SUMMARY
Why Choose AI-Supported Strategies
In an era like ours, where not adopting new technologies means losing a strategic advantage over competitors, artificial intelligence enhances the speed and frequency of implementing new techniques that can be valuable allies in supporting customer assistance.
While it is true that the AI available today is not yet capable of completely replacing a company’s customer care department, a hybrid system can greatly benefit from AI support in its operations.
AI for Efficient Shift Planning
For customer care departments within companies, it is important to manage workforce efficiently, minimizing operator downtime while also keeping customer wait times low.
In this regard, it is possible to analyze data related to peak request hours to efficiently organize work shifts for operators. This practice is not new and can be implemented using an algorithm that combines the number of available employees with the number of assistance requests, distributing work shifts based on historical data collected within a specific time frame.
The flaw in this approach lies in the use of historical data, which, by its nature, does not consider the real-time evolution of customer base needs.
This limitation can be overcome by a similar approach based on AI-powered data analysis, capable of reading real-time variations in request flows and adjusting staff shift distribution accordingly, automatically, without constant intervention from a data analyst.
With this practice, it is possible to vary the shifts of customer care employees from week to week based on the actual quantity of assistance requests received at different times. his enables maintaining a minimum number of customer care operators available during service hours and bringing in additional staff only during peak request times.
The Benefits of AI Application in Customer Care
- Improved efficiency in managing requests
- Reduced waiting times for customers, from request submission to actual contact with an operator
- Increased customer satisfaction
- Lower costs for operational staff management and data analysis
Conversational AI for Automating Intake
It is possible to automate the reception, routing, and in some cases, even the resolution of customer service requests through AI-based chatbots and conversational interfaces.
t is possible to automate the reception, routing, and in some cases, even the resolution of customer service requests through AI-based chatbots and conversational interfaces. Unlike old rule-based systems where user requests are funneled into conditional flows like “if A, then B,” artificial intelligence can understand the context and content of the request, providing a coherent response even if the question does not contain specific keywords.
Using AI-powered chatbots and automated responders for initial customer assistance contact can have two outcomes:
- Through AI responses, customers can autonomously resolve their issues quickly without human intervention.
- Through contact with AI, customers provide the system with all the information related to their assistance request, which is then forwarded to human staff to ensure precise, timely, rapid, and effective assistance.
The Benefits of this Strategy
- Customer ability to independently resolve their issues
- Increased profiling of customer assistance requests
- Faster resolution of requests by human operators
AI Sentiment Analysis to Improve Operator Approach
In customer care, AI can also play a role that is less operational and more focused on monitoring customer responses.
Sentiment analysis refers to the technique of evaluating opinions and emotions in textual or verbal content, assigning qualitative judgments such as positive, neutral, or negative.
AI-conducted analysis of customer responses can guide the operator towards a better understanding of the customer’s mood, enabling a more empathetic approach to resolving assistance requests.
This approach improves the user experience by making customers feel listened to and understood by the operator, who becomes a trusted consultant rather than just a means to achieve an objective.
Implementing this strategy offers several benefits, including:
- Increased customer affection and trust in the brand, as customers feel heard and treated as individuals rather than numbers.
- Greater awareness of brand perception.
AI and Machine Learning to Enhance Product Development
From a company’s perspective, customer care has a crucial function that goes beyond providing customer assistance and resolving issues: it includes listening to the audience.
Applying AI and machine learning analysis to customer service requests allows companies to identify and recognize patterns in the issues encountered by the customer base.
If many users contact customer care about the same problem, it is crucial data that the company can use to improve product usage instructions or the product itself.
Furthermore, becoming aware of frequently encountered issues can help the company immediately direct the training of customer care operators towards quicker and more effective resolution of assistance requests.
In the long term, data related to these patterns can be aggregated and analyzed for research and development purposes to improve the product in future iterations and eliminate the need for customer service contact.
Companies gain the following benefits from implementing this strategy:
- Clear prioritization of necessary product implementations for product roadmap management
- A deeper understanding of customer base needs, which becomes a strategic advantage over direct competitors
Discover Our Customer Service Solutions
INGO supports companies in creating customizedAI-powered customer service strategies that enhance efficiency and customer satisfaction. From the initial analysis phase to the implementation of integrated, scalable, and modular omnichannel strategies, for over 20 years, INGO has been representing the Made in Italy in the service of customer experience.
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INGO, thanks to multichannel and technological innovations, is able to build specific projects for each company, following the process from the initial analysis phase to the implementation of integrated, scalable and modular omnichannel strategies. For over 20 years, Made in Italy at the service of the customer experience.
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