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Sentiment Analysis: Why you Need it?

Task: "Measure the mood of each of your customers. Then the mood of potential customers. Add up these numbers. What answer did you get?". Agreed, the condition sounds rather unusual. But don't rush to find a ruler or open a textbook. Let's talk about the important things in business and how to measure emotions and digitise sentiment.

Sentiment analysis allows you to understand how users feel about certain products, services, brands or events. A few decades ago, salespeople had to knock on doors not only to offer products, but also to find out what customers want, what they think, and what they live by. Now, in the age of universal digitalisation, the internet and social media, it's easy to collect analytical data about customers. It requires tools that can integrate the processes of monitoring and analyzing information.

Monitoring 24/7. Not enough!

How do you track the response to your ads? Which online marketplace or platform has the most impact on your business? Without analysing consumer reactions it is impossible to make any meaningful business changes, improve your product or change your service processes. Monitoring 24/7 data from analytics programs only gives us dry numbers and reporting graphs that are hard to find a person in. Special metrics, such as customer satisfaction levels or the emotional attachment index, are introduced to gauge customer emotions and moods.

Dropshipping and analysis tools

Incorporating sentiment analysis tools into the dropshipping business model helps to adapt sales strategies, test new ideas, track feedback, analyse feedback, comments and social media postings. This helps to understand which aspects of the business are generating positive or negative reactions from customers. Life has moved online, sharing reviews, giving likes, rating a service, has become commonplace, especially for the new Internet generation. Customers share their positive or negative experiences with brands, describe their impressions of a brand's products or services, post comments on social media, tell on forums, platforms and websites. These posts are a snapshot of the customer experience.

Usually, when a company launches a new product or offers a new product to the market, it closely monitors consumer reactions. Test data can become part of the evolution of the product lifecycle. They are analysed and compared with competitors' offerings.

Instead of a line, an algorithm and automation

Step Link has introduced new analytics algorithms into its functionality that provide real-time information on customer sentiment, user experience and the reputation of brands represented on the platform. They are used to conduct:

- Monitor social media (Facebook, Instagram and Twitter). Scan social media and collect positive and negative feedback about the brand and its offerings.

- Monitor brand awareness, reputation and popularity at a particular point in time or over time.

- Analyse consumer perception of new products or features to identify possible product improvements.

- Evaluating the success of a marketing campaign.

- Identifying target audience or demographic data.

Collecting data, adding CRM

The sentiment analysis process typically involves: data collection (web scraping, identification), data cleaning (machine learning algorithm automatically extracts textual functionality, determines negative or positive evaluations), sentiment classification.

Customer service platforms integrate with customer relationship management (CRM) systems. This integration allows you to quickly identify conversions for each platform and platform used, understand how many users have converted to customers on each platform, and calculate the cost per conversion.

Scenarios and Forecasts

Step Link Platform's sentiment analysis tools can detect emotionally charged reactions, e.g. they can even detect sarcasm in the text when monitoring reviews. By analysing trends in a certain market and processing the incoming external data, the algorithm compares the performance of certain market offers to others. Sentiment analysis tools combine the results of customer sentiment data with other contextual data, including surveys, mentions in articles and online reviews. This feature helps predict customer behaviour.

Social media monitoring tools integrate with Facebook, Instagram and Twitter. Scanning mentions on social networks, news sites and search results allows you to analyse customer sentiment not only in terms of their relationship to the brand, but also by comparing it to competitors.

Step Link Platform monitors user reactions to products on the platform by connecting additional sentiment analysis tools. It monitors new trends and competitive ideas, examines social media sentiment, identifies service issues and optimises query categorisation.


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