Unleashing the Power of AI: Three Key Applications of Large-scale Models

Vincent Hsu

Vincent Hsu

Oct 10, 20234 min read

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Unleashing the Power of AI: Three Key Applications of Large-scale Models

In recent years, AI has made significant strides in various fields, with ChatGPT being one of the most notable advancements. However, the full potential of large-scale models is yet to be realized. Why haven't we seen more killer applications in this domain? Rather than fixating on how AI can replace us or how to apply it to our business, it might be more fruitful to adopt a strategic mindset and focus on understanding the underlying technology and observing its applications. By doing so, we can develop unique and profound insights and wait for the right opportunity to arise.

One area where large-scale models can have a high impact is in the realm of intelligent automation. Traditional approaches often involve conducting surveys or consulting firms to gather customer data or insights. However, these methods have their limitations. For instance, online data collection may suffer from a lack of timeliness, while survey questionnaires may raise concerns about the authenticity of responses. So, how can large-scale models help us analyze such situations?

Imagine having a "third person" sitting beside every sales or service representative, silently listening to their conversations with customers. These large-scale models can not only identify problems and propose solutions but also conduct sentiment analysis and root cause analysis. In the end, they can summarize and provide insights into the issues raised by customers and the underlying reasons behind them. This application can be valuable in both online and offline customer service scenarios.

For example, in the offline sales of real estate and automobiles, many salespeople make it a habit to take notes after meeting with customers. They may jot down details such as the customer's appearance, clothing, and height. This allows them to recognize the customer at their next visit and recall their previous needs, leading to better conversion rates. Furthermore, senior managers who have been detached from frontline operations for an extended period often desire to understand how customer service is provided in the present day. By leveraging large-scale models, and analyzing communication records, AI can help derive a comprehensive customer service SOP (Standard Operating Procedure).

The act of taking notes can be easily facilitated using tools like our product "Customer Intelligence Portrait." After meeting with a customer, sales representatives can use their smartphones to record the conversation, capturing details such as the customer's appearance, requirements, desired products, and expectations regarding our offerings. The AI system then analyzes this data, identifying the key points discussed by the customer. In essence, it provides every salesperson with a mentor, helping them improve their marketing conversion rates and capabilities.

Moreover, large-scale models allow us to explore the service patterns, language techniques, and service logic employed by high-performing sales and service personnel. By analyzing each interaction, managers no longer need to listen to recordings themselves, as the AI can summarize and distill the outcomes for them. For instance, in the real estate industry, we assisted in analyzing the preferred language techniques used by each sales consultant during their interactions with customers. We also examined whether these techniques effectively conveyed the advantages and value propositions of the properties, providing comprehensive analytical data. Armed with this information, sales managers can provide personalized coaching to each consultant.

Additionally, large-scale models can be leveraged for decision-making analysis. In a project we undertook for an automotive client, we used extensive communication data to pose questions to the model, such as: "How are our customers today? Summarize the advantages of today's customers. What questions did the customers raise? What is their intention? What should be my follow-up strategy?" Due to their ability to process vast amounts of real-time information and infer from pre-existing business inputs, large-scale models can provide decision-makers with additional data support. While the model's judgments may not always be completely accurate, they can offer valuable insights to inform more informed decision-making and effective management actions.

To summarize, the three key applications of large-scale models are centered around understanding customers, empowering frontline employees, and enhancing management capabilities. By leveraging AI in these areas, businesses can unlock its true value and drive tangible results.

In conclusion, while we are yet to witness the full potential of large-scale models in AI applications, it is essential to adopt a strategic approach, maintaining a deep understanding of the underlying technology and observing its various applications. Three actionable steps to consider are:

  • 1. Foster a culture of customer-centricity: Implement AI-powered tools to analyze customer interactions, identify pain points, and propose tailored solutions. This approach can significantly enhance customer service and increase conversion rates.
  • 2. Empower frontline employees: Equip sales and service personnel with AI tools that can automatically capture and analyze customer interactions, providing valuable insights and mentorship. This can enhance their effectiveness and drive improved customer satisfaction.
  • 3. Strengthen management capabilities: Leverage large-scale models to analyze frontline performance, identify successful approaches, and provide personalized coaching to employees. This data-driven approach can enhance decision-making and drive overall organizational performance.

By embracing these strategies, businesses can harness the power of large-scale models and achieve meaningful AI-driven transformations. The journey towards realizing the full potential of AI may take time, but with the right mindset and approach, organizations can pave the way for revolutionary applications and advancements.

Resource:

  1. "除了ChatGPT,大模型杀手级应用还没有跑出来的原因是什么?", https://www.8btc.com/article/6826250 (Glasp)
  2. "循环智能:AI大模型高价值应用的四个特征和三大场景", https://mp.weixin.qq.com/s/qxlh55iARjPKlqqj6aGPMQ (Glasp)

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