An unbeatable duo for outstanding customer experiences
Did you know that for many customers, the product is not the decisive criterion for why they buy from a company? The decision for or against an offer is often based on the customer experience. With AI in customer service and a powerful CRM, you can position your company correctly today to be able to meet customer requirements in the future.
Table of contents
Availability
Availability is just as important as personalization. This means being available not just from 9 a.m. to 5 p.m., but around the clock if possible. Here, too, AI in customer service is an efficient approach, for example in the form of chatbots. Chatbots don't have to work after hours or during lunch breaks, and they are able to solve more and more problems without human help. Thanks to AI, your customer service is therefore almost always available, helpful and cost-effective. Here too, it is particularly promising to link AI with the CRM system. With the "background knowledge" from the CRM, for example, an AI assistant can not only provide standardized answers, but also respond specifically to the respective needs of the customer.Seamless experiences
The omnichannel approach to customer service is closely linked to the topic of availability. Omnichannel means being available on as many channels as possible. This is nothing new; most companies use multiple communication channels such as email, telephone, trade fairs, events, social media, websites or landing pages. However, in order to offer real added value, it is crucial to link the channels together. Ideally, a customer can seamlessly start an interaction on Instagram, continue by email and finish on the phone. Thanks to AI in customer service and CRM, all data is available globally and a seamless customer experience is created.
Fast and efficient help
In addition to innovations, support should also master old virtues - in other words, provide efficient help quickly. AI also provides support here: many issues can be resolved without human assistance, including queries about the status of an order or questions about a product.
How can AI help in customer service?
Artificial intelligence in support offers a range of possibilities. Different types of AI are used. Depending on its type, AI is able to perform more or less complex tasks. These AI models are currently used in customer contact:
- Reactive AI is programmed to provide standardized responses. A simple example: customers can click on a button and receive information about the status of their order.
- Generative AI is able to evaluate text and respond individually. Corresponding AI bots are suitable for web chat applications. The more extensive their access to data in the CRM system, the more precise the (voice) output.
- KIM (artificial intelligent machines) have advanced capabilities, for example in recognizing human emotions(mood watch). They are also able to improve themselves through machine learning. Some of these capabilities, such as recognizing moods through voice analysis, are already being used in support.
Automation and relief for employees
Many tasks can be automated with AI in customer service. These include recording data during initial contact, answering recurring questions and identity verification. This reduces the workload on your service staff and ensures that the department becomes more productive with the same working hours.
Provision of information in real time
A major advantage of AI in customer service is the very fast data processing. It makes it possible to evaluate customer input in real time and provide information to your "human agents" within seconds. A particularly prominent example is the "next best action" - i.e. a recommendation for the ideal next action in direct customer contact.
Data evaluation from selective to big data
AI has enormous potential in support when it comes to evaluating data. With the help of advanced algorithms, it is possible to search and structure huge data sets and derive profitable insights from them. This is why the term "data treasure" is increasingly being used in connection with data analysis.
Analysis of tickets
Another benefit is the analysis of tickets, for example to prepare them for processing. If a lot of data is generated, AI in customer service can help to solve potential problems at a higher level. For example, as part of an AI-supported ticket analysis. The following overview illustrates what AI functions can do here.
- Number analysis: How often did the same problem occur? Are there clusters at certain times of year? The AI can carry out comprehensive numerical evaluations and create compact reports from them. This saves working time and makes support more productive.
- Prioritization: If specific selection rules are defined, the AI can prioritize tickets. This ensures that important requests are processed first.
- Classification: Technical support, accounting or complaints - the AI can assign tickets that were created externally to an internal department. This saves human labor at this point.
However, AI reaches its limits when it comes to complex requests, data protection-related actions or individual problems. Tickets of this type are usually automatically forwarded to contact persons in the service department.
Advantages of CRM and AI in customer service for companies
Why are more and more companies relying on automated support solutions? The benefits range from financial aspects to productivity gains and improved customer loyalty. The most important arguments for the introduction of AI in customer service are
- Faster problem resolution without waiting time for customers thanks to chatbots
- Cost reduction through automation
- More efficient use of existing data
- Stronger customer loyalty through personalized service
- More recommendations thanks to delighted customers
- Higher sales through AI-supported upselling
Good to know: The benefits result from the individually selected AI strategy for your company.
