For consumers shopping online – and not only online – reviews have long played a crucial role in reducing uncertainty, helping people compare products and brands, verifying whether a company's promises are reflected in other customers' experiences, and revealing information that is often missing from product descriptions or official marketing materials. Historically, eBay made it possible for consumers to purchase products even from private sellers, largely thanks to its effective system for displaying seller ratings and reviews.
This role is particularly evident from the consumer's perspective, but the same reviews can become an equally valuable source of information for businesses. They allow companies to observe the market through customers' own words and understand which aspects are genuinely appreciated, which problems occur repeatedly, which expectations remain unmet, and which factors influence purchasing decisions. A company planning to enter a new market can therefore use reviews not only to monitor its reputation, but also to better understand demand, compare its positioning with that of competitors, and identify more effective messages for communication, sales, and product development.
Translating a website, adapting a catalogue, preparing dedicated campaigns, and listing products on one or more marketplaces while continuing to communicate the offering using the same arguments adopted in the domestic market risks overlooking precisely those aspects that new customers consider most important. A manufacturer may emphasize technical specifications while buyers are primarily concerned with ease of installation and support response times. A furniture brand may focus on design while customers mainly discuss delivery and assembly. A luggage manufacturer may highlight materials and storage capacity while reviews concentrate on wheel performance and zipper quality. In these situations, online reviews become a far more valuable source of information than their traditional use might suggest. They do not simply measure brand reputation; they make it possible to observe the market through the words of people who have already purchased, used, and compared products and services. Reviews contain insights into perceived benefits, problems encountered, unmet expectations, objections raised before purchasing, and the factors that genuinely influence customer choices.
Collecting and interpreting this content can, however, be complex and time-consuming. Generative Artificial Intelligence makes the process much more accessible because it can analyze large volumes of comments, classify recurring themes, compare brands and products, and identify patterns that would be difficult to detect through manual analysis. The starting point should not be limited to a company's own reviews, as the greatest value emerges from comparing what customers appreciate about the company, what they criticize, and what they appreciate or criticize about its main competitors.
This comparison can reveal the most credible differentiating factors, as they are based not simply on what the company believes it does well, but on what the market actually recognizes as a competitive advantage.
Analyzing Online Reviews to Improve the Value Proposition and Content
Companies know their products extremely well and therefore tend to build their communication around technical specifications, features, and the advantages they consider most relevant. Customers and buyers, however, may apply very different criteria and place greater importance on aspects that the company considers secondary.
A B2B machinery manufacturer may focus on speed, materials, energy consumption, and production capacity, while online reviews, comments, and discussions may reveal that purchasing decisions also depend on ease of installation, maintenance requirements, spare parts availability, the quality of technical documentation, or customer support response times. This information can significantly change how a product is presented. A generic statement such as "robust and reliable machinery" can be replaced with much more specific arguments that address buyers' actual concerns, such as ease of component replacement, multilingual technical support, or average spare parts delivery times.
The same principle applies to B2C markets. A luggage manufacturer may discover that customers mainly discuss how smoothly the wheels roll, the durability of zippers, and ease of use at airports. A furniture company may find recurring themes in reviews relating to delivery punctuality, consistency between product photographs and the actual item, and ease of assembly. A cosmetics brand, meanwhile, can observe the words consumers spontaneously use to describe texture, fragrance, packaging, and the overall user experience, allowing the company to align its communication more closely with its audience's language.
Reviews therefore become a valuable resource for improving product descriptions, landing pages, SEO content, sales materials, advertising campaigns, and marketplace listings, because they allow companies to focus on what customers genuinely consider relevant rather than exclusively on what the business wants to communicate.
The most appropriate sources naturally vary by sector. Google is particularly useful for retail, hospitality, professional services, and local businesses, while Amazon and other marketplaces allow companies to compare competing products and understand which features customers actually evaluate after purchasing. Trustpilot provides insights into the entire customer experience, covering not only the product itself but also deliveries, customer support, returns, problem resolution, and relationships with the company. In B2B markets, useful sources may include vertical marketplaces, professional directories, specialized forums, and industry communities.
The concept of reviews can also extend beyond end customers. Platforms such as Glassdoor and Indeed make it possible to observe how current and former employees describe a company, providing valuable information for businesses planning to enter a new market, establish a subsidiary, build a sales network, or attract technical professionals. In this context, competitive analysis concerns not only the commercial offering but also the development of employer branding strategies. Employee reviews may reveal perceptions of corporate culture, management quality, career development opportunities, training, and workplace flexibility.
