Can the 0 code also help you easily build an exclusive intelligent customer service system?

Author of this article：Fiona

In the past, “building an AI customer service system” was a matter of extremely high technical threshold.

It requires programmers, algorithm engineers, and server operation and maintenance. With large investment and long cycles, it is almost impossible for ordinary small and medium-sized enterprises to start.

And today, you can have your own without knowing the code. AI customer servicealready.

With the maturity of 0-code tools and large-model technology, enterprises can quickly deploy an AI customer service system that can truly “understand customers, solve problems, and improve conversions” as long as it is visually configured.

Through the image Mixdesk With such a third-party tool, you don't need to understand any code. With a simple configuration, you can have your own intelligent customer service system that understands your business.，24 hoursHelp you reply to customers, guide conversions, and reduce labor costs.

1. Dismantling of pain points: Why are more and more sellers' customer service "getting more and more tired”?

It's not that many sellers don't want to improve efficiency, but are held back by these real-world problems.：

1. Multi-platform messaging is decentralized and management is chaotic

When the business grows bigger, the customer service messages are scattered in: multiple WhatsApp、Facebook Messenger, Independent stations and mail, etc.

NoUnified background, Customer service needs to constantly switch windows, not only is it easy to miss important customers, but it may also reply to the same question repeatedly, and customer data cannot be centrally managed.

2. High-frequency consultation takes up a lot of time

Most customer inquiries are repetitive questions, such as logistics progress, delivery time, refund process, and product parameter description.…

These problems may occur dozens to hundreds of times a day, occupying a lot of customer service time.

The result is: when real high-value customers appear, the customer service is exhausted and the quality of service is difficult to guarantee.

3. Customer data cannot be precipitated, and conversion and follow-up rely on "memory”

There is no systematic customer management: I don't know which customer has already talked about what, who is a high-intention customer, and which customers should focus on follow-up.

Doing customer service is like "fighting fire”, not "transforming”.

4. Labor costs are constantly increasing, but it is difficult to form a scale effect

In order to ensure that they are online throughout the day, companies must continuously increase the number of customer service.

The problem is：

• MultilingualCustomer service is difficult to recruit and the cost is high
• Training new employees takes time and effort
• Frequent staff turnover and easy loss of customer information

Even if more manpower is invested, efficiency and customer experience may not be improved.

2. Solution: Leverage a professional platform to build an efficient and intelligent customer service system

In actual implementation, to solve the pain points of chaotic multi-platform management, high duplication of consultation, and inability to precipitate customer data faced by independent sellers, the most direct and efficient way is to use professional third-party tools to build a unified customer service platform and turn on AI. Automatic reply。

Judging from the practical experience of many cross-border merchants we have served, like Mixdesk This kind of integrated customer service tool, under the premise of 0 code, can significantly reduce the construction threshold, allowing sellers to achieve professional-level customer service capabilities at a lower cost. Below, from several key dimensions, share the effective practices of the real implementation of the Bank of China.：

1. First solve the problem of "tired of multi-platform switching”: unified messaging entry

Before introducing AI, the first step must be to solve the problem of information dispersion.

When it actually lands, many third-party platforms can aggregate multi-channel customer messages, such as Mixdesk, You can centrally access customer messages from almost the entire network such as independent stations, WhatsApp, Facebook Messenger, etc. into a background for management and reply. Customer service only needs to receive and process all messages on the same interface, and there is no need to switch platforms back and forth. Sometimes customer messages are missed, and multi-person collaboration will not “grab conversations” with each other or miss messages.

In addition, chat logs and customer information can be stored uniformly, and managers can monitor employee responses in real time in the background! Even if the account is blocked, the employee leaves, the equipment is lost, etc., the customer information will not be lost!

2. 0 Code enables AI automatic reply to easily handle high-frequency problems

The focus of introducing AI is not to be a "chat-only robot”, but to be able to truly answer a large number of high-frequency and standardized questions from customers.

This requires that third-party tools must have the ability to customize AI! In the actual configuration, product information, frequently asked questions, FREQUENTLY asked questions, logistics policies, after-sales rules, etc. can be uploaded to the system as basic knowledge, and then automatic reply rules can be set visually and AI services can be enabled.

At the same time, high qualityCustomer service systemUsually hasMultilingualCommunication skills can cover more customer scenarios, effectively reduce the pressure on manpower allocation, and improve service efficiency while significantly reducing overall customer service costs.

Mixdesk AI It can automatically handle high-frequency and repetitive problems, and manual customer service only intervenes when necessary, greatly improving human efficiency!

3. Unify customer management and precipitate private domain assets

A common problem for many teams is that all communication stays in the chat software and is not precipitated into customer data.

Through professional customer service tools, all customer information, chat history, and behavior trajectories can be uniformly managed by the system, and classified through a labeling system, such as high-intent customers, old customers, and complaining customers.

From experience, when the customer service is upgraded from “reply to messages” to “manage customer relationships”, the subsequent secondarymarketingAnd repurchaseConversion efficiencyWill be significantly improved. This is not only an upgrade of the customer service system, but alsoOperational ideasThe upgrade.

4. Data analysis drives optimization to improve overall customer service efficiency

A good AI customer service system must not be "set up at once and leave it alone”, but a continuous optimization process.

In actual operation，Response speed, Session resolution rate, high-frequency consultation type, customer service processing efficiency and other data are all important bases for optimization.

High-quality tools (such as Mixdesk) Will provide a relatively completeData Kanban, Sellers can use this data to continuously adjust their tactics, diversion rules, and operating strategies, so that they are not built at once, but continue to evolve.

3. Summary

I used to think that AI customer service was a “technical activity” and needed to understand code and hire a development team. Now there are no code tools that allow ordinary people to easily build it. The core of 0 code construction is not “the more functions, the better”, but “to meet your own business needs."

For most small and medium-sized businesses，Mixdesk It is the most cost-effective choice: 0 code operation, accurate matching of cross-border scenarios, practical functions without redundancy, can quickly help you build an exclusive AI customer service, liberate customer service energy, and enhance the customer experience. No need to hesitate “do you want to do it” anymore, now follow the template and you can get started in 3 minutes.

Let AI customer service help you catch every consultation and retain every customer.

FAQ

Q1: Without a technical team, is it really possible to build an AI customer service?

A: Absolutely. Now mainstream professional platforms (such as Mixdesk) use a visual 0 code model, so operators can complete the construction without writing code or understanding technology.

Q2: Will the AI customer service reply very rigid?

A: Traditional robots will, but AI customer service based on large-model training has been greatly improved in terms of logic and language naturalness. As long as the knowledge base and vocabulary are properly designed, the experience is very close to the real person.

Q3: Is it suitable for small teams?

A: Very suitable. The small team has limited manpower, and AI is required to undertake a large number of basic consultations. Like Mixdesk, it also offers packages at different stages, so small teams can start at low cost.

Q4: Will it affect customer trust?

A: The key lies in the "design method”. Many brands are first received by AI, and then naturally transition to manual labor, allowing customers to experience “fast response” and "professionalism“, rather than ”machine sense".