SHOPING CUSTOMER AI: To build confidence in shop partners

The impact of shop training and AI for 100,000 partners

As a Boutique Customs company, Cinecraft products have been bound to design high-quality solutions associated with our best 7-learning policies: The real, fitting, fascinating, effective, effective, effective, effective, efficient, effective, effective. When a global seller with approximately 6000 stores and 100,000 stores drawn to us to help their sales training, we saw a happy opportunity to meet their needs.

Learning Strategy

The seller used the same sales process for 15 years. The sales process was effective, but unfortunately it was not working properly because it had very many steps that caused confusion. So the merchants allow the sales process into three direct steps. This change eventually leads to an increase in the average price of shopping.

Fulfilling their goal, we commended the consolidated approach to protect the protection of the protective behavior, video-based use, and updated by the AI ​​system offered a speedy response and truth.

Because new sales process is intended to direct friends rather than text, we recommend using a variable, timing. Participants write about their answers to the Customer rather than select More Choice option. The Model to Learn the Customs Language (LLM) trained in the sales process enables the answer to this distribution. Likely as a real training coach, train llm (also called model) allows to provide a specific response based on your answers. This approach helps to build confidence ‘

Store training and AI: How did we do?

There have been many features to take place as we develop AI coach to be recognized by a simulation. In addition to our standard procedure, here are the steps we followed to create an effective, secure solution.

Step 1: Get Client Requirements

This requires a complete analysis of their existing IT infrastructure and their legal and safety requirements.

The client did not have an existing platform for AI but wanted to handle a new AI solution within their existing infrastructure. This need is discussing a strong and flexible platform that cannot cover outside the seams in their current ecosystem while storing full control of the environment.

To meet these requirements, AI platform and all compatible information should be protected to ensure that the client maintains ownership and management of their contact. In addition, we propose to use the center server to ensure the security of data processing and reduce risk. This ensures that the students’ responses and AI’s reply remain safe and confidential.

Step 2: Get the best technology

The next step was to choose the correct technology to combine AI in training the sales process. Like all working solutions to learning, accuracy and response solutions are important. The AI ​​model had to give the right and quick response to social participants to support the powerful and powerful training environment.

To ensure quality standards, we examined many AI models to find out which results are very accurate and quick response times. This solid test process allowed us to choose a well-related model and client needs to work properly.

While the active AI integration can be very expensive, two main objects are high: the amount of data installation in model and number of questions or users enter the service. The navigation of these variables and find a very effective solution, build a detailed matrix. The matrix tested a variety of configurations and the use of situations to determine the appropriate balance of the operation and cost of costs for a particular Customer Application.

The solution we have chosen the restored income without compromising the quality, providing a limited solution that complies with the client budget and operating purposes.

Step 3: Determine the flow of technical activity

The Hardware Seller wanted to use the 360 ​​issue of the story, which required the safety of the students to work with AI by using the Interference Interface. After a comprehensive research and discussion, we use the following work flow:

• Type feedback on storyline – The student looks at the customer video entering the store or asking a question and received their answer to the news study.
• Central server processing – The student’s response is securely sent to a managed server and controlled by the customer to work.
• AI-Platform Processing – Central server sends resistant data to ai platform, producing feedback relating to the student’s response. Sensitive information is kept on a central server and is not transferred to ai platform.
• Central server processing – AI’s response is sent to the center of the center, where it is refinement and the back delivery in the storyline.
• Answer Delivery to Storyline – The student receives a quick and active response from AI Coach directly within the news training module.

This back process took place every learner answers the question, and it takes only seconds to complete!

Step 4: Train a model

We needed a ai model to act as our Hardware retailer seller suitable for the workshop’s coach. This means that we should teach everything about a new client trading process, as well as other expectations of friends, programs, and resources they can use in work. This was a careful process. Instead of developing a custom model, we used a basic model from our AI platform. We have provided a contemporary context of the adaptation of certain retailers. This includes training model to see special words in the industry, common customer conditions, and redailer policies and procedures. This content is defined in the status grid and the full news board such as our normal training program.

Step 5: Check the model

After providing all this information on the model, we had to make sure that it was successfully trained. If ai coach gives answers that were not relevant to the client’s goals, then we were successful! If not, we needed to find a model by providing different information. The test procedure began to be made by users who were familiar with training content but were not able to cooperate. After discussing the model, the simulation is presented as the driver of the selected number of stores to try. They have provided their thoughts on training, compliance, and accuracy of accuracy.

Step 6: Analyze the model based on the answer

The test section has shown areas to improve. For example, we needed to sink model answers to better accompany the vendor communication style and verify the tone and moderate accuracy. After many Itersions and repairs, we have found you in desired function and the learner’s standards.

Store

AI integration of the sale of sale of sale has been proven conversion of this Hardware Vendor around the world. By installing the edge of the edge and sound policies, we create a limited solution that is broken for intended self-esteem, customer development, and submitted by a balanced business results. To find the learning and development experts for the AI, the lesson highlights the importance of considerable use and commitment to high quality quality principles.