2025 Updated Guide: How Cross-Border Businesses Can Train Their Own AI Chatbots

AI chatbots are revolutionizing customer interactions by using artificial intelligence to simulate real conversations and enhance customer experience. Early chatbots relied on keyword matching and preset rules, which often resulted in ineffective responses when customer queries didn’t align with predefined keywords. However, advancements in AI, particularly through large language models and natural language processing (NLP), have dramatically improved chatbot capabilities. Today’s AI chatbots can understand user intent, even without exact keyword matches, and provide more accurate, flexible, and context-aware responses.

For cross-border enterprises, an AI chatbot can be configured to improve the efficiency of receiving customers. This article will introduce in detail how to choose tools to create AI chatbots, help cross-border enterprises train their own AI chatbots, and let intelligent chatbots better serve corporate business.

Identify AI chatbot usage needs and assess enterprise capabilities

Identify Business Use Cases

Before implementing an AI chatbot, businesses should clarify its intended role and functionalities. Clearly defining these goals ensures a focused training approach. In the cross-border sector, chatbots typically serve the following roles:

Pre-sales support chatbot: Before customers place an order, they may not be clear about the product price and advantages. The pre-sales support chatbot can provide customers with information such as product price and product features, allowing customers to have a deeper understanding of the products of cross-border enterprises.
Customer Service Chatbot: After a customer places an order, he or she may not be familiar with the product information and operations. At this time, you can train a customer service robot to answer questions that customers have during the use of the product, such as providing product operation guides and sharing product instructional videos with customers to improve the customer experience.
Lead Generation: Obtain information or contact details of potential customers through interactive conversations to support sales teams.

Assessing business capabilities

After confirming the application areas of AI chatbots, companies need to conduct a comprehensive assessment of their own budgets and technical resources. Because the configuration difficulty and functional requirements of different AI tools vary, companies need to confirm the resources they currently have before choosing AI on the market.

(1) Development difficulty: Some AI platforms provide simple templates or drag-and-drop tools that allow users to configure chatbots without programming knowledge, which is suitable for users with limited technical capabilities. For example, Coze and HelpLook both support simple configuration and are suitable for basic customer service. However, AI models like OpenAI Assistants and ChatGPT offer extensive customization but require programming knowledge, making them suitable for businesses with in-house development teams.

(2) Budget and cost: AI chatbot platforms follow different pricing models:

①API Call-Based Billing

Billing by API call count is a common AI service charging model. Service providers charge based on the number of API requests. For example, in a chatbot application, every time a customer sends a message, the AI will process it in the background, which counts as one call. This model is suitable for enterprises to flexibly control costs based on frequency of use while avoiding complex billing rules.

②Token-Based Billing

Token refers to the smallest unit of text, which can be a word or a punctuation mark. For example, the sentence "Hello, this is SaleSmartly." will be broken down into multiple tokens. Therefore, the longer the text you process, the more tokens you will need, and the higher the cost of using the AI. This model is suitable for companies that need to process a large amount of text content, and can accurately charge according to the actual length of the generated text.

Generally speaking, the charging items of many AI platforms are mixed. Before choosing AI tools, enterprises can first take the free trial provided by each AI tool, estimate the frequency and complexity of API calls before actual use, and choose a billing method that suits their own needs.

Choosing a platform to create an AI chatbot

A robot configured by a single AI tool is not enough to generate an enterprise AI chatbot. You need to use some platforms to create an interactive AI chatbot. You need to connect to some platforms that support AI chatbots to realize interactive chats between AI and robots, and then you can integrate AI into the business of the enterprise and configure a robot. The following are some points that cross-border enterprises should pay attention to when choosing a platform:

1. Expandable platform

For cross-border enterprises, they usually operate multiple social media platforms and independent website platforms, so the configured AI chatbot platform needs to be able to cover all relevant platforms to maximize the value of the trained AI.

As an omni-channel private domain communication tool, SaleSmartly supports the integration of multiple platforms, including Livechat, WhatsApp, Facebook Messenger, TikTok, Instagram, Telegram, Line, Email, VKontakte, WeChat, etc., which can meet the needs of cross-border enterprises between different social media platforms and independent sites. Simply integrate all platform accounts into SaleSmartly and connect the trained AI chatbot to the background to achieve unified customer service across platforms.

2. Accessible AI tools

When choosing an AI chatbot platform, you need to consider the types of AI tools it supports to ensure that the platform can meet the specific needs of the enterprise. SaleSmartly supports access to mainstream AI tools on the market, including ChatGPT, OpenAI Assistants, Coze, and HelpLook. These AI tools can basically meet the technical needs and application scenarios of different enterprises.

