How to use generative AI in social media management
For those who are worried about “it takes too much time to manage SNS” or “how to use generative AI on SNS.”
To continue to achieve results on social media, new information and efficient operation are essential. Currently, generative AI technology is the key to this.
In this article, the Japan representative of Agentools, who analyzed 25,000 AI agents, explains about “SNS management AI agents,” which have become synonymous with the use of AI in SNS management.
"Generative AI x SNS" is now spreading as an "SNS management AI agent."
In recent years, the use of social media by companies has increased, and the importance of operational tasks has risen. Tasks have become more complex, including the operation of multiple platforms, the creation of diverse content, and communication with users. With the development of generative AI technology, a new type of tool called “SNS operation x generative AI” = “SNS operation AI agent” is rapidly increasing.
Definition: “An integrated social media management platform powered by AI.”
The SNS Management AI Agent is not simply an automation tool for specific tasks, but a platform that utilizes the advanced capabilities of AI to provide comprehensive support for SNS management operations.
This is a “smart partner” that covers all aspects of SNS management, not only helping you write posts, but also proposing the best posting timing based on data, generating appropriate reply suggestions, automatically creating effectiveness measurement reports, etc. By linking various functions in one place, you can achieve more efficient and advanced SNS management than by combining individual tools.
Four main functions in SNS management
The main functional areas covered by the SNS management AI agent are diverse, but when organized according to the typical business processes of SNS management, they can be broadly categorized into the following four:
Content planning and creation support: We suggest content based on trends and competitive analysis, draft posts tailored to the target audience, and recommend appropriate image and video ideas and hashtags.
Optimizing posts and distribution: Reduces labor costs by adjusting content to suit the characteristics of each SNS platform, proposing and automatically scheduling optimal posting times based on past data analysis, and managing multiple accounts all at once. Promoting and managing engagement: Analyzes the content of comments and direct mail and automatically generates reply suggestions, displays high-priority comments, monitors brand-related mentions, and classifies comments as positive or negative based on sentiment analysis. Analysis and reporting: Reduces the need for data analysis expertise and time by automatically collecting and aggregating various performance data, deeply analyzing the effectiveness of posts, analyzing the strategies of competing accounts, proposing improvements and advising on next steps, and automatically creating reports to support strategic decision-making.
Why is generative AI (SNS management AI agent) attracting attention now?
The reason behind this is that the clear needs of SNS management and the evolution of generative AI technology have matched perfectly. We will dig deeper into how generative AI is specifically bringing about evolution in each process of SNS management and why it is now attracting attention.
By function: Evolution of social media operations enabled by generative AI
The following changes can be seen in each function between traditional SNS management and management using generative AI (especially SNS management AI agent). Let’s compare the before and after.
1. Content Generation:
Before: It took a long time to come up with ideas for posts, and we often ran out of ideas. It took a long time to come up with attractive post text and catchy slogans, and the expressions tended to become monotonous.
After (using generative AI): You can now get a variety of post ideas and text suggestions in a short amount of time. AI suggests new approaches and expressions that resonate with your target audience, improving the quality and variety of your content. Working with image-generating AI also lowers the hurdles of creating creative content.
2. Post Optimization:
Before: The optimal posting time relied heavily on the experience and intuition of the person in charge, and posting to multiple platforms was a time-consuming manual process.
After (using generative AI): AI analyzes and suggests the best posting timing based on data, and automatically schedules posts. This saves you the trouble of having to check by hand, allows you to reach more users, and makes it more efficient to manage multiple accounts at once.
3. engagement:
Before: Responding to comments and DMs took time and manpower, and when we were busy, we would miss some or our replies would be delayed. We had to manually respond to even routine inquiries.
After (using generative AI): Automatic replies to routine questions and automatic generation of reply suggestions improve response speed and prevent opportunity loss. AI-based sentiment analysis quickly identifies high-priority comments, enabling prompt response.
4. Analysis and reporting:
Before: Effectiveness measurement required a lot of manual data collection, which was time-consuming. The more data there was, the more complicated the analysis became. It was difficult to gain deep insights without specialized knowledge, and improvement measures tended to rely on experience.
