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How-to-Analyze-Customer-Sentiment-on-Fast-Fashion-Trends-and-Perceptions

Introduction

The fast fashion industry, a pivotal element in today's fashion scene, is anticipated to experience a Compound Annual Growth Rate (CAGR) of 10.12% between 2023 and 2030. The escalating demands of an expanding youth demographic predominantly drive this growth. This research delves into the intricate realm of fast fashion, explicitly concentrating on customer sentiment analysis. The goal is to uncover prevalent trends, customer preferences, and the broader consequences of fast fashion within the dynamic market landscape of today.

To achieve this, the study involves scraping and analyzing reviews from Trustpilot's top five fast fashion brands. These brands maintain verified accounts on the platform and actively seek positive and negative feedback. Actowiz Solutions' Scraping Browser collected thousands of reviews, ensuring a smooth scraping process while mitigating the risk of being blocked.

Methodology

We selected the fashion brands Wish, Shein, Boohoo, Temu, and Fashion Nova for review because they are widely recognized and commended across various reputable sources. To gather data for our study, we used Trustpilot, an online platform with a vast repository of verified customer reviews for each of the selected brands. We scraped the top 500 reviews for each brand and an additional 2000 reviews on average to ensure accuracy and a fair representation of each brand. These reviews were then cross-referenced with the scores obtained from the initial analysis to identify any discrepancies. As no disparities were found between the two sets of results, we decided to proceed with the smaller dataset for efficiency.

Results:

Assessing Customer Sentiment on Product Quality in Fast Fashion

Within fast fashion, the significance of product quality has heightened, serving as a linchpin for brand reputation, customer loyalty, and overall longevity. Positive perceptions of product quality among customers can translate into repeat business and positive word-of-mouth, critical elements for maintaining a robust market presence.

Online reviews and ratings on platforms like Trustpilot are pivotal in evaluating customer perceptions of product quality. They serve as a real-time barometer, offering valuable insights into customers' genuine feelings about their purchase items. The study involved scraping the top 500 reviews for each from Trustpilot to delve into this aspect for the five chosen brands. Subsequently, an analysis was conducted to discern the words and phrases associated with product quality, providing a comprehensive understanding of the general sentiments towards these brands.

What Customers Say?

What customers are expressing can be summarized by the most frequently used phrases, covering both positive and negative sentiments across all brands.

What-Customers-Say
Positive phrases:
Positive-phrases
Negative phrases:
Negative-phrases
Important insights:

Customer satisfaction and positive recommendations are crucial in building brand loyalty and encouraging positive word-of-mouth. The frequent use of terms such as "recommend", "pleased", and "satisfied" indicates their importance. Satisfied customers are more likely to endorse the brand and recommend it to others in their reviews.

Quality, affordability, and value for money are the key factors that influence customers. Timely and efficient delivery also contributes significantly to an enhanced shopping experience. Trust and reliability are essential for a positive customer experience, and negative sentiments like "scam" or "stole" can arise when customers don't receive the expected product or the wrong item.

Maintaining product quality and ensuring proper condition during delivery are vital considerations. Accurate sizing information and order fulfillment are crucial in preventing customer dissatisfaction.

Positive experiences can lead to customers recommending the brand they appreciate, while negative experiences, expressed through phrases like "never again," can lead to adverse word-of-mouth, customer attrition, and harm to the brand's reputation.

To gauge the general perception of these brands among customers, we will evaluate the overall average sentiment score for each brand, considering the identified positive and negative words or phrases.

Average Sentiment Score of Each Brand for Product Quality

We thoroughly analyzed each review in the dataset to determine an average sentiment score for product quality of top five fast fashion brands on Trustpilot. We isolated individual words related to product quality and assigned a positive, negative, or neutral sentiment score to each word. By averaging sentiment scores of these words in a review, we calculated an average sentiment score for that specific review. We repeated this process for all 500 reviews for each brand, providing a normalized measure of the brand's sentiment ranging from 1.0 to -1.0.

