Watchers’ CPO Adel Gaisin discusses analytics, metrics, and user insights that can completely transform platform performance.

Adel Gaisin, CPO at Watchers, shares how their analytics system was built and can be used, how the company protects personal data and complies with regulations in different markets, and how user insights gathered from chats can change everything.

Adel Gaisin: “We know how to work with user feedback, extract the meaning, and communicate it to the client”

Collecting user insights is vital for providing a personalised user experience. Gathering information directly from your target audience will help improve the user journey and content strategy.

Learn how to collect first-party data with the right tools and why it matters.

How & Why Is Collecting Users' Insights Crucial for Your Business

<div style="font-size:14px;line-height:1;" id="toc">On this page&nbsp;&nbsp;<a href="#go-through-numbers">Going Through the Numbers</a>&nbsp;<a href="#why-direct-user-insights-matter">Why Direct User Insights Matter</a>&nbsp;<a href="#making-the-most-from-first-party-data">Making the Most of First-Party Data</a>&nbsp;<a href="#five-ways-to-collect-user-insights">How to Collect User Insights in Five Ways</a>&nbsp;<hr style="margin-bottom:1vw;">Continuous development, driven by customer feedback, is a crucial component of any successful business strategy. But when it comes to identifying these insights, where do you turn? The easy answer is providing cusdev interviews, constant focus groups, or just voluntary surveys or interactions, but there is a tricky point.Firstly, people participating in such research can be, on the one hand, not sincere enough — trying to be polite or not to look critical; on the other hand, they try to be helpful and notice all potential problems and mistakes, while at the same time losing their real user impression. They can help to find some platform’s inconveniences, but being in an artificial situation, they can skip what is really important. Also, participants of any focus group or custdev present just a tiny part of your audience. But where to get insights from real users in satisfactory amounts?Continuous improvement based on user feedback is key to a strong business strategy. But when it comes to understanding user needs, where should you look?<figure class="image" style="margin-bottom:1vw;"><img style="aspect-ratio:2410/1378;" src="https://cdn.eu.watchers.io/6a57aca0-b2be-49b1-b5cd-6960f8d1311d.webp" width="2410" height="1378"></figure>Obvious solutions include customer development interviews, focus groups, or voluntary surveys. Yet, these methods come with challenges. Participants might not be entirely candid, may overanalyse, or simply represent too small a portion of your audience. While these can uncover usability issues, they often miss the subtle behaviours that matter most. So, where do you get scalable, authentic insights from your actual users?One of today’s strongest approaches involves deriving real-time insights directly through your platform interactions. As digital marketing moves toward deeper audience understanding and AI-powered analysis, accessing meaningful audience signals is more critical than ever. But how do you translate engagement into strategic insight? And what tools make it easier?Focusing on users’ direct insights is one of the current digital marketing trends you can’t ignore, especially as the world heightens its focus on AI and datafication. However, many companies struggle to understand how to collect and utilise this information effectively. For example, why would you pick user insights over third-party data when the latter often comes cheaper? And what tools can you add to your platform to gather such primary insights?<h2 id="go-through-numbers">Going Through the Numbers</h2>Brands can obtain data from various sources. The most accurate information is acquired directly and consensually from the customer through surveys, questionnaires, reviews, social media engagement, and website interactions.Then you have second-party insights, which is very similar, except you’re using another company’s trusted first-party data. You interact with the company directly to obtain this information.Third-party data is different still. This is information typically purchased through an external data aggregator that has no direct contact with the customers. Third-party cookies, tracking details like browser history and time spent online, were once common in search engines, although companies like Apple and Google are already beginning to phase them out.<figure class="image" style="margin-bottom:1vw;"><a href="#go-through-numbers"><img style="aspect-ratio:1080/1080;" src="https://cdn.eu.watchers.io/c5d17a88-0299-418d-b5bc-b1f46e8cb28e.png" width="1080" height="1080"></a></figure>And lastly, zero-party data is a relatively new data type that is almost identical to first-party. This involves information voluntarily and explicitly given by the customer, such as purchase intentions and communication preferences.<h2 id="why-direct-user-insights-matter">Why Direct User Insights Matter</h2>Data benefits your business by providing reliable information collected directly from your target audience. That’s invaluable in a world where <a target="_blank" rel="noopener noreferrer" href="https://www.forbes.com/sites/shephyken/2024/04/14/the-personalized-customer-experience-customers-want-you-to-know-them/">81% of consumers prefer </a>a tailored experience. Brands must adapt their digital marketing strategies to offer more personalisation for their customers. From budgetary figures alone, we can see this trend taking shape. In 2023, <a target="_blank" rel="noopener noreferrer" href="https://admin.comviva.com/wp-content/uploads/2023/02/2023-Global-Survey-Report-The-Business-Value-of-Real-Time-Personalization-1.pdf">around 22% of a digital marketing budget</a> was allocated to personalisation. In 2024, that figure jumped to 40%. This highlights the significant importance of personalisation for both consumers and marketers.Direct users’ insights give you a deeper understanding of customer preferences and habits. You can identify which channels they prefer to interact with and learn about their browsing and purchasing behaviour in real time, what exact content they like and why. These insights then allow you to refine your marketing and content strategy to include personalised outreach and targeted ad campaigns, creating a more tailored approach and correcting the roadmap. And a more personalised approach brings additional benefits, such as brand loyalty and user engagement.