Implementing and training AI
To start using AI, it is necessary to train it and for this the best way is to use ready-made models, loading large volumes of data and testing the accuracy of the responses. However, this requires considerable resources and does not always guarantee a return. A practical alternative is to use tools such as ChatGPT, which, when configured with appropriate prompts, helps in automating processes, identifying customer “pains” and generating valuable insights.
You may ask yourself: "why teach the most intelligent creature on the planet?" It may not seem to make sense, but it does, because ChatGPT uses a huge volume of information. Therefore, it is possible to simply use the right prompt, i.e. to set the pace and format of communication appropriately. This can be done through a simple trial and error method, i.e. by interacting with the neural network for a long time.
The Chatterfy tool, for example, makes it possible to integrate AI into Telegram chats and bots, making it easy to create automated sales funnels and personalized message flows. Essentially, it is a construction platform that offers different types of ready-made prompts and a rather complex backend. What you need to do is draw a flowchart of how the service process will be carried out. This can be compared to a job description given to any manager.
Structuring sales funnels with AI
On average, a classic sales script has a maximum of six elements. It is possible to divide these elements into follow-up questions, but this depends on how faithful to the script you want the AI to be.
Currently, AI cannot calculate the probability of lead conversion, since much of the responsibility lies on the "buying" side (traffic purchase). Looking at global statistics, we can see that even with identical funnels and scripts, audience behavior can vary. However, AI, through internal analytics, can provide some insights:
* At what point, on average, do leads stop responding to messages
* What are the most common questions
* What are the most frequent objections, etc.
Based on this information, a sales manager can adjust scripts to improve the conversion rate.
Challenges and limitations of AI
Although useful, AI is not perfect. Among the limitations is the difficulty in personalizing responses at a human level and understanding emotional nuances. In addition, its accuracy depends on the quality of the instructions provided, requiring attention to the detail of commands and objectives. In more complex dialogues or with images, for example, manual intervention may be necessary. Other limitations include the fact that AI does not generate new “niche” ideas, such as “what is the best campaign to convert?,” based exclusively on the data provided.
AI and human traits
The simplest way to give a neural network a “character” is to have it simulate being someone. That is, in the prompts, you can tell it to act like a stand-up comedian or a salesperson. In previous versions of ChatGPT, this didn’t work well, which OpenAI itself has acknowledged. The new versions understand the instructions well and execute them appropriately.
The AI can be configured to imitate certain human “characteristics.” First, it uses training data that contains examples of texts with typical behavioral and emotional characteristics. Second, it can apply algorithms that analyze the character’s characteristics and adjust the AI’s responses based on them. Finally, user feedback helps to “tune” the AI’s behavior, making it closer to the desired character.
Performance evaluation
One of the biggest advantages of using AI in arbitration is its data analysis capabilities. It can monitor the point at which leads lose interest, identifying recurring questions and main objections. This allows strategic adjustments to service scripts, optimizing the funnel to improve conversion. However, it is important to remember that AI offers analytical support and does not determine sales closures on its own.
Strategies to optimize the use of AI
To make the most of AI's potential, it is essential to define clear objectives. The more detailed the instructions for AI, the better the tool's performance. In practical terms, knowing learning algorithms and neural network structures can facilitate the creation of effective commands.
AI represents a powerful tool for traffic arbitration. The strategic integration of AI allows processes to be optimized and approaches to be personalized, contributing to more efficient service focused on the customer's needs. To continue exploring the topic, we at 1win Partners provide updated content on our networks, including voice chats and discussions on technological trends.
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Source: 1win Partners
