- 63% of customers see service value as a crucial differentiator for companies.
- Businesses have long struggled to understand their service quality across all journeys and touchpoints. Manual analysis by employees is costly and inaccurate, while traditional sentiment analysis tools are too simplistic to deliver.
- Deep learning is changing that. Re:infer’s new Quality of Service feature uses state-of-the-art AI to capture business-specific customer intents, revealing just how successful businesses are at meeting specific, nuanced customer needs.
Customer and client service is a crucial point of competition across industries - from investment banking to insurance, telecommunications and e-commerce. Customers are constantly providing companies with feedback on their service. More often than not this feedback is implicit and requires human intelligence to understand, making it difficult to capture at scale.
Traditional sentiment analysis tools rely on broad stroke keyword matching or tone analysis to understand how customers feel. But they fail to get to the heart of what’s driving demand, and what customers really want.
Ed Challis, Co-founder and CEO at Re:infer, explains:
“Good service means more than politeness, tone and speed of response. It’s about intention. Do you understand what your customers want and expect from the interaction? Are you offering them constructive alternatives when their preference isn’t available? Are you actually answering their questions? You can’t know this with simple sentiment analysis or chatbots.
“Negative sentiment means it’s already too late. It’s a lagging indicator of service quality. That’s why you need deep conversational intelligence that extracts intention as well as emotion, predicts rather than reacts, running in real time and omnichannel. And you can’t discount domain knowledge when it comes to understanding your service quality.”
Key stakeholders lack the visibility and tools needed to quantify, track and improve the quality of service their business provides. They fail to understand customer needs, identify and get ahead of issues before they escalate. Furthermore, they struggle to demonstrate real improvements to service levels.
Introducing Quality of Service
But now Re:infer provides a new capability for businesses to accurately track and improve their service, with real-time monitoring and customised alerts across all touchpoints and service teams. Re:infer Quality of Service is a platform extension that uses in-depth sentiment, emotion and business-specific intent analysis to help users understand the quality of service their business delivers - in real time and at scale.
Quality of Service combines the intent of each message, domain knowledge of whether it’s a positive or negative event, and the tone and emotional content of the sender’s language. It collates this information into an overall Quality of Service Score (QSS), showing stakeholders at a glance if customer needs are being met by the service provided.
The QSS can be aggregated to different levels, per product, process, team and journey. This gives enterprises, for the first time, a quantifiable metric to understand and track the quality of service they provide to customers.
Quality of Service is highly customisable. It offers custom in-platform reporting and dashboards for actively monitoring quality of service trends at all service levels. Customisable alerts can be configured that are triggered by specific events or trends, such as deviations from acceptable quality of service levels. This gives users full visibility and control over their services.
Quality of Service event and sentiment models come pre-trained, meaning they work right out of the box. Models recognise urgency, escalations, chasers and other important message qualities with no training required.
Re:infer’s powerful machine learning models, coupled with fast and effective active learning techniques, also enable Quality of Service to understand industry-specific language and events. Employees can rapidly train the platform to recognise implied meanings and nuanced language, ensuring it accurately recognises positive and negative service experiences.
Re:infer’s multilingual models understand all major languages, making Quality of Service ideally suited for international services and operations. English, French, German, Spanish, Italian, Portuguese and Dutch are currently supported with Japanese, Korean and Chinese languages in development.
George Barnett, Head of Product & Operations at Re:infer, said:
“The client lifecycle is complex. Client relationships involve multiple people, teams and products and are mediated across multiple service and communications channels. What makes Quality of Service such a powerful tool is its ability to accurately extract customer intents and provide insights at any level - showing the service impact of a single message all the way up to the service quality of an entire function. Quality of Service will be invaluable to service, customer and operations leaders, giving them a tangible baseline from which to understand and improve their business.”
Quality of Service is available for purchase as an extension to the Re:infer NLP platform, or can be integrated with the solution during the initial deployment.
Re:infer is the Conversational Data Intelligence platform for the enterprise. Businesses use Re:infer to mine, monitor and automate their service conversations. Through our no-code NLP platform, we democratise the power of AI for every employee. Re:infer increases scalability, enhances the customer experience, and improves governance and control.
For more information, visit reinfer.io or contact firstname.lastname@example.org.