<a target="_blank" rel="noopener noreferrer" href="https://www.researchgate.net/publication/367128795_The_Impact_of_Personalization_on_Customer_Loyalty_and_Retention">In his recent publication,</a> “The Impact of Personalization on Customer Loyalty and Retention,” Shezan Ahmed notes that “customers are more likely to make additional purchases and remain loyal to a business that personalizes their experiences.” Meanwhile, user engagement through first-party data is another benefit of increased personalisation. Customers are more likely to engage with your platform when you know exactly what they wish.By contrast, third-party data offers limited scope for personalisation. It does not come directly from your target audience, which means it provides little insight into the genuine wants and needs of your customers. This is why gathering first-party data is crucial.<h2 id="making-the-most-from-first-party-data">Making the Most of User Insights</h2>All sorts of companies can benefit from gathering first-party data. For example, sports apps, due to such insights, establish and sustain a likeable brand reputation — an important metric for clubs looking to cater to a diverse customer network.Another example? Fitness apps that use live streaming feeds for at-home personal training (like Peloton) can adjust staff schedules to accommodate busier times, thanks to insights on when users like to train and what kind of instructor they prefer.It’s evident that all of this is vital for companies in the entertainment industry. However, obtaining user insights can be difficult without adequate channels for user engagement.Collecting user insights helps companies identify the following user metrics: · Engagement levels · Busiest traffic times · Preferred communication channels · Most popular film and TV genres · Favourite sports to watch and bet on · Overall opinionsEntertainment businesses can then use these metrics to refine their offerings and enhance user engagement through the use of first-party data.<blockquote>User engagement is crucial for sports betting companies like Sky Bet and Paddy Power, where competition is fierce. If a sports betting app learns that its customers prefer to bet on tennis but have little interest in badminton, the site can then look to increase its coverage of tennis games (if it offers live streaming features) or broaden its betting markets for the most popular tournaments (like Wimbledon and the US Open). This data-driven marketing will likely increase customer retention and brand loyalty.</blockquote><h2 id="five-ways-to-collect-user-insights">How to Collect User Insights in Five Ways</h2>Implement a range of user insights collection strategies to gather a broad and varied scope of information from your customers.<h3>Use AI for Insights Collection and Tagging</h3>AI tools are on the rise. <a target="_blank" rel="noopener noreferrer" href="https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work">More than 92%</a> of businesses are looking to increase their AI spending over the next three years. Fortunately, AI and analytics combine well. You can use AI tools to gather vast troves of data, including customer purchase history and frequency of communication, at once. Automated algorithms track these metrics and record each time a customer interacts with your brand. They then collate this first-party data to build a profile of every customer, allowing you to personalise the experience for each user.<blockquote>Tools like Bardeen use natural language to implement workflows that can scrape and enrich data in bulk. Other apps, such as Databricks, facilitate data analysis by learning your analysis habits and preferences.</blockquote>But you’ll need somewhere to store the masses of data you collect from AI tools. That’s where data lakes come in. An alternative to the rigid structures of data warehouses, data lakes are more fluid and flexible. They can house large amounts of data and allow analysts to compare and extract insights more easily.<h3>Send Out Surveys &amp; Questionnaires</h3>Of course, there are other manual methods of collecting first-party data. Surveys and questionnaires are classic examples of obtaining primary data right from the source. You can learn lots from your customers if they complete the form, helping you identify what aspects of your site are under and what are overperforming. Incentivise your users to complete the survey by offering a reward, such as a discount or a free in-app item.<h3>Integrate community in-app chats</h3>Chat rooms provide a unique setting for data collection. They allow app users to engage with your brand directly, offering unfiltered views on your services and voluntarily divulging preferences. Plus, the time stamps from each message tell you the busiest communication times.<h3>Add Comment Sections</h3>Similar to live chat rooms, companies can retrieve valuable information from comment sections. For example, a broadcaster could learn when users are most active via the number of comments over a given period. This would then allow them to show targeted ads at the most advantageous times.<h3>Second Screens</h3>Use the stunning experience of La Liga and use second screens to offer a space where users can engage with others without leaving your platform. Instead of losing valuable data to messaging sites like X and WhatsApp, you can gain insights into customer behaviour by recording the interactions on your integrated second screen.<hr> You’ve learned how to collect first-party data and why this process is crucial for your business. This is not one of those digital marketing trends that will fade quickly. Start implementing it in your customer success strategies now.<hr>Please fill out the <a target="_blank" rel="noopener noreferrer" href="https://calendly.com/watchers-platform/social-tools-for-your?month=2025-08">Get in Touch form</a> if you'd like to integrate community chats and other tools for gathering user insights into your website or app. We'll be happy to help you find the best solution.</div>