3. Data Privacy and Compliance

When using AI chatbots, data privacy and security are of utmost importance. Companies do not want chat information with customers to be leaked, which may lead to information security issues. SaleSmartly meets international security standards ISO/IEC 27001, CCRC and other international standards certifications, to protect customer conversations and sensitive business information.

Select AI Chatbot

In order to help cross-border enterprises better choose the AI chatbot they need, the following will introduce the differences between four commonly used AI tools on the market: ChatGPT, OpenAI Assistants, Coze, and HelpLook. These four tools have different advantages and scopes of application, which can meet the needs of most cross-border enterprises.

	ChatGPT	OpenAI Assistants	Coze	HelpLook
Key Features	Natural language processing for conversations and content generation.	OpenAI Assistants is an assistant based on the OpenAI model that provides functions such as conversation and task execution.	Coze is an AI Bot development platform for the international market, using large models such as OpenAI's GPT 3.5/GPT 4 to drive conversations.	HelpLook is a knowledge base tool that supports multiple input formats, such as text, images, audio, and video.
Ease of use	Users can customize the output through prompt engineering, but cannot modify the model weights directly.	It requires a certain level of programming skills, but supports flexible adjustments and is suitable for development teams.	Provides a modular training approach to quickly create robots from predefined templates.	Just upload the document to the backend and AI will automatically crawl it.
Integration	APIs for custom apps; limited native integrations.	It can be embedded into different applications to provide customized assistant services.	Supports access to international social platforms such as Telegram, WhatsApp, etc.	Support cloud synchronization.
cost	GPT-4o : $2.50/million input tokens; $10.00/million output tokens.	Assistants API : $0.03/session.	30 free API calls/month.	80 free AI calls/month; paid upgrades.
applicability	Suitable for simple user interaction and answering, the application scenario of chatbot is relatively single	Suitable for highly specialized chatbots that can handle complex tasks or multilingual scenarios	Companies that need to support multiple languages, cross-border e-commerce, and global customers	Suitable for cross-border enterprises that need to establish multilingual knowledge bases and help centers.

Creating an AI Chatbot

After confirming the purpose of the intelligent chatbot and the creation platform, the next step is to start configuring the cross-border private domain AI chatbot dedicated to the enterprise. The training process of different AI platforms is different, but there are some common ideas and processes that can help cross-border e-commerce companies operate more efficiently when configuring AI chatbots. Next, we will introduce the basic configuration ideas for creating AI chatbots, so that cross-border companies can know the general process before training AI chatbots.

1. Build a knowledge base dedicated to the enterprise

When interacting with AI, such as having a conversation with ChatGPT, AI's answers are usually based on the training data of its general large model, which cannot accurately reflect the specific needs of the enterprise. If you want to train an AI chatbot dedicated to your enterprise, the first step is to upload knowledge about the enterprise to AI and let AI answer customer questions based on the content you upload.

Upload corporate information: Cross-border companies can upload relevant information such as product introductions, terms of service, and customer FAQs to the AI system.
Historical chat records: Upload historical conversation records with customers to help AI better understand customers' questions and needs and improve the accuracy of its responses.
Order information: AI can be used to crawl all orders on the order page. When customers want to know their order information, AI can provide order status information.

This data can be used as a knowledge base, and AI will answer customers' questions based on the information provided by the business. This can prevent AI from making up answers or lacking content in professional fields, allowing AI to answer business questions more accurately and professionally.

2. Set up the conversation flow

After uploading the basic knowledge of the enterprise, AI will have the basic ability to answer questions, but in order to make the interaction with customers smoother and more effective, it is necessary to set up a suitable dialogue flow. Through reasonable dialogue guidance, AI can understand and respond to customer needs more accurately, improve service efficiency and customer experience.

(1) Set up the opening remarks

When configuring the AI chatbot, you need to set an opening statement to let customers know the basic information of the company and guide customers to ask questions to facilitate the operation of the AI chatbot.

For example, you can set the opening remarks to be automatically triggered when the user opens the chat window: [Hello, I am Sale S, the robot of SaleSmartly. Thank you for consulting SaleSmartly. How can I help you? ]

(2) Collect frequently asked questions

Cross-border enterprises often face some repetitive customer questions. For these questions, AI chatbots can improve the response speed by setting quick question buttons. Through these preset buttons, customers can quickly select common questions to ask questions, and AI can respond efficiently based on the preset answers.