A sentiment score exceeding 0.05 was considered positive, while a score below -0.05 was considered negative. Scores falling within this range were categorized as neutral. We chose this specific range due to its optimal correlation between the review's sentiment score and the customer's actual rating.

A-sentiment-score-exceeding

The Trustpilot reviews for all five brands indicate an overall positive sentiment regarding product quality. Wish stands out with the highest customer sentiment score for product quality, followed by Temu and Fashion Nova. On the other hand, while maintaining a positive sentiment, Shein has the lowest score for product quality among these brands.

To delve deeper into customer perceptions, the analysis considered the positive-to-negative review ratio for each brand. This metric provides a more nuanced understanding of customer feedback by examining the overall sentiment and the balance between positive and negative sentiments within the reviews of each brand.

To-delve-deeper-into-customer-perceptions

The positive-to-negative sentiment ratio for each brand is as follows:

Boohoo: 2.04

Wish: 8.64

Shein: 1.44

Fashion Nova: 12.58

Temu: 4.37

Important insights:

Wish secured the highest average sentiment score overall. Still, Fashion Nova stands out with the best positive-to-negative sentiment ratio, accompanied by more neutral reviews than others. Following Fashion Nova, Wish, and Temu trail closely with commendable positive-to-negative sentiment scores. Conversely, Shein exhibits the least favorable positive-to-negative sentiment ratio, nearing neutrality.

Identifying Popular Product Categories: Analyzing Customer Sentiment Across Brands

To gauge customer sentiment regarding different product types, sentiment analysis was conducted across five brands, focusing on innerwear, outerwear, tops, bottoms, dresses, and swimsuits. By calculating positive, negative, and neutral sentiment scores for each brand within these categories, the mean sentiment score was derived for each product type across the entire dataset.

Changing similar data into tabular formats:

Sentiment-based analysis has revealed that there are distinct trends among various product types within the fast fashion industry. Stay ahead of the curve with Web Scraping Retail Data services, unlocking valuable insights into consumer sentiment and trends shaping the fast-paced world of fashion retail. This analysis sheds light on customer perceptions across different brands.

Standout Categories:

Swimsuits and innerwear constantly get high sentiment scores in different brands, suggesting widespread positive customer perceptions. These categories are trendy and well-received in the fast fashion market.

Variable Sentiments:

Dresses and outerwear exhibit more varied sentiment scores across brands, with some excelling while others lag. This suggests that customer satisfaction with these product types is brand-dependent, showcasing the importance of brand-specific offerings in these categories

Moderate Reception:

Tops and bottoms generally garner moderate sentiment scores, indicating they are staple products in the fast fashion industry. While customers generally perceive these categories positively, they stand out as something other than exceptionally popular or unpopular.

Brand Insights:
Wish:

While Wish previously held the highest average sentiment score, a closer look at specific product types reveals mixed customer sentiment. Wish tends to receive lower scores overall, but innerwear, swimsuits, and dresses enjoy moderately high sentiment, suggesting a more positive perception in these categories.

Temu:

Despite ranking second in the overall average sentiment score, Temu consistently receives high sentiment scores for various product categories, especially swimsuits, dresses, outerwear, and innerwear. This indicates strong positive sentiment and customer satisfaction with Temu's offerings in these specific categories.

Shein:

With the lowest average sentiment score, Shein generally maintains moderate sentiment scores across all product types. Innerwear and bottoms are more popular categories, enjoying relatively higher sentiment scores than other product types.

Fashion Nova:

With a relatively high average sentiment score, Fashion Nova performs well across various product types, particularly in bottoms, tops, dresses, innerwear, and outerwear. However, swimsuits receive a lower sentiment score, suggesting room for improvement in this category.

Boohoo:

Boohoo, with a comparatively lower average sentiment score, needs help achieving positive sentiments across all product types. Lower sentiment scores are observed, especially for dresses, bottoms, and dresses. However, innerwear and swimsuits receive comparatively better scores, indicating a more positive customer perception of these product categories.

