Thanks to the Artiwise team, we can analyze our data quickly and take action based on real-time insights. Whenever we need, we can access all data at branch and store level, making our company’s strengths and areas for improvement clearly visible—together.
In banking, it is not always possible to put artificial intelligence directly in front of customers. With Artiwise, we chose to embed AI into our operations first—making employees’ work easier and reducing error rates. As a natural result, we clearly observed an increase in customer satisfaction.
As a 101-year-old institution, we have always placed customer interest at the center. While seeking solutions that deepen our customer experience focus through new technologies, we established a highly valuable collaboration with Artiwise. With teams working as one, this synergy delivered successful results in a short time.
This year, we truly worked as one team with Artiwise in a highly productive way. We integrated many channels including the call center, complaints, chatbot, social media, and branch correspondence. Being able to analyze all customer voices in an integrated manner became one of the most satisfying outcomes across the organization.
We had conducted similar studies before, but never at this scale or with such a large volume of data. Together with Artiwise, we transformed experience data into a structure accessible to all teams—not just one. Now everyone sees the same data and speaks the same language.
We are not on the front line of direct customer interaction; we focus on channels where technical issues arise. By bringing together all customer voices—surveys, social media, and complaint channels—we made common problems visible in one place. This allows us to detect issues before they turn into warranty costs and act more proactively.
Raw customer data alone has no meaning. With the AI-powered Artiwise CXM, we transform this data into actionable insights and detect part- and defect-based signals at an early stage. In many cases that later reflect on warranty, we clearly see that Artiwise identified the issue in advance—providing proactive alerts and acting almost like a working companion for our teams.
At its core, the problem is simple: moving the customer smoothly from point A to point B. But due to the scale of operations, we needed a structure that simplifies the process. With Artiwise, we gather all data in one place, see disruptions more clearly, and make the end-to-end customer journey fully visible.
Before Artiwise, we spent weeks manually reading customer complaints. In the very first outputs, we saw that the results perfectly matched our manual analyses. Beyond the technology, we built a truly strong partnership through both ways of working and communication.
Artiwise provides a powerful analytics platform, but the real value emerges through mutual feedback between teams. Thanks to this collaboration, we regularly produce brand-level insights and report them to our manufacturer. Analyzing data and closing the feedback loop takes these outputs to a much higher level.
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Customer sentiment analysis is a data processing technique that evaluates and interprets customers’ opinions, emotions, and attitudes from their written or spoken feedback. This analysis transforms subjective “customer sentiment” into actionable insights, allowing businesses to understand and respond to customer perceptions effectively.
Customer sentiment analysis is crucial for businesses because it enables them to understand the emotions and opinions of their customers towards their products or services. This understanding helps in identifying customer needs, improving product quality, enhancing customer service, and tailoring marketing strategies.
Real-time sentiment analysis plays a pivotal role in the realm of Big Data. As people actively share their views and opinions on platforms like Facebook, a wealth of textual information is generated in real time. By analysing this data, we gain insights into public sentiment, political decisions, and public opinion. Organisations can leverage sentiment analysis to monitor brand experiences, customer sentiments, and campaign performance. It’s a powerful tool for understanding how people feel about specific subjects, making it essential in today’s data-driven landscape.
