5 TIPS FOR GENERATIVE AI IN CUSTOMER SERVICE

A recent survey of executives also suggests a promising trend: 73% of respondents believe that generative AI will have a positive impact on their customer success.

These are highly compelling figures. So, for those looking to increase efficiency or improve customer support, generative AI is the way to go.

Studies also show that three out of four use cases of the technology focus on four key areas, including customer service, sales, and marketing.

And nearly two-thirds of executives recently surveyed by KPMG believe that generative AI will play an important role in their companies in the next three to five years. With further technological advancements, it is essential to prioritize the implementation of generative AI – both to remain competitive and to achieve the best results possible. In this article, you'll find five tips on how to optimize the use of generative AI in customer service.

Senior Content Strategist | Freshworks

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TIP 1: PERSONALIZED COMMUNICATION

Train AI for Conversational Leadership: Enhance Your Customer Service with Large Language Models that Can Better Capture and Imitate Human Language and Behaviors. This way, you can better understand customer inquiries, respond more precisely, and tailor communication to be more personal. Here are some specific tips on how to adapt an AI model to your company's needs:

Tone: Train the AI to represent the language and values of your brand. For example, it can be designed to be especially friendly, accessible, or even humorous.

Empathy: Empathetic responses increase customer satisfaction and ensure a natural conversation flow. The AI should, for instance, be able to recognize the customer's emotional state, show understanding for their situation, and offer encouragement.

Natural Language: Ensure that your AI can account for the subtleties of human language, such as colloquialisms and context, to always provide an appropriate response. This can be achieved by training the model on large corpora that include various dialects and writing styles.

Multilingualism: It might be worthwhile to offer a multilingual customer service. This way, you can personally attend to customers from different countries. However, this requires training data in multiple languages.

By adapting the AI model to the needs of your company, you increase its effectiveness and efficiency.

TIP 2: HUMAN SUPPORT

Generative AI cannot replace your employees but should be seen as additional support for better, more personalized, and faster service.

For example, if a customer contacts with an urgent issue, the AI can immediately analyze the request, search for suitable solutions, and suggest appropriate actions.

For a consistent and efficient customer experience, it is essential to strike the right balance between automation and supervision.

Automation is particularly suitable for routine tasks such as answering common questions or handling simple issues. This relieves your employees, who in turn have more time for particularly complex or sensitive matters.

To strengthen customer loyalty and interaction, direct communication between AI and staff is also recommended so that inquiries can always be forwarded to the right place immediately.

In essence, generative AI is like a turbocharger that gives your customer service an extra boost. It ensures that routine matters are handled as efficiently as possible, allowing team members to focus better on more challenging questions and particularly important conversations.

TIP 3: DATA protection

AI models require high-quality training data that is representative of actual customer interactions. For privacy reasons, this data must never contain personal data of real customers. Instead, only anonymized data from customer service should be used. With every innovation in AI, the utmost importance must also be placed on data security. Pay particular attention to never sharing your data with external parties.

Here are some recommendations for data privacy and security when training generative AI models:

No personal data: Personal data allows conclusions to be drawn about specific individuals; using it is considered a violation of privacy.

Only anonymized data: Only use data from which all personal information has been removed. This makes it nearly impossible to draw conclusions about specific individuals; such data offers significantly more security when training generative AI models.

Data security: Protect your training data from unauthorized access. It is best to use encryption or other security mechanisms.

These recommendations help ensure data privacy and security when training generative AI models.

TIP 4: MONITORING AND FEEDBACK

Artificial intelligence is good at actively providing relevant data. This allows you to make informed decisions more quickly. And with AI-based feedback, you can immediately identify areas for improvement, optimize your communication, and identify any bottlenecks.

For example, the AI can be used for the following purposes:

Efficiently create and edit complex reports

Highlight important data and recommendations to identify optimization potentials

Increase operational efficiency – by automating tasks such as report retrieval or calculations

Provide prompt-based recommendations for further action and provide relevant information to executives to enable them to make informed and successful decisions

TIP 5: INTEGRATION

To seamlessly integrate generative AI into your existing software landscape and infrastructure, you should consider the following:

Clarify AI compatibility with existing processes and systems: Get an overview of the data formats, APIs, and security requirements of both your existing systems and the new generative AI platform.

Adapt processes and responsibilities: Adjust procedures related to data collection and training, as well as the deployment of your models if necessary.

Thorough integration testing: By carefully testing the integration in advance, you can eliminate any problems before they affect the production environment.

Gradual introduction of generative AI: This way, you can test the performance of your AI and make adjustments if necessary.

Freshworks develops AI-powered enterprise software that anyone can use. Our products are purpose-built for IT, customer support, sales, and marketing teams to help everyone work more efficiently and deliver value for immediate business impact. Freshworks is headquartered in San Mateo, California, and operates globally to serve more than 65,000 customers, including American Express, Blue Nile, Bridgestone, Databricks, Fila, Klarna and OfficeMax. For the latest company news, visit www.freshworks.com

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