For example, you can set up FAQ buttons in the conversation window, such as "Product Price", "Return Policy", and "Usage Scenarios". After the customer clicks the button, AI can automatically answer the customer's questions based on relevant information in the corporate knowledge base, further improving customer experience and accelerating problem solving.

(3) Conduct multiple rounds of dialogue

Considering that customers may continue to ask questions, set up a dialogue flow to let the AI robot guide customers step by step to ask more specific questions, so as to provide customers with more accurate services, such as the following dialogue:

Customer: I need help.
AI Chatbot: Sure! Could you share what you’d like assistance with today?

Customer: I want to return an item.
AI Chatbot: No problem! To help you quickly, may I have your order number?

Customer: 123456.
AI Chatbot: Great—order #123456 is eligible for return. Let’s schedule a pickup. When would be most convenient for you?

Customer: Tomorrow afternoon.
......

When the customer asks questions at the beginning, the questions are broad. Under the gradual guidance of AI, the customer asks specific questions that he wants to know so that AI can mobilize the content of the knowledge base to answer the questions.

When training AI, there are two ways to achieve multi-round dialogue:

Set multiple dialogue nodes: By presetting the branches of questions, enterprises can set multiple dialogue nodes according to customers' common question logic. Customers make choices based on the prompts of the chatbot, and each node has a targeted answer. For example, when a customer asks about returns, the AI will automatically go to the return-related node and provide a solution after collecting the necessary information.

Configure AI big model nodes: The flexibility of big models allows AI chatbots to intelligently select appropriate answers based on customer questions and advanced conversations. Combined with the company's knowledge base, AI can conduct multiple rounds of conversations more naturally, making the entire communication process more professional and personalized.

3. Test and Iterate

Testing AI Chatbots

After training the AI chatbot, you need to test it. You can first use the configured robot in a personal chat to test the accuracy of the answer. During the testing process, companies can focus on the following aspects:

Accuracy: Ensure that the AI gives the correct answer based on the content provided by the knowledge base, rather than the answer crawled from other websites.
Fluency: Whether the AI chatbot’s conversation is natural and whether it can guide customers smoothly.
Diversity handling: Can AI understand different ways of asking the same question from different customers and provide appropriate responses?

Repeated testing and optimization can help improve the overall performance of AI chatbots and ensure that they can provide high-quality services in actual use.

Iterate knowledge base content

The answer to a question given by an enterprise will change with the update of the product, so the content of the knowledge base should be regularly iterated to ensure that the answer of the intelligent chatbot is up-to-date and consistent with the updated content of the enterprise. For example, if the price of an enterprise product is adjusted or a new product is launched, the relevant information should be added to the knowledge base to ensure that the service provided by the AI chatbot is always accurate and effective, avoiding customer confusion or misleading due to outdated information, thereby avoiding potential losses to the enterprise.

The detailed process of training AI on different platforms can be found in the official AI documents provided below. After confirming the needs and selecting the appropriate AI platform, cross-border enterprises can configure it themselves according to the steps in the official documents:

ChatGPT: https://platform.openai.com/docs/introduction

OpenAI Assistants: https://platform.openai.com/docs/introduction

Coze: https://www.coze.com/open/docs/guides/create_conversation

Button: https://www.coze.cn/open/docs/guides/chatflow_quickstart

Helplook: https://help.helplook.com/docs/q6RlEz

4. Deploy AI chatbots to chat software

After the test is passed, the enterprise can deploy the trained AI chatbot to the actual chat software to provide customers with automated consulting services in daily operations. Combined with the SaleSmartly platform selected above, the enterprise can click the link below to see how to configure the AI chatbot to SaleSmartly to achieve intelligent automatic replies:

ChatGPT: How to configure ChatGPT API Key? -SaleSmartly-Help Center-SaleSmartly User Guide

OpenAI Assistants: How to connect to openai Assistants - SaleSmartly - Help Center - SaleSmartly User Guide

Coze: Tutorial on configuring Coze bot

HelpLook: How to get HelpLook Token? - SaleSmartly - Help Center - SaleSmartly User Guide

After connecting the AI chatbot to SaleSmartly and enabling it, you can have the AI chatbot respond to customers’ questions at any time with one click. Let the AI chatbot automatically respond to customers’ inquiries on platforms operated by companies such as WhatsApp, Facebook Messenger, TikTok, Instagram, Telegram, Line, etc.

Frequently asked questions

Do I need a dialogue flow if I already have a knowledge base?

Yes. A knowledge base provides factual answers, while a structured conversation flow guides users through ambiguous inquiries. For instance, if a customer says, "I need help," the chatbot should prompt them to specify their issue rather than relying on the knowledge base alone.