E.ON’s Success with SentiSquare: Unlocking Customer Insights from Vast Feedback Data

What they say about us

“With SentiSquare AI, we better understand customer pain points and focus our initiatives where they are most needed.”

Jana Hrabětová

,

Company Development @ E.ON

Challenge

E.ON, an energy provider, faced a significant challenge in managing and analyzing a large volume of customer feedback received from various touchpoints and third-party services. With over 12,000 open feedback pieces each month and subtle differences between topics, classifying and understanding customer sentiments became a daunting task. To tackle this issue, E.ON deployed SentiSquare AI, an advanced artificial intelligence solution that brought together all feedback sources and provided automatic recognition of topics and sentiments.

E.ON received an overwhelming amount of feedback from customers across multiple channels and interactions with third-party contractors. Manually sifting through and classifying the feedback to gain valuable insights was a time-consuming and challenging process. Subtle nuances in customer feedback made it difficult to accurately categorize topics and determine customer sentiments.

Solution

In response to these challenges, E.ON decided to leverage SentiSquare AI, an innovative AI-powered platform designed to handle natural language processing and sentiment analysis. The implementation involved integrating all feedback sources into the SentiSquare system to create a comprehensive 360° view of customer sentiments and topics. The AI model was trained to recognize and categorize feedback across different touchpoints and regions, including interactions with third-party contractors.

Comprehensive Feedback Aggregation: SentiSquare AI seamlessly aggregated feedback from various sources, consolidating customer sentiments and interactions with third-party contractors. This holistic approach provided E.ON with a complete picture of customer perceptions.

Automatic Topic and Sentiment Recognition: The AI system employed state-of-the-art natural language processing algorithms to automatically identify and categorize customer feedback based on topics and sentiments. It efficiently analyzed the subtle differences between feedback pieces, streamlining the classification process.

Actionable Insights: With SentiSquare AI’s precise topic and sentiment recognition, E.ON gained valuable insights into what drove the Net Promoter Score (NPS) at each touchpoint, regional level, and even specific interactions with third-party contractors. This granular understanding allowed E.ON to make data-driven decisions to enhance customer experience and loyalty.

Collaboration results

The deployment of SentiSquare AI provided E.ON with transformative results:

Enhanced Customer Understanding: E.ON now possesses a comprehensive view of customer sentiments and preferences, allowing them to identify pain points, areas of improvement, and potential opportunities for enhancing services.

Targeted Improvement Strategies: By knowing the drivers of NPS at each touchpoint and region, E.ON can implement targeted improvement strategies tailored to specific customer needs and preferences, thus maximizing customer satisfaction.

Time and Resource Savings: The automation of feedback analysis significantly reduced the time and resources previously spent on manual work, enabling E.ON’s teams to focus on taking action and addressing customer concerns proactively.

Through the deployment of SentiSquare AI, E.ON successfully addressed the challenges posed by a vast amount of customer feedback from various sources. The AI-powered platform provided a 360° view of customer sentiments and topics, allowing E.ON to gain actionable insights and improve customer experience at all levels. With SentiSquare, E.ON is now better equipped to deliver exceptional service and drive customer satisfaction, securing its position as a customer-centric leader in the energy industry.

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“At Kooperativa, we strive to achieve the best possible Customer Experience, and it would be very difficult for us to progress without the analysis of unstructured data. With AI technology as an integral part, SentiSquare's tool makes this job much easier.”

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"At Raiffeisenbank, we have long been interested in the voice of the customer, we try to obtain feedback in various ways and use it to improve our services but also to motivate our employees. This approach provides us with extensive data from clients, their comments, remarks, and ratings. And because we don't want any opinions to get bogged down, we’ve deployed SentiSquare AI on top of that data to help us process it. SentiSquare AI can structure the unstructured data into ready-made categories so that our employees, CX experts, and managers can see what resonates with our clients. It can also catch sentiment from comments or clients who require our help and need to be contacted immediately to resolve their issue. We also use the system for cases where clients are reacting irritably or it’s clear from their response that it wouldn’t be appropriate to contact them further, and we also adjust our client outreach policy as a result. Deploying SentiSquare AI has saved us a lot of capacity and time when addressing some needs manually or through simpler mechanisms. It has also increased the interest in client feedback outputs, as categorizations and structuring have made it more digestible and clearer for the end recipients. Moreover, everything is done in a purely automated way, so there’s no need to worry about the whole mechanism in any dramatic way.”

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“Customer care has an important role in FTMO. Often these are recurring queries, where SentiSquare text analytics helps to speed up responses to our clients and save routine work for agents. This allows them to focus on more complex queries.”