Assessing Customer Perceptions: Balancing Quality and Price in the Fast Fashion Landscape

The value for money is crucial in determining customer satisfaction with fast fashion. Fast fashion brands are known for providing affordable and stylish clothing, but does this align with the customers' perception of value for money after they have used the products?

Previous metrics have shown that customers express positive sentiment regarding the value for money, which plays a significant role in shaping their opinion towards fast fashion. However, the extent to which this is true is still debatable.

To gauge the current sentiment regarding the value for money among five fast fashion brands, phrases related to this concept were analyzed. These phrases included positive and negative expressions such as "cost-effective," "value for money," "overpriced," "worth the money," "cheap quality," and "not worth the money," and The sentiment distribution was then computed, which revealed negative, positive, and neutral sentiments for each brand.

Sentiment-Distribution-by-Brand
Insights:

Shein and Wish received the highest positive sentiment at 79.8% and 75.8%, respectively. This suggests that customers generally perceive these two brands as offering good value for money, aligning with their reputation for affordability.

In contrast, Boohoo and Temu have higher percentages of negative sentiment, having Temu at 39.87% and Boohoo at 24.6%, indicating significant customer dissatisfaction with perceived value for money.

Fashion Nova strikes a balance between positive and neutral sentiments, with a positive sentiment of 68.20% and a substantial neutral sentiment of 24.4%. While it receives praise for value for money from a majority, a notable portion of customers remains neutral, suggesting a degree of variability in customer perceptions.

For brands like Temu and Boohoo, where a significant proportion of customers express negative sentiments, addressing issues related to perceived value for money could be pivotal in enhancing their customer satisfaction and loyalty.

These sentiment statistics provide valuable insights into how customers perceive the value for money offered by these fast fashion brands. While Shein and Wish appear to excel in this aspect, Temu and Boohoo face challenges and may benefit from addressing customer concerns related to value for money.

Analyzing Brand Sentiment: A Country-wise Examination Based on Trustpilot's English Reviews

Assessing brand sentiment on Trustpilot, we focused on the top five countries with the highest English reviews due to the platform's diverse international community. Not all brands received reviews from every country, leading to a concentrated analysis. Mean sentiment scores were calculated for each brand in these select nations to gauge overall perceptions.

Analyzing-Brand-Sentiment-A-Country-wise-Examination-Based-on-Trustpilot's-English-Reviews

Insights highlight the U.S. market consistently favoring all five fast fashion brands with high sentiment scores, reflecting positive perceptions. Temu stands out in Australia, maintaining top scores across countries, indicating a widespread positive image. Boohoo excels in Australia and the U.S., showcasing strong market perception. Shein's scores fluctuate, revealing varied perceptions across countries. Fashion Nova faces negativity in the Netherlands, signaling challenges in that market. Wish encounters low sentiment in the U.K. but performs well in Australia, the U.S., and Canada, suggesting diverse market perceptions. Overall, the analysis unveils a nuanced sentiment landscape for these brands globally.

Assessing the Impact of Eco-Friendliness

The fast fashion industry has come under scrutiny for its significant ecological impact as environmental concerns grow. It is the second-largest consumer of water and contributes to 10% of global carbon emissions, surpassing even the combined emissions of all airplanes and ships worldwide, as reported by the UN Environment Programme (UNEP). This increased awareness has led to concerns about excessive waste and overproduction.

A 2021 LendingTree survey found that 54% of customers in the US are willing to spend more on sustainable, eco-friendly products. To assess the eco-conscious sentiments among global and US fast fashion consumers, Trustpilot reviews were analyzed. This involved a careful examination of brand reviews for specific eco-conscious terms such as "recycled," "sustainable," "environment," and "eco-friendly." The percentage of reviews for each brand that explicitly referenced eco-friendliness as a significant factor in the customer's evaluation was then calculated.

A-2021-LendingTree-survey-found-that

The analysis across all five brands reveals that many customers, ranging from 86.9% to 96.5%, seem indifferent to sustainability. This implies that environmental concerns are not a primary consideration for a substantial majority when evaluating these fast fashion brands.