How to integrate AI into customer support
There are three basic ways to implement AI in customer service:
1. external AI functions
The simplest option is for your customer service employees to use artificial intelligence in the form of external software solutions. This means that there is no interface between the company software and the AI. In this way, only simple data evaluations can be realized by the AI. Due to the limited possibilities, the solution is cost-effective and easy to implement.
Example: Customer Service would like to know which problems have occurred most frequently in the past two years. To do this, data is anonymized and transferred to an Excel spreadsheet. This serves as the basis for evaluating the request with programs such as ChatGPT-4.0.
2. hybrid AI environments
Hybrid AI environments are frequently used. This means that several programs are used in the company, each with highly developed AI functions. If you opt for this solution, you have a wide range of options and can combine the technologies individually(best-of-breed approach).
Example: A company has noticed that the number of shopping cart abandonments is high. Customer Service then starts an AI-supported analysis that can be performed directly from the CRM. This means that no confidential data is leaked from the company's internal IT environment. With the help of predictive analytics, critical customer behaviour can be better predicted in future so that preventative measures can be introduced to minimize shopping basket abandonment. You can use another AI tool to develop innovative measures to reduce shopping cart abandonment and document results and campaign activities in CRM.
A second example of the use of integrated AI is the personalization of mailings. To do this, artificial intelligence generates an individual approach that matches the needs (needs, wishes or requirements) of your distribution group
3. fully integrated AI
There are also fully integrated systems in which AI is available across various services and combines the CRM and contact center software, for example. This enables advanced customer service offerings.
Example: A customer wants to complain about a product. The chatbot has access to the order history in the CRM and processes the request automatically.
The AI recognizes the problem and uses predictive analytics to determine the next best action.
For example, this could be a how-to list to resolve the problem by the customer themselves or forwarding it to a real contact person. At the same time, the AI can leave a note in the CRM that the customer is dissatisfied with a particular product.
Data quality and data expertise as a prerequisite for outstanding customer service with AI
Well-maintained data and employees with a high level of data expertise are just as crucial as a technically modern solution. The CRM system therefore plays a central role in the AI world of the 21st century. The CRM manages the central treasure trove of data when it comes to customer relationships and customer service. With a CRM system such as Gedys CRM, you set the course for high data quality, the basis for AI-supported actions.
How do AI and CRM work together? 5 scenarios
The CRM system provides the data basis and ensures data quality. These five scenarios from everyday business life show how the two solutions interact successfully.
- Automated customer communication
CRM system: provides data on customer history and for identity verification
AI: reacts to customer input in real time, analyzes the customer's request, forwards it to a contact person or resolves the request automatically - Prediction of customer needs (predictive analytics)
CRM system: provides the database on which the AI works - for individual customers as well as customer groups
AI: creates recommendations or automatically initiates service offers - Self-service
CRM system: offers customers access to their own customer data for processing
AI: supports customers in solving inquiries on their own, for example using a chatbot - Ticket assignment
CRM system: provides a data basis for evaluation and supplies data for the service employee
AI: analyzes customer inquiries, compares them with historical data from the CRM and forwards customers to suitable contact persons - Prioritization of requests
CRM system: contains data on all customer activities (e.g. frequency of inquiries)
AI: decides on the basis of the existing data, according to previously defined rules, which inquiries are processed first
Conclusion: CRM and AI in customer service secure competitive advantages for the future
These use cases show that CRM and AI work closely together in many areas of customer service. To maximize the benefits, it is advisable to plan the use of technology from the outset. A successful strategy leads from a well-thought-out specification sheet to the CRM checklist to the selection of the best software for your needs. It is then helpful to train your teams intensively so that the technology is used correctly right from the start - for the greatest possible success in the company. You will then be able to offer personalized, fast and cost-effective customer service - and thus secure one of the most important competitive advantages of tomorrow.
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