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Recently, relevant researchers predict that by 2020, people will have more conversation time with chat robots than with spouses. It has to be said that companies currently focusing on the development of chat bot applications have found the right direction and they have seen the good prospects of chat bots.
More and more companies are starting to use chat bots, and by 2020, 80% of companies expect to use chat bots in customer service. A suitable chat bot plays a very important role in the company's performance development, but there are many kinds of chat bots on the market, there are many successful, and many are just simple dialogue procedures, far from meeting the needs of consumers. How to judge the performance of chat robots is still a big problem for many companies.
This article lists seven key indicators, which can be used to measure the eligibility of a chat robot used by a company.
1. Revenue growth
The first thing any potential investor wants to know about a company is to look at the company's revenue performance. Similarly, the most important indicator that a chatbot proves its value is to see what economic benefits it brings to the company.
For example, a company can choose to have a human service team and users keep 24 hours a day, or you can choose to have chat bots serve users. Compared with the two, it is obvious that the former has to pay a great price, not only the high labor costs, but also inevitable omissions. The chat bot can stay online for 24 hours, allowing users to consult questions at any time, saving the company a lot of money.
In addition, if the chat robot is satisfactory to the user, it will bring more repeat customers and higher online sales, which will increase revenue.
2. Self-service rate
What the company most wants to see is that users can solve the problems they encounter with the help of chat machines without any human assistance.
If the user's needs are to change the password, the company can measure its performance based on the percentage of the robot's task of completing the "modify password" with the help of the human. If the chatter function is better and better, the better the user experience, the more the user will change the password autonomously. If the robot has a lot of functional flaws, even the patient who has patience will lose the enthusiasm.
Self-service rates are closely related to company costs. In other words, the higher the self-service of the chat bot, the more money the company can save.
3. User satisfaction
To know if a chat robot is good or not, it is the most effective way to ask the user directly.
Through the NPS (Net Recommended Value) method, we are able to determine the user's satisfaction with the chat robot service. For example, after the interaction between the chat bot and the user is over, the user is immediately pushed a question "How likely are you to recommend our chat bot to friends/colleagues in the range of 1-10?" feedback of.
Through the user's feedback data, valid NPS data can be obtained. As a core growth indicator, NPS has given companies a critical foundation in understanding user satisfaction.
Activation rate
Before talking about the activation rate, you need to understand the AARRR model (Acquisition - User Acquisition, Activation - Retention - User Retention, Revenue - Revenue, Refer - Self Propagation) and its importance in measuring the success of the company's business.
The activation rate of a chat bot refers to the number of times the user responds to the initial information of the chat bot with a question or answer related to your business goal, and the percentage of the total number of times the bot sends the initial message to the user.
For example, this has a chat bot designed to help users get weather information from a certain location. When the user receives a message from the robot indicating that it will provide help, the user can enter the weather information that they want to know about the location. The location of the input" is equivalent to allowing the robot to help, which is a user activation.
If the chat bot first sent a message to people, people didn't respond. If this happens for a long time, it will lead to a low activation rate, which may indicate that the robot's performance is not good enough, and the robot developer can adjust it accordingly.
Five. Chaos trigger
As we all know, even the chat robot with the most powerful natural language processing ability is not omnipotent, and it can't fully understand all the information that the user puts forward.
These difficulties in understanding can help us understand where the chat bot still needs improvement. But keep in mind that we can trigger the robot's unique response type through three different triggers to avoid the chatbots being helpless when it encounters difficulties.
First, if the chat bot can't understand a paragraph, just need one sentence: "Sorry, I don't understand what you just said, can you ask again in another way?" is enough.
Second, if the user sends messages that are not within the answering range of the chat bot multiple times, then you can program the chat bot to pass a message about the specific function description to the user, clearly telling the user what the chat bot is.
Third, if the chat bot encounters information that is not understood after the user interacts, the user can be contacted by the manual customer service to solve the problem.
Through the above chaotic triggering methods, you can understand what the chat robot interacts with the user every time, and then can solve the same difficulties.
Reservation rate
Similar to the AARRR model, the retention rate is the percentage of users who retain content interacting with the chat bot over a certain period of time.
The length of this time period is not fixed, but varies according to the function of the chat bot. For example, if a chat bot is responsible for providing fitness-related content consultation, then the user may interact with it every day; if it is responsible for providing weekly news coverage, the user may interact with it once a week.
7. Intelligence and machine learning rate
To know how smart your chat bot is, you can measure the accuracy of the chat bot's understanding of the problem after the user asks a few questions.
In addition to understanding, the ability of chat robots to learn is also important.
In the above, we mentioned the self-service rate. By analyzing the data of user self-service, we can find out which functions of the chat robot need to be improved. The chat robot with self-learning function can self-improve in the field that needs improvement.
summary:
Modern people are increasingly demanding chat bots. Consumers need simple and effective user services, but not every chat bot can easily achieve this goal. In this increasingly competitive market, the seven key metrics presented in this article can help you improve your chat bots and take them a step further.