Why bot personas are the key to
better chatbots

Imagine visiting a website and being greeted by a competent virtual assistant. They understand your questions immediately, offer helpful solutions and make you feel like you're chatting to a real person. Now imagine the opposite: an impersonal, halting dialog with a bot that doesn't really understand your concerns. This is the difference between conventional chatbots and those based on data-driven bot personas. But how exactly are these digital personalities created? And how do they contribute to better efficiency and customer loyalty? In this article, you will find out why bot personas are the key to better chatbots - and how your company can benefit from them.

With increasing competition, companies need to perform at all levels in order to remain competitive. This includes customer service that answers questions in real time, solves problems without long waiting times and interacts empathetically with customers at all times. The fact is, however, that most companies lack the resources to do this. The solution: chatbots that take over a large part of the communication. According to a Bitkom survey of German companies, 86% rely on artificial intelligence for customer contact. And it's not just corporations that rely on AI-based solutions, but also SMEs: For example, every second medium-sized company already uses artificial intelligence for email response management and/or automation in customer care while more than 3 in 10 respondents, use ChatGPT as a chatbot. The figures show: In order to remain competitive, the use of AI in customer service is mandatory.

What can chat bots do and what can't they do?

From automated chatbots that provide proactive advice and answers in real time to virtual assistants that process complex inquiries, companies are spoilt for choice when it comes to intelligent AI customer service. Algorithms process language and help the bot to understand customers and answer questions precisely. At the same time, sentiment analysis machines recognize emotions in real time - important for chat bots to respond empathetically to concerns and feedback. Using AI-supported databases that can be operated intuitively, customers receive answers to their questions in the shortest possible time - which significantly increases efficiency in customer service. However, despite all this efficiency, bots are still machines - they are unable to feel their own emotions or empathize with the emotional world of their customers. As a result, interactions with the digital helpers of many companies still feel technical and impersonal. So what distinguishes bots that can hardly be distinguished from humans based on their interactions with customers? The answer: these companies have trained their AI. Data-based bot personas are an important tool that helps with this. They are the basis for transferring customers' emotional world, concerns and brand requirements to the AI. Stefan Rippler, CEO and founder of the Persona Institute, confirms: " data-driven personas not only make chatbots more intelligent, but also more empathetic and user-friendly. They understand their target group better, communicate more naturally and provide more relevant answers, which significantly improves the user experience."

What are data-based bot personas?

In contrast to traditional, fictitious personas, data-based bot personas are based on real customer data. Companies obtain this data from internal sources such as CRM systems, customer surveys, social media analyses and interaction logs. Additional market research data, which supplements existing data, sharpens the persona and helps to respond to customers' needs in even greater detail when communicating with them. Bot personas are digital twins, i.e. digital images of existing customers and, similar to buyer personas, contain information on demographics, character, education level and social background. However, the focus of data collection is primarily on communication and media usage behavior, as well as data that provides information on how problems and challenges are dealt with. Ultimately, a data-based bot persona should represent at least 80 percent of customers. Tip: A data-based buyer persona is usually suitable as a basis for developing a bot persona. Depending on what data your buyer persona is based on and when you developed it, it may make sense to and add further data if necessary.

The most important building blocks of a successful bot persona

A chatbot that speaks empathetically and at eye level is based on a bot persona, ...

• ... that adapts its tonality to the concerns of your customers
• ... whose personality traits harmonize with the character of your clients
• ... that adapts to your target group in its choice of words and sentence structure and at the same time communicates in line with your corporate identity
• ... can derive emotions from speech patterns and react appropriately to them
• ... which adapts to specific use cases and their context without errors.
• ... who has an appropriate reaction style and acts proactively or reactively depending on the context.

