本文源引自Laura Kegley在《Forbes》2024年3月28日的刊文，采用中英双语排版，由ImmersiveTranslate提供翻译支持。
For data-driven businesses, star ratings represent a treasure trove of invaluable insights. They offer a compelling, easily accessible glimpse into customer sentiments surrounding your business, products or services. But what if I told you that star ratings alone can’t tell the whole story?
对于数据驱动的企业来说，星级评级代表着宝贵见解的宝库。它们提供了令人信服且易于了解的客户对您的业务、产品或服务的看法。但如果我告诉你仅凭星级评级并不能说明全部情况呢？
Understanding User Ratings
了解用户评分
User ratings, typically depicted in the form of stars ranging from one to five, are a quantifiable measure of customer satisfaction and experience with a product or service. They provide a quick snapshot of individual and collective opinions, allowing potential buyers to gauge the quality and reliability of what they’re considering purchasing.
用户评级通常以 1 到 5 颗星的形式表示，是对客户满意度和产品或服务体验的量化衡量标准。它们提供了个人和集体意见的快速快照，使潜在买家能够衡量他们正在考虑购买的产品的质量和可靠性。
From e-commerce giants like Amazon and eBay to service-oriented platforms such as Airbnb and Uber, star ratings have become ubiquitous, offering a streamlined way for consumers to share their feedback and for businesses to showcase their reputations.
从亚马逊和 eBay 等电子商务巨头到 Airbnb 和 Uber 等服务导向型平台，星级评定已经无处不在，为消费者分享反馈和企业展示声誉提供了一种简化的方式。
Research suggests that star ratings wield significant influence over consumer behavior and perception. A staggering 90% of consumers consider ratings and reviews when making purchase decisions, and a whopping 94% of purchases are made for products rated four stars and above.
研究表明，星级评级对消费者的行为和看法具有重大影响。令人震惊的是，90% 的消费者在做出购买决定时会考虑评级和评论，高达 94% 的购买行为是四星级及以上的产品。
Advantages Of Star Ratings
星级评定的优点
Let’s explore some of the benefits of the star rating system that may explain why it has become so dominant.
让我们探讨一下星级评定系统的一些好处，这或许可以解释为什么它变得如此占主导地位。
• Simplicity: In a world where attention spans are short, and choices are abundant, a quick glance at a product’s star rating can often be enough to sway a purchasing decision.
• 简单性：在一个注意力持续时间短、选择丰富的世界中，快速浏览产品的星级评级通常足以影响购买决定。
• Universality: Star ratings provide a standardized metric that transcends language barriers, making them universally accessible and understandable.
• 普遍性：星级评定提供了超越语言障碍的标准化指标，使之为所有人所接受和理解。
• Comparison: Star ratings offer a clear and easy way for consumers to compare multiple products or services within the same category. By quickly scanning star ratings, consumers can discern which options are better rated compared to others.
• 比较：星级评级为消费者提供了一种清晰、简单的方法来比较同一类别内的多种产品或服务。通过快速扫描星级评分，消费者可以辨别哪些选项比其他选项评分更高。
Limitations Of Star Ratings
星级的限制
While star ratings offer a convenient shorthand for assessing quality, they may not always paint a complete picture of consumer sentiment. Let’s explore some of these limitations.
虽然星级评级为评估质量提供了方便的速记方式，但它们可能并不总能描绘出消费者情绪的完整画面。让我们探讨其中的一些限制。
• Lack Of Nuance And Context: One of the primary drawbacks of star ratings is their inability to capture the nuanced aspects of user experiences. A product rated four stars may seem stellar at first glance, but what if those ratings are based solely on fast shipping rather than the actual quality of the product itself? Without accompanying context or detailed feedback, star ratings can be misleading and fail to provide a comprehensive understanding of consumer satisfaction.
• 缺乏细微差别和背景：星级评定的主要缺点之一是无法捕捉用户体验的细微差别。乍一看，评级为四星的产品可能看起来很出色，但如果这些评级仅基于快速运输而不是产品本身的实际质量呢？如果没有附带的背景或详细的反馈，星级评级可能会产生误导，并且无法提供对消费者满意度的全面了解。
• Negativity Bias: Studies have shown that negative sentiments tend to have a stronger impact on the star ratings assigned by customers. This aligns with negativity bias theory, which suggests that individuals are more sensitive to losses (negative sentiments) than gains (positive sentiments), leading them to weigh negative information more heavily in their evaluations. This negativity bias can skew perceptions and unfairly tarnish the reputation of an otherwise excellent product or service.
• 负面偏见：研究表明，负面情绪往往会对客户指定的星级产生更大的影响。这与消极偏见理论相一致，该理论表明，个人对损失（消极情绪）比收益（积极情绪）更敏感，导致他们在评估中更重视负面信息。这种消极偏见可能会扭曲人们的看法，并不公平地损害原本优秀的产品或服务的声誉。
• Discrepancy Between Ratings And Review Text: Another challenge with star ratings is the potential disconnect between the numerical rating and the content of the accompanying review text. Research has found that there is only a moderate correlation between the sentiment expressed in reviews and the star ratings assigned. This makes it difficult to rely solely on star ratings as an accurate measure of customer satisfaction.