From Sentiment Analysis to the Real Drivers of Purchasing Decisions
The simple distinction between positive, negative, and neutral reviews, typical of sentiment analysis software developed before the emergence of Generative Artificial Intelligence, provides limited information. It describes the overall tone of a comment but does not explain which elements caused satisfaction or dissatisfaction, nor does it clarify which factors genuinely influence purchasing decisions.
A more useful approach involves analyzing reviews through categories directly connected to the value proposition and commercial communication. This makes it possible to identify which benefits are mentioned most frequently, which difficulties arise during purchasing and product use, which concerns precede purchasing decisions, which expectations customers now take for granted, and which needs suggest opportunities that are not yet adequately addressed.
This type of analysis also helps identify genuine differentiating factors, as certain attributes may be more strongly associated with one brand than with its competitors and can therefore become credible communication messages. An effective product description or landing page should not simply list features. It should translate those features into benefits, address objections, reduce uncertainty, and clearly explain why customers should choose one solution over another.
A further level of analysis can be developed using the "Jobs To Be Done" framework, whose objective is not simply to understand what customers purchase, but which problem they are trying to solve. Someone purchasing industrial machinery is not merely buying production capacity: they may want to reduce downtime, simplify maintenance, lower operational risks, and minimize problems for the production department. Similarly, someone purchasing furniture online is not simply buying an item: they also want reassurance that the dimensions are correct, that the color matches the photographs, and that the product will arrive undamaged.
Reviews therefore help distinguish between functional, economic, and emotional motivations, while revealing which factors carry greater weight in a particular market. This is especially relevant in internationalization, as customer priorities may vary from one country to another, and a value proposition that works effectively in the domestic market may be less convincing elsewhere.
Competitive analysis becomes even more valuable when it highlights issues that matter to customers but are not clearly addressed by any competitor. These gaps can represent genuine opportunities in the market or in commercial communication and may suggest new positioning strategies. A recurring but insufficiently addressed need can become a sales argument, a new section of a product description, an FAQ, a service commitment, or an aspect to investigate during future product development.
How to Use Artificial Intelligence to Analyze Reviews and Competitors
To obtain meaningful results, it is advisable to clearly separate data collection from analysis. Direct access to online platforms is not always straightforward, as some websites restrict crawlers, require authentication, or load content dynamically. The most reliable approach often involves building a representative sample of reviews covering both the company's own products and those of its main competitors, collecting them in an Excel or CSV file, or manually selecting them when the volume is smaller, and only then submitting the material to Artificial Intelligence models for analysis.
The process can then become much more structured. AI can group comments by themes, problems, benefits, expectations, and differentiating factors; compare products and brands; and highlight areas where the company is perceived more or less favorably than its competitors.
ChatGPT can be used to analyze structured datasets and develop classification models. Claude can provide an alternative interpretation of the same material. Gemini can be particularly useful when working with documents and data within the Google ecosystem, while Perplexity can support the research phase and help identify publicly indexed sources. Using multiple tools can be especially valuable when dealing with large or ambiguous datasets, as it allows companies to compare interpretations and reduces the risk of relying on a single automated assessment.
However, the most important stage comes after classification, when data must be translated into decisions. The insights collected can be used to revise the value proposition, improve product descriptions, update landing pages, rewrite FAQs, develop new sales arguments, optimize advertising campaigns, and adapt content for international marketplaces.
For many businesses pursuing internationalization, a common risk is adopting an inside-out approach: translating the website, adapting the catalogue, and replicating abroad the same communication strategy already used in the domestic market. Review analysis makes it possible to reverse this approach and start by listening to customers. Companies can first observe how the market describes problems, expectations, and purchasing criteria, and only then decide what and how to communicate.
Artificial Intelligence makes this listening process faster and more systematic, allowing companies to transform hundreds or thousands of comments into a structured map of customer needs, pain points, and purchasing motivations. For a business seeking to enter new markets, this type of analysis can become one of the most accessible ways to reduce uncertainty and build a value proposition that is better aligned with actual market demand. Before convincing a new customer, a company must first understand the criteria that customer is already using to evaluate its products and those of its competitors.