Social media platforms already use artificial intelligence (AI) to enhance user experience, improve audience engagement, and optimize content delivery. The current phase in the evolution of the social media landscape is generative AI.
Generative AI is artificial intelligence that uses machine learning to generate original content, such as pictures, videos, text, and audio. Users enter a prompt, and the software creates an article or image.
Content creation is vital to the success of any social media strategy. So, the ability to produce a continuous stream of new and relevant content is game-changing for content creators, digital marketers, and social media managers. This technology doesn’t only support creativity and productivity. It also offers a level of content personalization that drives positive business outcomes.
A boom in user-generated content is a good thing. However, generative AI can undermine authenticity, which is vital to building trust with followers.
That said, here’s a guide on how to use generative AI in social media campaigns:
1. Define Clear Goals
Before you leverage generative AI in social media strategies, you must be clear on why you’re using the technology and what you hope to achieve. How else would you know your content strategy is working if you don’t have a goalpost?
Setting goals directs your social media marketing efforts. For example, if your goal is brand awareness, you shouldn’t be marketing to existing customers. Instead, you’ll use AI to target lookalike audiences.
Outlining your objectives also provides meaningful context to metrics and analytics. With these data-driven insights, you can determine whether you are on track and what action (if any), you should take.
For instance, your social media teams should continue using AI voiceovers if there’s increased engagement on your social platform after introducing the audio content.
2. Blend Creativity with Automation
You want to maximize the use of generative AI in social media campaigns, so take advantage of both its creative and practical applications.
On the creative side, content creators can make high-quality content.
The example below highlights the creative application of generative AI.
The creator chronicles a vegetable sci-fi saga using AI-generated visual content and voiceovers.
Another creative application of generative AI is content generation using keyword-based prompts. Below are the results for the prompt ‘content ideas for an anime blog.
The list consists of 15 ideas for long-form content, from reviews to recommendations.
On the practical side, the most notable application of generative AI is workflow automation. AI streamlines the social content creation process, saving you time and money. It manages tedious tasks like scheduling upcoming posts, allowing you to concentrate on strategic work.
You can check out your generative AI software’s website to determine your chosen tool’s specific use cases. Then train your social media team on how to properly and effectively use the tool for these purposes when running social media campaigns.
3. Create Personalized Content
Don’t just use generative AI to create visually appealing content and streamline social media operations. Use it to personalize content as well.
Over 71% of customers expect customized communication from brands. That means sharing the right marketing message with the right person.
Besides, social media platforms like Facebook, Instagram, and LinkedIn use machine learning to predict the value of content to social media users. Machine learning algorithms use a combination of content semantics and user preferences to rank content by relevance and deliver content curated to an individual’s interests. For example, LinkedIn tailors content recommendations based on job titles, skills, and career goals.
What is these social platforms’ goal in presenting the most relevant social media posts to users? Increased engagement and user satisfaction.
So, when using generative AI in social media strategies, make sure you incorporate data that will enable the tool to tailor its output. With Writer, for instance, you can easily specify your target audience. Generative AI can continuously learn from this data, which means the social media content it comes up with can become even more tailored to your target audience over time. As a result, the appropriate AI templates don’t just help you deliver personalized content to target audiences. They increase the likelihood you’ll achieve your marketing and, ultimately, business goals as well.
4. Choose the Right Tools
The result of the growing popularity of generative AI is a multitude of content creation tools.
It can be challenging to know which solution is best for your business. So, here’s what to consider when choosing generative AI solutions.
- Business requirements: The tool you select must have the necessary features to deliver your business needs. For instance, choose solutions with robust analytic features if your goal is improved decision-making.
- Cost-effectiveness: The initial investment and maintenance must fit your budget, and the return on investment should justify the cost. Fortunately, many AI tools offer free and paid versions, depending on your needs.
- Scalability: Generative AI tools must grow with your business. That means adapting to increasing workloads, technological advancements, and future business requirements.
- Integration: Effective AI solutions seamlessly integrate with your existing technology stack, like your customer relationship management (CRM) system and social media channels. Otherwise, you create data silos, decreasing productivity.
- Privacy: Look for tools that comply with data security regulations, such as GDPR. Key security features include user access control and data encryption.
Below are examples of generative AI tools and how you can use them in your social media campaigns:
- Writer: accelerates content production processes.
- ChatGPT: crafts text using natural language processing.
- Dall-E: translates text into images.
- Synthesia: generates videos from text inputs.
- Soundraw: produces unique, royalty-free music.
It’s not just third-party providers that offer generative AI. Social media platforms have AI features, enabling users to create text and images easily. For example, Facebook and Instagram users can generate personalized stickers for their Stories or restyle existing images. You can take advantage of them, too.
5. Input Quality Data
Generative AI uses machine learning models to generate content. These models train on large datasets to discover patterns, understand relationships, and make predictions. Consequently, data quality is paramount to the successful application of the technology.
Poor-quality training data produces low-quality algorithms, resulting in inaccurate, unreliable, and biased AI-generated content. So, be sure you service AI models with good data. You also want to have the fastest web hosting service you can afford. Machine learning is resource-intensive and can slow down other computer operations.
Characteristics of good datasets are:
- High-quantity data – AI algorithms require vast amounts of data to recognize patterns. Insufficient data will result in inaccurate conclusions.
- Representative data – Training data sets must reflect your target market. If the training data doesn’t represent your customer base, it won’t make relevant content, alienating a significant portion of social media audiences.
- Accurate data – Machine learning models don’t distinguish between correct or incorrect information. If your datasets contain errors, the machine learning algorithms will formulate predictions with these, resulting in inaccurate content.
Low-quality data is a problem, costing businesses $15 million yearly in losses. It affects your credibility, and it’s difficult to win back followers once you’ve lost them due to misinformation. It also undermines your ability to deliver personalized social posts. Again, personalization is critical to sustainable growth. It improves social media experiences, increases engagement, and boosts retention.
Despite fears of an AI takeover, generative AI still requires human input to ensure accuracy and authenticity. Mechanisms like human-in-the-loop (HITL) or human-in-command (HIC) provide oversight and prevent undesirable consequences.
Conclusion
Some businesses already realize that integrating generative AI into their social media strategies yields substantial benefits.
However, the technology is still new and can pose problems, such as bias amplification and branding inconsistencies. That said, we shared five tips to help you effectively harness the power of generative AI in social media campaigns. To recap:
- Define your goals to lay the foundation for how you’ll use this technology.
- Blend creativity with automation to get the most out of AI applications.
- Choose the right content creation tools that will help you meet your business goals.
- Input quality data to ensure quality content.
- Create personalized content
The best way to use generative AI is as a collaborative tool and not the sole source of your social media content. The technology is not infallible or a one-stop solution. AI-generated content can sound generic, compromising your brand identity.
So, leverage both unmatched human rationality and generative AI’s efficiency. This way, you can reap the tool’s benefits without damaging your reputation. Good luck!