• 评级与评论文本之间的差异：星级评级的另一个挑战是数字评级与所附评论文本内容之间可能存在脱节。研究发现，评论中表达的情绪与所分配的星级之间只有中等相关性。这使得很难仅仅依靠星级来准确衡量客户满意度。
• Specific Topics Driving Ratings: Furthermore, star ratings may be influenced by specific topics or aspects of a product or service rather than providing an overall assessment of its quality. For example, a hotel may receive a low star rating due to cleanliness issues despite receiving praise for its excellent customer service. Understanding the specific drivers behind star ratings is essential for businesses to address areas for improvement effectively.
• 特定主题驱动评级：此外，星级评级可能会受到产品或服务的特定主题或方面的影响，而不是提供对其质量的总体评估。例如，尽管酒店因其出色的客户服务而受到好评，但由于清洁问题，酒店可能会获得较低的星级评级。了解星级评级背后的具体驱动因素对于企业有效解决需要改进的领域至关重要。
Customer Sentiment Analysis
客户情绪分析
In response to the limitations of star ratings, businesses are increasingly turning to customer sentiment analysis to gain deeper insights into consumer experiences. Customer sentiment analysis involves the systematic interpretation of opinions, emotions and attitudes expressed in customer feedback and reviews. It provides businesses with valuable insights into how customers feel about their products, enabling them to make informed decisions and drive improvements.
为了应对星级评级的局限性，企业越来越多地转向客户情绪分析，以更深入地了解消费者体验。客户情绪分析涉及对客户反馈和评论中表达的观点、情绪和态度的系统解释。它为企业提供了有关客户对其产品的感受的宝贵见解，使他们能够做出明智的决策并推动改进。
Research indicates that sentiment analysis is highly effective in detecting the underlying tone of analyzed content. It serves as a complementary approach to star ratings, offering a more nuanced understanding of consumer sentiment beyond numerical ratings alone.
研究表明，情感分析在检测分析内容的潜在基调方面非常有效。它是星级评级的补充方法，除了数字评级之外，还可以更细致地了解消费者情绪。
Customer Sentiment Analysis Methodologies
客户情绪分析方法
Several methodologies are employed in customer sentiment analysis, each with its own strengths and limitations.
客户情绪分析采用了多种方法，每种方法都有自己的优点和局限性。
• Rule-Based Approach: This method relies on predefined rules and linguistic patterns to categorize text into positive, negative or neutral sentiment categories.
• 基于规则的方法：此方法依赖于预定义的规则和语言模式将文本分类为积极、消极或中性情绪类别。
• Machine-Learning Approach: Machine-learning algorithms are trained on labeled datasets to classify text based on sentiment. These algorithms can improve over time as they process more data.
• 机器学习方法：机器学习算法在标记数据集上进行训练，以根据情感对文本进行分类。随着处理更多数据，这些算法可以随着时间的推移而改进。
• Hybrid Approach: Combining rule-based and machine-learning techniques, the hybrid approach leverages the strengths of both methodologies to enhance accuracy.
• 混合方法：混合方法将基于规则的技术和机器学习技术相结合，利用两种方法的优势来提高准确性。
• Lexicon-Based Approach: Lexicon-based sentiment analysis utilizes dictionaries containing words and their associated sentiment scores to analyze text. It assigns sentiment scores to words and aggregates them to determine sentiment.
• 基于词典的方法：基于词典的情感分析利用包含单词及其相关情感分数的词典来分析文本。它将情绪分数分配给单词并聚合它们以确定情绪。
• Aspect-Based Approach: This approach focuses on analyzing sentiment at a granular level, considering specific features of a product or service rather than treating the entire text as a single entity.
• 基于方面的方法：此方法侧重于在粒度级别上分析情绪，考虑产品或服务的特定功能，而不是将整个文本视为单个实体。
Ways To Use Customer Sentiment Analysis
使用客户情绪分析的方法
Customer sentiment analysis offers numerous practical applications for businesses.
客户情绪分析为企业提供了大量的实际应用。
• Tracking Customer Sentiment Over Time: Monitoring changes in customer sentiment over time helps to identify trends and track the impact of business initiatives.
• 跟踪一段时间内的客户情绪：监控一段时间内客户情绪的变化有助于识别趋势并跟踪业务计划的影响。
• Customer Segmentation: Breaking down sentiment analysis by customer segment can illuminate whether certain segments have different opinions than others.
• 客户细分：按客户细分进行情绪分析可以了解某些细分是否与其他细分有不同的意见。
• Product Improvements: Analyzing customer sentiment allows for identifying areas for product enhancement and addressing common pain points.
• 产品改进：分析客户情绪可以确定产品改进的领域并解决常见的痛点。
• Identifying Customer Service Issues: Businesses can identify and prioritize customer service issues based on their impact on sentiment.
• 识别客户服务问题：企业可以根据客户服务问题对情绪的影响来识别客户服务问题并确定其优先级。
To The Stars And Beyond
通往星星及更远的地方
User ratings offer a convenient snapshot of consumer satisfaction and influence purchasing decisions significantly. However, they fall short of capturing the nuanced aspects of customer experiences. This underscores the need to embrace qualitative customer sentiment analysis as a way to complement quantitative user rating data and gain a more nuanced understanding of consumer opinions for better decision-making.
用户评分提供了消费者满意度的便捷快照，并显着影响购买决策。然而，它们未能捕捉到客户体验的细微差别。这强调需要采用定性客户情绪分析作为定量用户评级数据的补充，并更细致地了解消费者意见，以便做出更好的决策。