Among well-known fashion brands, Shein, Boohoo, and Wish have a relatively lower proportion of reviews expressing sustainability concerns, ranging from 5.7% to 9.4%. In contrast, Temu has the highest percentage at 13.1%. Conversely, Fashion Nova has the lowest sustainability concern percentage, with only 3.5% of reviews indicating such worries.

A contrasting perspective emerges from Trustpilot reviews, representing a broader spectrum of U.S. consumers surveyed by LendingTree. Although there is a segment expressing sustainability concerns in the survey, these individuals are unlikely to be fast fashion consumers. As the analyzed reviews indicate, most fast fashion consumers seem more focused on aspects like affordability, quality, and the overall shopping experience rather than eco-friendliness.

Given the increasing scrutiny of fast fashion brands for their environmental impact and the prevalent desire among the majority of U.S. consumers to shop in an eco-friendly manner, there is an opportunity for these brands to expand their customer base through implementing sustainability initiatives.

Evaluating Customer Service Excellence Across Five Brands

Within an industry characterized by swift trends and budget-friendly offerings, the caliber of customer service often distinguishes brands. This segment delves into the sentiment surrounding customer service for each of the five brands.

A compilation of positive phrases related to customer service was utilized to assess customer service sentiment. These included expressions such as "fantastic service," "professional," "quick response," "great service," "amazing experience," "speedy delivery," and others. The data was then analyzed on a brand-by-brand basis, with the percentage of positive experiences with customer service calculated for each.

A-compilation-of-positive-phrases-related-to

Boohoo, despite initially receiving a low average sentiment score, excels in customer service and boasts the highest percentage of positive sentiments. This suggests that customers frequently express satisfaction with the brand's customer service. Although the initial sentiment analysis associated negative phrases like "stole" or "scam" with Boohoo, indicating poor customer service, a larger number of positive phrases such as "recommend" and "fast delivery" balance out the overall sentiment. This implies that although some customers may have had negative experiences, the prevailing perception of Boohoo's customer service remains positive.

Temu achieved the second-highest score of average sentiments and maintained a commendable positive-to-negative sentiment ratio. This is in line with the findings, as Temu closely trails Boohoo in positive sentiment, indicating a significant level of customer satisfaction with its customer service.

Wish, Shein and Fashion Nova perform relatively well, each receiving more than 50% positive sentiment. This suggests that most of their customers appreciate their service efforts. However, there may still be room for improvement for these three brands.

Examining Customer Sentiment on Single-Use Apparel

Single-use wear refers to clothing and accessories crafted for momentary trends and stylish occasions rather than long-term use. For fast fashion brands, excelling in this category entails staying abreast of the latest styles and setting new trends.

In this segment, we delve into customer sentiment surrounding the concept of single-use wear items to gain a more profound insight into how these brands navigate this crucial aspect of their market. Reviews specifically focusing on items purchased for events and special occasions, such as concerts, weddings, birthdays, etc. were identified to conduct this analysis. Each brand underwent scrutiny for positive, negative, or neutral sentiment associated with single-use wear purchases.

In-this-segment-we-delve-into-customer-sentiment-surrounding

The sentiment statistics surrounding disposable fashion items for these five fast fashion brands reveal several notable trends. Across the board, positive sentiment prevails, indicating widespread satisfaction and enthusiasm among customers for the one-time wear items offered by these brands.

Shein distinguishes itself with the highest positive sentiment percentage, reaching 78.66%. This suggests a particularly strong appreciation for Shein's one-time wear offerings, possibly owing to the brand's reputation for providing a diverse and budget-friendly selection of stylish items.

Neutral sentiment remains relatively low, ranging from 4.38% to 11%. This indicates that customers generally hold clear and distinct opinions about the one-time wear items from these brands, with only a small fraction expressing indifference.

While negative sentiment is generally less prevalent than positive sentiment, there is some variability among the brands. Boohoo stands out with the highest negative sentiment at 29.2%, while the other brands exhibit negative sentiment percentages ranging from 14.6% to 24.27%.

