The Potential of AI Large Models in High-Value Applications

The Potential of AI Large Models in High-Value Applications

In recent years, there has been a lot of excitement around AI large models, with ChatGPT being one of the most prominent examples. However, despite the hype, killer applications for these models have yet to emerge. Why is that? Perhaps instead of focusing on how AI can replace us or how it can be applied to our businesses, the better mindset is to strategically wait and tactically observe. By maintaining a deep understanding and observation of the underlying technology and its applications, we can better position ourselves for success when the time is right.

One of the key challenges in leveraging AI large models is finding the right use cases and connecting them to our specific needs. Traditionally, businesses would rely on methods such as online sales analysis or consulting firms conducting surveys. However, these approaches have their limitations. For example, online analysis may suffer from low timeliness if the data is not collected in real-time. Surveys also raise questions about the authenticity of the responses. So how can AI large models help us analyze these issues?

Imagine having a "third person" sitting beside every salesperson or service representative, silently listening to their conversations with customers. This "third person" is the AI large model, capable of identifying problems, refining solutions, conducting sentiment analysis, and root cause analysis. It can summarize and provide insights on customer concerns and reasons behind them. This capability can be valuable in both online and offline customer service scenarios. For instance, in offline sales settings such as real estate and automotive sales, salespeople often take notes about customers' preferences and requirements to better serve them in the future. With AI large models, these notes can be analyzed to create comprehensive customer service standard operating procedures (SOPs).

To facilitate the note-taking process, tools like "Customer Insight Portraits" can be used. After meeting with a customer, salespeople can use their mobile phones to record a conversation, mentioning details like the customer's appearance, needs, preferred products, and expectations. The AI system can then analyze and record the key points from the conversation. This essentially provides every salesperson with a personal mentor, helping them improve their marketing conversion efficiency and skills.

Furthermore, AI large models can provide insights into the service patterns and strategies of high-performing sales and service personnel. By analyzing the entire communication process, managers no longer need to listen to individual recordings, which can be time-consuming. Instead, the AI model can summarize and extract the essential information, providing managers with the final results. For example, in the real estate industry, we helped analyze the preferred sales scripts used by each consultant and assessed whether these scripts effectively conveyed the unique advantages and value propositions of the properties. This data enables managers to provide personalized coaching to each consultant.

Moreover, AI large models can be used for decision-making analysis. In the automotive industry, we developed a product that uses extensive communication analysis to provide answers to specific questions, such as summarizing the day's interactions, identifying the strengths of potential customers, listing the questions raised by customers, assessing their intentions, and suggesting follow-up strategies. By leveraging a broader and real-time information pool, the AI model combines this data with predefined business inputs to make judgments. While these judgments may not always be perfectly accurate, they can provide decision-makers with additional data support. Having access to more authentic data samples can lead to more accurate decisions and effective management actions.

In summary, there are three primary scenarios where AI large models can create value for businesses: understanding customers, empowering frontline employees, and enhancing management capabilities. By leveraging these models strategically and tactically, businesses can unlock the potential of AI and drive meaningful outcomes.

To effectively leverage AI large models, here are three actionable pieces of advice:

• 1. Identify suitable use cases: Analyze your business processes and customer interactions to identify areas where AI large models can provide valuable insights and improve efficiency.

• 2. Invest in data collection and analysis tools: Implement tools that enable seamless data collection and analysis, such as mobile applications that facilitate note-taking and conversation recording.

• 3. Continuously refine and optimize: Regularly assess the performance and impact of AI large models in your organization. Adapt and refine your strategies based on the insights provided by the models to maximize their effectiveness.

By following these advice, businesses can harness the power of AI large models and drive significant improvements in customer service, sales conversion rates, and overall decision-making processes. With the right approach and mindset, AI large models can unlock new possibilities and transform industries in ways we have yet to imagine.