Artificial intelligence (AI) is significantly reshaping social media marketing.
Where brands once had to rely on guessing what content and messages would resonate with audiences, AI now enables data-driven personalization, automation, and experimentation. .
The results are evident through increased engagement, reduced costs, and streamlined operations.
In this article, we explore five major applications of AI in social media marketing and how brands large and small are seeing tangible improvements by implementing AI.
AI tools are revolutionizing social media marketing, allowing marketers to analyze data and gain insights into consumer behavior and preferences. Speed up creative development and ensure targeted messages optimally reach the right audience.
Let's take Coca-Cola as an example. By combining storytelling and AI, we were able to create this visually pleasing campaign that engages the senses of consumers.
1. Content personalization: At the heart of AI-driven social media
AI algorithms can sift through user data such as past interactions, likes, shares, and comments, allowing you to customize content that resonates with your audience and increase user engagement.
For example, imagine an e-commerce company uses AI to analyze user interactions. AI systems can identify patterns, such as preferring yoga over high-intensity training.
By leveraging this knowledge, brands can personalize their content by focusing on yoga-related products and tips to resonate with their target audience.
One case study that illustrates this was about a large UK-based “sale of the day” e-commerce company called Wowcher. They leveraged AI to create engaging and personalized ad copy.
Using AI copywriting tools, the brand honed its Facebook ads. For example, if you often click on his Facebook ads for holiday sales, the AI will detect this pattern and show you deals tailored to your interests. In addition to improving relevance scores, the brand saw a 31% reduction in cost per lead.
2. Chatbots improve customer experience
AI and chatbots are significantly improving customer service by providing 24/7 availability, instant responses, and the ability to handle high volume queries, significantly improving the customer experience.
Deliver personalized interactions through data analysis and ensure information consistency and accuracy. These technologies are particularly good at automating routine tasks such as scheduling appointments and basic inquiries, and even providing recommendations for appropriate products.
One example is makeup brand Sephora, which leverages AI to improve the customer experience. In research, the brand found that users were overwhelmed by the sheer number of products available.
In response to the survey results, Sephora introduced engaging quizzes using chatbots to help customers with their shopping journeys. These chatbots provide customized advice and recommendations based on individual responses.
AI can more accurately segment your audience based on demographics, interests, behaviors, and other psychographic factors. This allows for more precise targeting of ads.
I recently spoke with the Care + Giving brand about how they are leveraging AI in their marketing efforts.
They use Instagram for segmentation and prefer to promote their content over users they have previously interacted with or liked. This saves time and is effective in reaching niche audiences.
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4. Data integration and management: A/B split testing + AI
AI streamlines the process of creating, deploying, optimizing, and analyzing A/B tests, helping organizations achieve their goals faster and more efficiently.
Twilio Segment and Evolv AI collect and manage data from multiple sources, including social media platforms. AI can be used to analyze this data and identify patterns and insights that can inform your A/B testing strategy.
Experiences can be refined in real-time and targeted to different audiences and segments across multiple platforms. Unlike traditional A/B testing, AI makes changes to ongoing experiments on the fly. Eliminate underperforming elements and seamlessly integrate new variants without restarting experiments.
For example, if a particularly effective combination increases orders but reduces the number of items per order, the AI can introduce a variant that increases the number of items in the cart without setting up another test.
Traditional A/B testing is time-consuming and requires multiple steps from ideation to execution to analysis. AI streamlines this process by identifying effective strategies, suggesting optimal user experience actions, and quickly adding new variants to your tests.
5. Visual content development
I was recently experimenting with AI on existing photos. Using his Remini, an AI photo his enhancer, he was able to clean up the old slides that his father created from his 50s to his 60s. This can easily be done in Adobe Lightroom, but I don't have access to that tool.
Generative AI tools like Midjourney, DALL-E, and Runway help marketers create personalized images for targeted marketing campaigns.
By analyzing customer data, AI can suggest changes to images and generate images tailored to the preferences, past behavior, and demographics of specific customer segments to increase engagement and conversion rates. I can.
You can also generate your own images and graphics based on text descriptions. This allows you to quickly create customized visuals for your campaigns, social media posts, or advertisements without requiring extensive graphic design resources.
Understanding these real-world applications of AI can improve your social media efforts.
The opinions expressed in this article are those of the guest author and not necessarily those of Search Engine Land. Staff authors are listed here.