After (use of generation AI): In addition to automatically aggregating performance data, AI automatically detects trends and areas for improvement from the data and gives suggestions. Automatic generation of standardized reports reduces the time spent creating reports, allowing people to focus on more strategic decision-making and considering the next action.
Utilizing generative AI to manage social media not only improves work efficiency, but also leads to improved content quality, facilitated data infrastructure operations, and standardized operations, which is why it is attracting attention from busy social media managers.
Specific use cases
We will introduce some concrete examples of how generative AI and SNS operation AI agents are actually used in SNS operations. By comparing yourself with the companies in these case studies, you can get an idea of what kind of quality improvements and efficiency improvements can be achieved.
AI system/model development
Custom development is required for special issues or issues that cannot be solved with existing tools. AI Agency can also develop tailor-made solutions, but a “smart agency” will first thoroughly consider existing solutions and only recommend development when truly necessary.
Support for AI human resource development
Case 1
1. Service name: Hootsuite user: RE/MAX (real estate franchise)
2. Benefits of implementation: The headquarters streamlined and standardized content distribution and operational management on behalf of numerous franchisees. The platform, including AI functions, optimized posting creation and timing, improving overall SNS effectiveness.
3. Reason for success: It reduced the time that franchisees spent on social media management, allowing them to focus on their core business of customer service.
Case 2
1. Service name: Sproutsocial customer: Sharpie (marker brand)
2. Benefits: Leveraging the platform’s AI capabilities to perform in-depth social media data analysis, leading to a deeper understanding of the online behavior and needs of specific target audiences (e.g. artists).
3. Reasons for success: Based on a deep understanding of customers, the company developed a content strategy and engagement measures that resonated with the target better, which led to increased brand loyalty.
Case 3
1. Service name: Statusbrew (Statusbrew) User: Evernote (productivity app)
2. Benefits: Streamlined and centralized management of operational workflows and collaboration across multiple social channels and teams. Optimized post management and approval processes with automation tools including AI capabilities.
3. Reasons for success: Collaboration between staff members became smoother, a system for disseminating information quickly and consistently was established, and the quality of brand communication was improved.
Case 4
1. Service name: Buffer (Buffer) user: Momentive (formerly SurveyMonkey)
2. Benefits: Streamlined the process of scheduling, publishing, and measuring social media posts, saving staff time. AI Assistant helps with content creation and post generation.
3. Reasons for success: The company was able to efficiently deploy more social media activities with limited marketing resources, increasing engagement opportunities while reducing operational efforts.
The traps and misunderstandings that many people fall into when using "generative AI x SNS"
Be aware of common pitfalls and misconceptions when using generative AI and social media.
When considering adopting AI tools, it is important to be aware of the following pitfalls and misconceptions:
The pitfalls of "mass-producing low-quality content"
Generative AI can post a large amount of content, but if the quality is not there, it will be a problem. Content that lacks individuality, is superficial, or contains misinformation will lose trust and damage the brand. Rather than mere quantity, it is important to have “quality” that is useful to users and encourages engagement. AI products are only “drafts.” Human fact-checking, brand verification, and the addition of one’s own “individuality” are essential.
Misconception 1: Overconfidence in content creation AI tools It is a misconception to be overconfident that “everything can be left to AI.” AI cannot replace the core tasks that humans should perform, such as strategy planning, target understanding, and brand building. AI is a powerful “assistant.” The key to success is “collaboration,” which combines human strategic thinking with AI’s generative capabilities.
Misconception 2: Neglecting the operation, analysis, and improvement cycle It is a misconception that posting is the end of it. The essence of SNS operation is the DAIA cycle of continuing to measure, analyze, and improve the effectiveness after posting. In many cases, results are not seen due to a lack of this cycle. SNS operation AI agents streamline and enhance this cycle by automatically collecting data, analyzing it, and suggesting improvements. Utilizing analysis is the key to AI success.