In terms of positive sentiments associated with one-time wear items across the five brands, the most commonly expressed sentiments include...

In-terms-of-positive-sentiments-associated-with

The analysis yields several critical insights into the factors influencing the popularity of one-time wear items among fast fashion brands:

Customer Satisfaction: The frequent use of terms like "pleased" and "satisfied" indicates high customer satisfaction with one-time wear items, underscoring their role in driving popularity.

Word-of-Mouth Endorsement: The prevalence of the term "recommend" suggests that satisfied customers are not only content with these items but are also inclined to endorse them to others. Positive word-of-mouth plays a crucial role in the success of fast fashion products.

Efficient Order Fulfillment: The emphasis on "fast delivery" and "fast shipping" highlights the importance of quick and efficient order fulfillment in ensuring a positive customer experience with one-time wear items.

Customer Service: Including phrases like "great customer service" underscores the significance of responsive and helpful customer support in one-time wear shopping experiences.

Quality and Affordability: Positive mentions of "good quality" and "good value" suggest that customers associate one-time wear items with a balance between quality and affordability. Striking this balance is crucial for sustaining the popularity of these items.

Professionalism and Outstanding Service: Using terms like "professional" and "outstanding" indicates that customers perceive fast fashion brands as meeting their expectations for quality, service, and overall satisfaction. This contributes to a positive brand image and customer loyalty.

The analysis identifies speedy delivery, excellent customer service, affordability, perceived quality, and overall customer satisfaction as significant contributors to the popularity of one-time wear items within the fast fashion industry. Collectively, these factors foster customer loyalty and enable fast fashion brands to thrive in a competitive market.

Consequences Arising from Current Trends

After conducting an in-depth analysis of customer sentiments towards various fast fashion brands on multiple platforms, we have discovered notable trends and insights.

Overall, fast fashion brands are perceived positively by customers, as reflected in positive sentiments across both structured review websites and social media.

Customers prioritize both product quality and affordability. Brands that can offer good quality products at reasonable prices tend to elicit better customer sentiments, contributing to a positive brand perception.

Customer reviews frequently include phrases like "recommend" and expressions of satisfaction. This indicates that pleased customers are more likely to endorse these brands, fostering loyalty and positive word-of-mouth.

Efficient delivery and responsive customer service significantly enhance the shopping experience. Brands excelling in these aspects tend to garner positive sentiments from customers.

Swimsuits and innerwear are perceived positively across all fast fashion brands. However, sentiments vary for outerwear and dresses, suggesting brand-specific differences. "Value for money" is a critical factor influencing customer sentiment. Brands perceived to offer good value

Conclusion

In conclusion, within the wealth of insights gleaned, a fundamental reality becomes apparent: the significance of data's quality and quantity in unveiling valuable perspectives. Accessing a substantial volume of clean, reliable data is the linchpin for precise, actionable, and high-quality customer sentiment analysis.

Nevertheless, challenges arise as websites often restrict data collection frequency and volume. The question then arises: how does one efficiently navigate the intricate data acquisition process? This study effectively utilized Actowiz Solutions' Scraping Browser, a tool explicitly crafted to surmount the obstacles when gathering extensive data.

Alternatively, Actowiz Solutions offers an array of readily available datasets for those seeking a hassle-free solution. These datasets furnish high-quality, clean, and accurate data in significant volumes across various industries. Access to such data proves pivotal for any data analysis undertaking, ensuring accuracy and reliability. With Actowiz Solutions' tools, the challenges associated with data acquisition are mitigated, presenting a streamlined path to uncovering indispensable insights. You can also contact us for your mobile app scraping, instant data scraper and web scraping service requirements.

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                    [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] => 216.73.216.153
                    [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
)
Array
(
    [city] => Columbus
    [country] => United States
    [countryCode] => +1
    [currencyCode] => USD
)
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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] => 216.73.216.153
                    [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] => 216.73.216.153
                    [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
)

Request Free Sample Data

Our team will reach out within 2 hours with 500 rows of real data — no credit card required.

+1
Free 500-row sample · No credit card · Response within 2 hours