What do your users really feel and think about your product, service, or content?

Unlock user insights with sentiment and semantic analysis. Learn how in-app messages, live chat, and comments help brands understand consumer feedback, enhance loyalty, and build a love brand. Discover the sources for actionable data-driven decisions

Semantic and Sentiment Analysis: What Are the Best Sources of Consumers’ Thoughts?

Table of contents<a href="#sentiment-analysis">Sentiment Analysis</a>&nbsp;<a href="#semantic-analysis">Semantic Analysis</a>&nbsp;<a href="#combining-analyses">Combining Sentiment and Semantic Analyses</a>&nbsp;<a href="#right-data-source">Finding the Right Data Sources&nbsp;</a>&nbsp;<a href="#gathering-in-app-data">How to Gather In-App Data</a>&nbsp;<a href="#watchers-semantic">How Semantic Analysis Works on the Watchers Platform&nbsp;</a>&nbsp;<a href="#get-in-touch">Get in Touch Sources</a>&nbsp;<hr style="margin-bottom:1vw;">Datafication is something we always talk about. We have data flows, we want as much data as possible, and we try to find a way to interpret it. Data tells us a lot, but not about the feelings of users. Imagine you have a user who has a subscription to your service. They spend time and money on your platform, consuming your content. You have as much data as possible about them, but once they cancel their subscription and switch to another platform, you attempt to win them back with offers and emails. However, by then, they are classified as churned. However, you still don’t know why this user left and what you actually need to offer to bring them back.It sounds like we are discussing not just a relationship with a user but a relationship with a significant other. But come on, aren’t your users significant to you? Of course, they are. And what is the best way to prevent a relationship catastrophe? Listening.Direct questions you ask your users do not always work well. A user must be extremely loyal and have plenty of free time to fill out occasional surveys about user satisfaction. If the user is no longer satisfied and decides to switch to another service, your final attempt with a five-question poll asking why they are leaving is a last-ditch foul, but you should have listened earlier.We can reflect on this for a long time. Still, two key methods really help you listen to your users and extract as many insights as possible: the first is sentiment analysis, and the second is semantic analysis.<h2 id="sentiment-analysis">Sentiment Analysis</h2>Sentiment analysis encodes the emotional tone of a text. Usually provided by NLP, this type of analysis can be applied to any text: social media posts, threads, comments on YouTube or Twitch, or survey results. Sentiment analysis is less about deep insights and more about understanding users’ feelings and satisfaction with a product or content. Typically, sentiment analysis categorises data into three groups: positive, negative, and neutral. All comments, responses, and messages—depending on your goal and the platform for analysis—fall into these categories.For example, if you release a trailer for a game or film, a demo of a new feature, or plan a rebranding for the product, you can gauge the general impression of your current or potential consumers. How do they feel about it? Good, bad, or indifferent? This allows you to address issues if something was not well-received.<figure class="image"><img style="aspect-ratio:1080/1080;" src="https://cdn.eu.watchers.io/5e4e283e-817c-49fd-8e49-58b944a04a7b.png" alt="Semantic and Semiotic analysis for marketing" width="1080" height="1080"></figure><h2 id="semantic-analysis">Semantic Analysis</h2>Semantic analysis provides specific answers. If sentiment analysis reveals that users did not like your trailer or feature, you need to find out why. Of course, you can try to survey a sample of people who had an adverse reaction, but a sample may not capture all insights. More importantly, consumers are less honest when asked directly than when they simply interact. When faced with someone responsible for the product, their behaviour changes—they become less critical, more polite, and ultimately less insightful.Semantic analysis helps by categorising discussions based on topics relevant to the content users are engaging with. For example, if it’s a film or game trailer, you can determine which aspects users discussed the most: graphics and CGI? Voice acting? Facial animations? An unrealistic plot? Predictable gameplay? Or perhaps the controversy surrounding the producer? Sentiment analysis may show that 60% of comments were negative, but the underlying reason for this negativity may vary widely. A controversy involving a key figure in the project is a very different issue from an unpleasant voiceover.