ChatGPT learns enterprise products, service content, and previous plans, processes the input customer needs, and generates customized solutions

Keyword libraries corresponding to this scenario (6):
enterprise product and service content, customer needs and parameters, marketing plan and promotion strategy, data processing and model training, customer satisfaction and marketing efficiency, past marketing plans

Question template:
scene + product + question

Template 1:

Scenario: The TVs produced by a home appliance company occupy a certain share in the market, but recently received feedback from some customers that there are problems with product quality, such as bright spots or dark corners on the screen. To maintain customer satisfaction and market share, companies need to address this issue.

Product: A 55-inch OLED TV produced by a home appliance company.

Question: How to solve the product quality problems reported by customers, such as problems such as bright spots or dark corners on the screen?

Template 2:

Scenario: The machinery and equipment produced by a manufacturing company are very popular in the market, but customers report that the production efficiency is low and the cost is high. To improve customer satisfaction and market competitiveness, companies need to increase production efficiency and reduce costs.

Product: Automatic machinery and equipment produced by a manufacturing company.

Question: How to improve customer productivity and reduce costs?

Template 3:

Scenario: A software service company provides customized service and support solutions for enterprise-level customers to meet the different needs of customers. A customer requires a specific service and support solution, but the company's existing solutions do not meet the customer's needs. To meet customer needs and maintain customer satisfaction, companies need to provide customized service and support solutions.
Product: Enterprise-level customized service and support solutions provided by a software service company.

Question: How to provide customized service and support solutions to meet the specific needs of customers?

The first step, ChatGPT model training, build your own solution library

Collect information on the company's products, service content and previous plans, including product and service introductions, features and advantages, as well as past marketing plans, successful cases and customer feedback. It can be collected from internal databases, documents and materials of the enterprise, and can also be obtained from external markets and competition conditions. Feed to ChatGPT, so that ChatGPT can learn and master the characteristics and advantages of enterprise products, services and marketing solutions, as well as customer needs and parameters.

The second step is to collect and analyze customer needs, enumerate customer needs and parameters

After the model training is completed, the customer's needs and parameters can be input into ChatGPT, allowing it to customize and generate solutions according to the customer's needs and parameters. These requirements and parameters can include information on the client's industry, size, needs, and budget.

The third step is to generate a customized solution and fine-tune the details according to the needs

Based on the trained ChatGPT model, a solution is generated according to the customer's needs and parameters. Solutions can include product and service introductions, recommendations, and pricing, as well as marketing and promotional strategies. The proposal needs to take into account the specific needs and budget of the client so that the client can accept the solution satisfactorily.


Example:

Question input:
1. Please understand the following vocabulary clearly:
• Solution
• Introduction of products and services
• Product recommendation and product pricing
• Marketing plan
• Promotion strategy
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Question input 2. Please learn the following for a complete customer solution example

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Question input 3. The company plans to launch a new product XXX, please output a customized solution based on the existing solution library

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Origin blog.csdn.net/m0_46653805/article/details/130353465