Hello, I am Kakeya, the representative of Scuti.
Our company provides services such as offshore development and lab-type development in Vietnam, with a focus on generative AI, as well as consulting for generative AI. Lately, we have been fortunate to receive many requests for system development integrated with generative AI.
The marketing industry is evolving daily, and the use of generative AI is rapidly expanding. If you are looking to improve the efficiency of your work, generative AI holds great potential.
Handling vast amounts of data, the question becomes how to implement more effective strategies. Generative AI offers a powerful solution to this challenge. However, when introducing it, the question arises as to how to proceed and what aspects to prioritize.
In this article, we will introduce specific methods for improving marketing efficiency using generative AI, along with practical examples.
The Innovation Generative AI Brings to Marketing
Achieving Marketing Efficiency with Generative AI
Generative AI automates marketing tasks that traditionally required time and effort, significantly improving efficiency. For example, generative AI can automatically create personalized ad copy or email content tailored to specific customer segments. It analyzes vast amounts of customer data and automatically generates the most suitable messages for each individual customer.
Furthermore, based on the browsing history of website visitors, it can predict products of high interest in real-time and display the most appropriate recommendations. In this way, generative AI maximizes marketers’ creativity and supports the execution of more effective marketing strategies.
Use Cases of Generative AI to Enhance Customer Experience
- Chatbots that Facilitate Smooth Communication with Customers
Generative AI-powered chatbots can answer customer inquiries naturally and provide information about products. This allows customers to receive necessary support 24 hours a day, leading to improved customer satisfaction. - Personalized Content that Offers the Best Content for Each Customer
Generative AI can automatically generate content tailored to each customer’s interests based on data such as past purchase history and website browsing behavior. This increases opportunities for customers to encounter valuable information, thereby enhancing engagement with the company.
The Three Stages of Introducing Generative AI
1. Introduction into Existing Operations
First, the aim is to improve the efficiency of existing marketing operations by utilizing generative AI tools. For instance, tasks such as simple copywriting, image creation, and conducting A/B tests can quickly benefit from the implementation of generative AI, allowing the immediate realization of its effects. This reduces the time and resources spent on routine tasks, creating an environment where employees can focus on more value-added tasks. Specifically, it enables a greater focus on more complex data analysis and the formulation of long-term marketing strategies, ultimately leading to an increase in overall team productivity.
Moreover, by utilizing generative AI tools, not only will work processes become more efficient, but the opportunity to generate new ideas and creative concepts will also increase, resulting in further improvements in marketing outcomes.
2. Differentiation through Customization
Differentiation through customization is the next step in effectively utilizing generative AI tools. Once familiar with the basic use of generative AI tools, the next stage is to customize them using your company’s unique data, allowing for more precise marketing activities.
Specifically, by training AI on your brand guidelines, past marketing campaign performance data, and customer behavior data, you can obtain outputs optimized for your business needs and customer characteristics. This type of customization enables the creation of unique content and strategies that differentiate your company from competitors, allowing for more personalized marketing that better aligns with your target audience.
As a result, customer engagement is strengthened, leading to increased brand loyalty and revenue growth. The use of customized generative AI becomes not only a tool for efficiency but also a crucial means of enhancing your company’s unique value.
3. The Transformation of Marketing Operations through Generative AI
The transformation of marketing operations through generative AI is a crucial long-term initiative. Ultimately, it requires integrating generative AI into all marketing operations and establishing new approaches that are not bound by traditional methods. Generative AI is more than just a tool; it has the potential to revolutionize and streamline every process of marketing—from data analysis to customer segmentation, content creation, and even campaign performance measurement. This enables marketers to instantly analyze vast amounts of data, allowing for more precise and accurate targeting. In content creation, it allows for the rapid generation of optimal creatives tailored to the target audience.
Furthermore, in campaign performance measurement, real-time data acquisition and immediate result analysis enable faster and more flexible decision-making. The use of AI in this way significantly enhances marketing efficiency, allowing for performance levels that were previously unattainable with traditional methods. By fully embracing generative AI, companies can strengthen their competitiveness and establish more data-driven, effective marketing strategies.
Successful Case Studies of Marketing Using Generative AI
Improvement in Customer Targeting Accuracy
In the case of a retail company that successfully improved customer targeting accuracy using generative AI, the precision of targeting was significantly enhanced. This company built a system that utilized generative AI to learn from a wide range of data, including purchase history, website browsing history, and demographic data, to deliver optimized ads to each customer segment. By using this data, generative AI gained a deeper understanding of each customer’s behavior and preferences, allowing it to deliver highly relevant ads at the right time.
As a result, the return on ad spend (ROAS) improved significantly, unnecessary ad distribution was reduced, and more efficient marketing activities were achieved. This approach allowed the company to pinpoint its target customers more precisely, greatly contributing to increased sales. Advanced targeting using generative AI captures customer needs that were previously overlooked by traditional approaches, providing companies with a powerful competitive advantage.
Personalized Content Marketing
A travel company implemented personalized content marketing by utilizing generative AI to propose optimal travel plans for each customer. Based on customer data, such as past travel history and interests, the generative AI automatically created travel plans and sent them to customers via email. As a result, the number of inquiries and booking rates increased significantly, contributing to enhanced customer satisfaction.
Key Considerations When Introducing Generative AI
The Importance of Data Accuracy
To improve the accuracy of generative AI, the quality of the data used for learning is crucial. Whether generative AI can produce accurate results largely depends on the precision and comprehensiveness of the data behind it.
If the training data is accurate and comprehensive, generative AI can generate more reliable results. However, if the quality of the data is poor, the results produced by the AI are likely to include errors or inaccurate information. Therefore, ensuring the precision and reliability of data is essential when operating generative AI. Overlooking this point may lead to the AI not performing as expected and producing incorrect results or decisions, which makes careful data selection and management crucial.
Ethical Issues
When utilizing generative AI, careful consideration of ethical issues is essential. For example, it is never acceptable to use generative AI to create discriminatory content or to collect data that invades personal privacy. Since AI learns from vast amounts of data, there is a risk that biases or inappropriate information contained in the data could be reflected in the generated results. To avoid such problems, strict monitoring of both the data used by AI and the entire learning process is required.
Moreover, in marketing or content creation using generative AI, it is crucial to always check from an ethical perspective and ensure compliance with legal regulations and industry guidelines. For instance, intentional checks are necessary to ensure that AI-generated content does not harm specific individuals or groups. As AI technology evolves, so does social responsibility, making it fundamental to use generative AI in an ethically sound manner, which in turn supports trustworthy corporate activities.
Conclusion
Generative AI not only streamlines marketing tasks but also holds the potential to create entirely new marketing approaches. By effectively utilizing generative AI, companies can provide better services and products to customers, enhancing their competitiveness. Generative AI will undoubtedly become a powerful tool for marketers.