<h2 id="combining-analyses">Combining Sentiment and Semantic Analyses</h2>It’s best to combine both analyses. First, use sentiment analysis to understand the general attitude toward your content—was it positive, negative, or neutral? Once you have an answer, apply semantic analysis. It identifies the most and least discussed topics as well as the words and concepts users mention most often. Such a simple technique can provide valuable insights.If you want to dig even deeper, use sentiment analysis again, but this time, apply it to specific sets of messages or comments. For example, suppose semantic analysis shows that a significant portion of comments is about CGI. Are most of these comments positive or negative? Another popular discussion topic is the production team—what is the sentiment there? Good, bad, or neutral?It’s not just about raw data—it’s about interpretation, not subjective but direct and objective. You may have 10,000 comments under posts about two games you promoted. Both posts have excellent engagement rates, suggesting your brand is popular. However, sentiment analysis reveals that the first post’s 10,000 comments are mostly negative, while the second’s are predominantly positive. Meanwhile, semantic analysis shows that the positive comments were about the winning team, whose fans flooded the post to celebrate, whereas the negative comments stemmed from technical issues on your platform. Despite high engagement rates, analysis reveals the actual reasons behind the activity.<h2 id="right-data-source">Finding the Right Data Sources</h2>Of course, data is necessary for such analysis, and social media is an obvious feedback source. But is it truly the best? Are those commenting on your posts actual users, or did they simply see the post in their feed, leave a comment, and move on?For some businesses, this distinction is not critical. If you are marketing a new product that is available everywhere, social media is ideal. However, if you are marketing a service, platform, or content exclusive to a&nbsp;specific platform, analysing social media may not provide the insights needed to refine your strategy or improve your product. In such cases, in-app messaging is the most valuable data source. Users share their emotions and opinions while consuming content, not through structured surveys but in organic discussions with each other. Such feedback is far more sincere and, therefore, more insightful.<h2 id="gathering-in-app-data">How to Gather In-App Data</h2><h3>Public Live Chats</h3>When users have a space to discuss topics they enjoy openly, they become honest. They discuss both the&nbsp;advantages and disadvantages of your platform and may even debate among themselves. This not only boosts retention and engagement but also provides you with valuable, unsolicited feedback—at no additional cost. Public chats can be integrated in various ways, such as a general lobby for all conversations or dedicated chats for specific events or content pages.<h3>Comment Sections</h3>Like event chats but designed for long-term discussions rather than real-time interaction, comment sections provide direct feedback at all times. Media platforms, streaming services, and marketplaces can all introduce comment sections to continuously receive user insights. Publishers claim that comment sections also increase time spent on the platform and subscriber numbers, as users often need to sign in to participate.Moreover, an essential aspect of in-app data for sentiment and semantic analysis is that you own the data. On&nbsp;social media, inappropriate comments may not be visible, meaning they are excluded from analytical tools. However, on your platform, even hidden comments can be analysed, allowing you to understand what truly frustrates your users.