Agentools' "Successful Generative AI x SNS" Strategy
In order to maximize the power of AI in SNS management and achieve results, smart “collaboration” with AI is necessary. Our successful strategy is based on the following elements:
"Ideas" and "bouncing ideas" to produce high-quality content (A)
The most important thing in SNS operation is to provide high-quality content that resonates with the target users. By using generative AI as a “partner for ideas” and “someone to bounce ideas off,” innovative ideas and expressions are born. By combining human planning skills with AI’s idea support, high-quality content that attracts users can be realized.
The latest LLM focuses on "ideas and structure," while specialized tools focus on "execution."
The latest LLM excels at the “idea and composition” stage, while SNS management AI agents have strengths in “execution.” The ideal way is to first develop content ideas with LLM, and then use specialized tools to efficiently execute posts, analyze, and improve them.
The core of SNS management: "Management, analysis, and improvement" are all about efficiency with AI
The “main point” of SNS management is how to continuously run the “management, analysis, and improvement” cycle after posting. This part requires specialized knowledge to collect and analyze data, which is a big burden, but a SNS management AI agent automatically collects and analyzes data and suggests areas for improvement. This allows the person in charge to focus on strategic decision-making and creative work. The biggest benefit of introducing an AI agent is that it allows for a smooth operation of the PDCA cycle based on data.
Key points for selecting a "fast, cheap, and effective" SNS management AI agent
We will explain how to choose an AI agent SAAS for SNS operation. Here too, the selection criteria are “fast, cheap, and good.”
1. fast:
Choose a tool that is easy to use. It is recommended to use a tool that is easy to use rather than a tool that is difficult to operate.
2. cheap:
Choose a tool that offers a free trial. Choose one that is within the affordable price range of several thousand to several tens of thousands of yen per month.
3. good:
There are two main types of social media management tools: content creation and social media management analysis. We recommend that you start by choosing management analysis.
We recommend that you choose from the perspective of “fast, cheap, and good.” If you are having trouble choosing, Agentools can help you.
» Find the best AI agent with Agentools
Summary: How to achieve results with social media in the age of generative AI
Generative AI and SNS operation are made possible by the use of the “SNS Operation AI Agent.” This AI Agent SAAS is a powerful tool that will evolve SNS operation, including improving the quality of posts, streamlining operations, and supporting data analysis. To make the most of its power, a “fast, cheap, and efficient” perspective is also useful in terms of operation.
The key to success is "fast, cheap, and efficient" operation
The key to successful SNS management using AI Agent SaaS is “fast, cheap, and good.” The cost of the tool is reasonable, ranging from a few thousand yen to a few tens of thousands of yen per month. In contrast, the labor costs of spending time considering implementation and setting goals are often much more expensive.
That’s why it’s a smart approach to start by “trying something out quickly.” If it’s a proven tool that is already used by many users, you can expect some results. Try out that tool in your actual operations.
If it doesn’t suit you, don’t hesitate to switch to another tool. Finding a tool that fits you in this way and getting used to using it through practice is the shortcut to getting results with SNS management.
AI is beginning to produce concrete results in various business areas. In this article, we will briefly introduce four examples of AI use cases in major functions such as recruitment, accounting/finance, human resources, and sales.
Message from Agentools and author introduction
Agentools is developing a business that recommends AI agents, aiming to create a world where all companies can find and utilize the most suitable AI agents.
There are more than 25,000 AI agents in the world, and choosing the right one is not an easy task. Agentools was created to solve the problem of “Which one should I use?” and “Which one matches my company?”
I hope this article will provide a strong boost to your first step towards using generative AI to manage your social media presence.
Author information
About Agentools
Agentools is a service that recommends AI solutions that contribute to solving customer problems, with the mission of “providing the best AI agents for everyone.” It is jointly operated by Growth LLC and Devnagri AI, a leading Indian AI company (awarded the 2024 Graham Bell Prize and Tie50, among others). It provides reliable information with world-class technical capabilities and meticulous research.
Author: Murata Dai, CEO of Agentools Japan
Representative of Agentools Japan. Involved in the analysis of more than 25,000 AI agents in the world, he is passionate about supporting business transformation through technology. He aims to pursue the potential of AI agents and bring that knowledge back to the Japanese business scene. He hopes that this article will be of help to you.