
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
Real results from real businesses using Actowiz Solutions
In Stock₹524
Price Drop + 12 minin 6 hrs across Lel.6
Price Drop −12 thr
Improved inventoryvisibility & planning
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
"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"
✔ Scraped Data, SKU availability, delivery time
With hourly price monitoring, we aligned promotions with competitors, drove 17%
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Benefit from the ease of collaboration with Actowiz Solutions, as our team is aligned with your preferred time zone, ensuring smooth communication and timely delivery.
Our team focuses on clear, transparent communication to ensure that every project is aligned with your goals and that you’re always informed of progress.
Actowiz Solutions adheres to the highest global standards of development, delivering exceptional solutions that consistently exceed industry expectations