<h3>In-App Live Streaming</h3>Live streaming is an exceptional source of insights because it is spontaneous, engaging, and real-time. Users are accustomed to following Twitch influencers who analyse content or products, and they trust these influencers. If an influencer streams directly on your platform, users will still be direct and honest.<h2 id="watchers-semantic">How Semantic Analysis Works on the&nbsp;Watchers Platform</h2>Our clients can analyse messages sent to any chat <a target="_blank" rel="noopener noreferrer" href="https://watchers.io/post/How-and-Why-Is-Collecting-First-Party-Data-Crucial-for-Your-Business">using AI-powered tools</a>. Messages from a given period are forwarded to the AI tool, and clients can select from various analysis prompts or customise them for optimal results. The system categorises messages, enabling clients to understand the most frequently discussed topics, the sentiment behind them, and the most commonly used words and phrases.Semantic analysis can also serve specific purposes. For instance, one recent analysis revealed that the client's public chat contained messages in six languages. However, 60% of the messages were in French, with the most common words being gagner, real, psg, lyon, and mbappe. With this info, the client understood which events to prioritise on their platform’s homepage.<h2 id="get-in-touch">Get in Touch</h2><span style="font-style:normal;font-variant-alternates:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-emoji:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-variant-position:normal;font-weight:400;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;">If you want to integrate community-based live chats or other social tools into your website or app and receive insights about user behaviour, <a target="_blank" rel="noopener noreferrer" href="https://calendly.com/watchers-platform/social-tools-for-your"><span style="font-style:normal;font-variant-alternates:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-emoji:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-variant-position:normal;font-weight:400;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;">book a&nbsp;call</a><span style="font-style:normal;font-variant-alternates:normal;font-variant-caps:normal;font-variant-east-asian:normal;font-variant-emoji:normal;font-variant-ligatures:normal;font-variant-numeric:normal;font-variant-position:normal;font-weight:400;text-decoration:none;vertical-align:baseline;white-space:pre-wrap;"> with our team. We will help you find the best solution for your engagement strategy.***<h2>Sources</h2><ul><li>YouTube Comment Analyzer Using Sentimental Analysis | <a style="background-color:transparent;" target="_blank" rel="noopener noreferrer" href="https://www.researchgate.net/publication/381412037_YouTube_Comment_Analyzer_Using_Sentimental_Analysis">International Research Journal on Advanced Engineering Hub</a></li><li>Brand meaning and its social categories: A semiotic approach for future marketing | <a class="nova-legacy-e-link nova-legacy-e-link--color-inherit nova-legacy-e-link--theme-decorated" style="border-width:0px;color:inherit;cursor:pointer;display:inline;font-family:inherit;font-size:inherit;font-weight:inherit;margin:0px;outline:0px;padding:0px;text-align:inherit;" target="_blank" rel="noopener noreferrer" href="https://www.researchgate.net/publication/365152542_Brand_meaning_and_its_social_categories_A_semiotic_approach_for_future_marketing">Journal of Eastern European and Central Asian Research</a></li><li>Semiotics in Marketing: What It Means for Your Brand and Messaging | <a style="background-color:transparent;" target="_blank" rel="noopener noreferrer" href="https://cxl.com/blog/semiotics-marketing/">CXL Blog</a></li><li>What Is Sentiment Analysis Marketing? Tips, Tools, and Techniques | <a target="_blank" rel="noopener noreferrer" href="https://www.semrush.com/blog/sentiment-analysis-marketing/">SemRush</a></li><li>How &amp; Why Is Collecting Users' Insights Crucial for Your Business | <a target="_blank" rel="noopener noreferrer" href="https://watchers.io/post/How-and-Why-Is-Collecting-First-Party-Data-Crucial-for-Your-Business">Watchers Blog</a></li></ul>

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