The advantages of data-based bot personas

• More individuality in customer service despite - or perhaps because of - artificial intelligence: When fed with the right data, artificial intelligence can do what humans can only do after many years of training or with an excellent knowledge of human nature: namely respond to customers' needs in real time - objectively, empathetically and in line with CI.
• Improved customer satisfaction: Through empathetic and relevant interactions, data-driven trained chatbots increase customer satisfaction and loyalty.
• Efficient customer communication: Data-based bot personas know the problems of existing customers inside out. With their help, frequent customer inquiries can be answered even faster, more precisely and in such a way that consumers derive maximum benefit from them. This not only improves customer satisfaction, but also significantly increases the efficiency of customer service.
• Valuable insights into customer behavior: Data that companies collect during interactions between chatbots and customers helps to further optimize the bot persona and thus the chatbot. In addition, this data provides a valuable basis for decision-making in order to further develop products and services in a customer-centric manner.
• Increased brand perception: A bot that acts in the interests of both the customer and the corporate identity improves the external perception of the brand as well as its reputation.

Successfully implementing bot personas in customer service

Companies can either develop bot personas themselves or with the help of external service providers. The latter is often the faster, more accurate and more cost-effective solution. By way of comparison: while developing a persona yourself, including resources and working time, involves around seven steps and costs around 10,000 euros including market research, service providers such as the Persona Institute can create data-based bot personas for as little as 1095 euros. Developing data-based bot personas yourself, on the other hand, is worthwhile if your company has its own market research department with the appropriate resources. But even in this case, it can help to have the bot persona validated by an independent body in order to close any data gaps.

But regardless of whether you develop the data-driven persona yourself, bring in an external service provider or expand an existing buyer persona into a bot persona: implementing a bot persona is a complex project that cannot be realized overnight. Instead, different stakeholders from customer service, marketing and IT need to work together to train existing or new chatbots with data-based bot personas. In addition to the bot persona, modern AI technologies and natural language processing (NLP) are also required . Alongside the data-based bot persona, they are the basis for making interactions with your customers as natural and efficient as possible. Specifically, bot personas can be integrated into customer service in five steps:

1. collect & analyze data

A persona is always as good as its database. That's why you should collect, collate and analyze as much data as possible. Real customer data from chat histories, support tickets, surveys and your CRM are a solid starting point. Analyzing interactions on social media, forums and other communication platforms also provides information about what really moves your target group. AI-supported analysis tools help to structure communication and identify frequent questions, the preferred tone of voice and recurring problems. What data do you already have and what data do you still need to create a bot persona that truly represents your customers? In short: take a "data inventory" and close data gaps if necessary: through your own surveys or external market research.

2. develop a persona profile

After you have collected, analyzed and presented data in the form of a target group matrix you create a detailed persona profile. The data-based persona profile not only provides information on demographics, but also on the character, highlights and pain points of your target group as well as media usage and communication behavior. Define the persona, especially in terms of language style, tonality, scope of knowledge and interaction behavior. Important: To ensure that your bot can later become an ambassador for your company, make sure that the persona and corporate identity harmonize.

3. train AI models

Use NLP models such as GPT or Gemini to train the bot using the collected data. Techniques such as fine-tuning help to integrate specific industry terms, company data and corporate identity into the communication. For example, an e-commerce company can optimize its chatbot by training the AI with data queries from support chats with customer service so that the AI model better understands product inquiries and returns processes. At the same time, blog posts, white papers and FAQs help the AI model to adopt the corporate identity in the form of word choice and language style.

4. test and optimization phase

Carry out A/B tests with different bot versions and analyze the interaction data. User feedback helps to sustainably optimize the bot persona and thus your chatbot and bring it up to date. Regular validation of your data helps to ensure that it is up to date and to supplement it if necessary.

5. regular maintenance & further development

The same applies to AI as it does to employees. It never stops learning and constantly needs new input. From complex service requests and marketing texts to extensive product databases, companies need to constantly optimize their chatbots.

Bot personas are the key to success

Companies that optimize their chatbots using data-based bot personas contribute to a personalized customer journey and an improved brand experience. The Persona Institute supports you in developing customized bot personas that are based on data and transform chatbots not only into digital assistants, but into brand ambassadors - for intelligent service that really convinces your customers.