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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] => 216.73.216.115 [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] => 216.73.216.115 [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 )
Embrace localization to unlock new opportunities and connect with consumers on a deeper level. By harnessing the power of consumer-generated web data, businesses can gain valuable insights into local preferences, cultural nuances, and consumer behavior in specific countries. This blog equips you with the knowledge and strategies to effectively navigate these localization challenges and optimize your business's performance in the Japanese and Chinese markets.
Web data collection guides have become invaluable resources as vendors seek to expand their business into new markets. The key reason for this is the recognition that consumer preferences and trends vary significantly from one country to another. Here's why localization is essential:
Price Sensitivity:
Price points that attract and convert American consumers may repel customers in the Asia-Pacific (APAC) region and vice versa.
Localization enables businesses to understand the price sensitivity of their target market, allowing them to set competitive pricing strategies and maximize profitability.
Tailored Marketing Approach:
Consumers in different regions initiate their buying journey with distinct Google search queries and respond differently to marketing campaigns.
By localizing their marketing efforts, businesses can optimize their messaging, channels, and tactics to effectively engage and resonate with the target audience.
Cultural Relevance:
Product trends and popular items vary significantly between countries. For example, adult women in China demand Hello Kitty paraphernalia more than their British counterparts.
Localization helps businesses identify cultural preferences and adapt their product offerings to align with local tastes, ensuring relevance and increasing customer appeal.
Market Entry Strategy:
Gaining concrete insights into new markets is crucial for developing a successful market entry strategy.
Web data collection provides valuable information on consumer behavior, competitor analysis, and market trends, enabling businesses to make informed decisions and tailor their expansion plans accordingly.
Localization is vital for businesses expanding into new markets. By understanding and adapting to each country's unique preferences and trends, vendors can position themselves for success and establish a strong market presence.
Obtaining accurate and relevant insights into consumer trends within your target geographical location can be challenging when scraping data from eCommerce platforms like Amazon, eBay, Walmart, or Etsy's local sites. The issue arises when these sites block access or provide incorrect data if the origin IP differs from the target site's IP.
To overcome this challenge, it is crucial to utilize proxies corresponding to the desired geographical locations. For instance, if you are located in Germany but targeting audiences in the United States and Great Britain, using the United States and UK proxies becomes essential. These proxies enable you to leverage Residential, ISP, Mobile, and Datacenter IP addresses originating from the US/UK.
By employing Residential proxies, which are real IPs belonging to individuals residing in specific locations like Dallas, New York, London, or Birmingham, you can request data as if you were a local consumer. For example, if you want to retrieve the price of a laptop bag on Amazon for a consumer in London, the request will be routed through an actual Londoner who has opted into the proxy network. This ensures highly accurate responses, such as £12. In contrast, attempting to access the same information with your German IP address would likely result in distorted data, potentially showing an average price of £15.
By utilizing appropriate proxies aligned with your target market's geographical locations, you can collect localized eCommerce web data accurately and effectively. This lets you gain valuable insights into consumer trends, pricing strategies, and market dynamics, supporting informed decision-making for your business expansion or market analysis efforts.
Collecting open-source web data can provide valuable insights for various eCommerce use cases. Here are some of the high-impact data points that businesses in the digital commerce space often focus on:
Pricing Strategy Web Data: To effectively enter a new market, gathering data on competitors' pricing strategies is crucial. This includes understanding which price points convert well, when discounts are applied, and how holidays or special occasions impact pricing. For instance, collecting data on promotions during Chinese New Year and Golden Week in China can inform your pricing strategy. Additionally, analyzing specific Stock Keeping Units (SKUs) and their correlation with characteristics like color, brand, size, or style can uncover pricing patterns unique to different regions. For example, in Japanese culture, blue products may command higher retail prices due to their perceived luckiness.
Inventory and Product Discovery Web Data: Collecting competitors' catalogs allows businesses to discover new products and categories that align with market demand. Cross-referencing competitor data allows you to identify popular items in specific regions and incorporate them into your offerings. Real-time monitoring of competitor product introductions and stock availability provides insights for proactive market positioning and capturing market share.
Consumer Sentiment and Search Trend Web Data: Social media and search trends are essential for understanding consumer sentiment and identifying emerging trends. Monitoring influencers, engagement metrics (likes, shares, comments), and search engine queries can highlight popular products or themes among specific consumer segments. Leveraging this data helps businesses align their offerings with current trends and capitalize on high-intent traffic.
Product Ranking and Market Share Web Data: Tracking product rankings on local and global eCommerce websites, considering local IPs, and analyzing shopper engagement data such as reviews and likes provide insights into a product's performance and market share. By correlating these data points, businesses can clearly understand their product's position in a specific market. For example, a sausage cooker may have a small market share in Brazil but enjoy significant popularity in Germany.
By collecting and analyzing these high-impact eCommerce data points, businesses can make informed decisions regarding pricing, product offerings, market-entry, and customer targeting. These insights create a competitive edge and drive success in new markets.
Leveraging eCommerce data from different countries is valuable for making informed decisions on product stocking, marketing campaigns, and pricing strategies tailored to specific target audiences. This is achievable through collecting consumer and competitor-generated web data, enabling businesses to gain crucial insights and maximize their market effectiveness.
For more detailed information, feel free to get in touch with Actowiz Solutions today! We are your go-to source for all your mobile app scraping, web scraping, and instant data scraper service needs. Contact us now to discuss your specific requirements and how we can assist you.
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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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