Introduction
Social media is an essential channel for modern brands to engage audiences and promote their products and services. However, continuously creating captivating, high-performing content can be extremely challenging.
This is where artificial intelligence comes in. The latest AI tools can automate the process of generating viral text, images, and video tailored specifically to perform well on social media.
In this comprehensive guide, we’ll explore the capabilities of AI content generators and how to leverage them to take your social media results to the next level. Let’s get started!
Benefits of AI-Generated Social Media Content
Here are some of the main reasons brands are embracing AI content tools for social media:
Saves Time
AI content generation platforms can create posts and assets hundreds of times faster than humans. This frees up marketing teams for more strategic efforts.
Lowers Costs
Automated solutions are much more affordable than constantly paying to outsource content creation.
Drives Engagement
AI can rapidly generate high volumes of content optimized to perform well and engage followers.
Provides Consistency
AI adheres to brand voice and guidelines more consistently than overworked humans.
Enables Experimentation
It’s easy to produce numerous variations of content to determine what resonates best.
Expands Creative Possibilities
AI copywriting and image generation opens up fresh, innovative content angles.
Allows Personalization
Data can be used to tailor content specifically to individual followers’ interests.
Tracks Performance
Robust analytics show how each piece of AI content performs to further refine efforts.
Current Adoption Trends
Here are some statistics highlighting the growing importance of AI in social media marketing:
- 51% of marketers believe AI assists with content creation for social media (Salesforce)
- 72% of high-performing companies have implemented AI for social media marketing activities (Social Animal)
- 53% of brands that use AI tools saw increased audience engagement on social media (Buffer)
- AI-generated tweets for a national auto brand saw clickthrough rates increase by 450% (Phrasee)
- Microsoft saw 40,000 more people engage daily after using AI to optimize LinkedIn content
- Over 50% of forward-thinking B2C marketing teams plan to leverage AI-generated content within a year (Skyword)
As these statistics demonstrate, AI adoption for social media marketing is rapidly accelerating to boost efficiency and results.
Types of AI Content Generation Tools
There are many emerging AI platforms designed specifically to create high-performing social media content. Here are some leading options:
Text Generation
- Phrasee – Optimizes text for engagement
- Jasper – Creates posts based on performance data
- Copy.ai – Generates clickworthy social copy
Image Generation
- Anthropic – Produces on-brand social images
- Canva – Provides templates and easy design
- Promo – Resizes and enhances images with AI
Video Creation
- Vidyard – Converts text and images into video
- Wibbitz– Automatically produces short videos
- Toonify – Animates images into cartoon videos
Mixed-Media Content
- Kapwing – Enables adding text, music, effects to video
- Snappa – Creates graphics and visuals integrated with text
- Adobe Express – Quickly makes graphics and visual stories
This range of innovative tools opens up tremendous possibilities for viral social content. For an in-depth guide on how to create AI generated content, click here.
Crafting Shareworthy Text With AI
AI-powered platforms can generate engaging, effective text tailored specifically to the unique demands of social media. Here are some techniques and tactics they employ:
Analyze Trending Topics – Identify current trendsing hashtags, news events, and topics to capitalize on what’s hot.
Optimize Tone For Each Platform – Adapt text style for the norms of each social platform. More professional tone for LinkedIn versus informal for Twitter.
Localize References – Craft regionally relevant posts with localized data, names and places.
Promote Calls-To-Action – Insert strategic CTAs to drive clicks, conversions, and engagement.
Use Compelling Headlines – Create intriguing, clickworthy headlines optimized for social media. Research shows most of the impact comes from the headline alone.
Diversify Post Types – Produce a mix of educational content, entertaining content, promotions, etc. to cater to different audience needs.
Leverage Interactive Content – Generate posts that encourage comments and shares like polls, quizzes, fill-in-the-blanks.
Sprinkle In Emojis & Slang – Use emojis, acronyms like LOL and social-friendly terms strategically to stand out.
Follow Trending Meme Formats – Replicate meme concepts and structures adjusted for your brand.
AI takes care of studying data to determine what engages followers and crafting creative that hits the mark.
Creating Viral Images and Videos With AI
Compelling visual content often performs best on social media. AI platforms can automatically generate relevant, brand-aligned images and videos:
Design On-Brand Graphics – Provide the AI with brand assets like logos, fonts, colors and have it design graphics incorporating them.
Resize For Each Platform – Automatically resize and reformat visuals for ideal display on Instagram, Facebook, Twitter, etc.
Add Engagement Elements – Dynamically insert polling widgets, tagging prompts and other interactive elements into visuals.
Modify For Key Events – Customize graphics for holidays, cultural events and relevent moments leveraging built-in templates.
Convert Content Into Short Video – Transform blogs, news and other content into short-form videos optimized for social.
Remix User-Generated Content – Creatively repurpose UGC like customer photos and reviews into new social posts.
Make Memes – Instantly generate branded meme images using trending formats and topics.
Animate Brand Assets – Bring static brand assets like logos and mascots to life as videos or GIFs.
Produce Interactive Videos – Effortlessly add CTAs, graphics, effects and interactive elements to video.
AI empowers even small teams to efficiently generate loads of professional, eye-catching visual content.
Optimizing Timing Based on Analytics
AI tools can determine the ideal timing for social media content based on historical analytics:
Identify Peak Posting Times – Discover when followers are most active on each platform. AI will suggest the best times to post throughout the day and week.
Schedule For Key Events – Recommend timing adjustments around holidays, events, sales, and other moments to maximize exposure.
Spread Out Content – Ensure social content is evenly distributed for consistent engagement versus flooding followers all at once.
Set Reminders To Follow-Up – Prompt to follow up and re-promote evergreen content that performed well periodically.
Adjust For Time Zones – Stagger post times to reach audiences in multiple time zones during their peak hours.
Test Alternative Timing – Experiment with posting at new times and days informed by performance data to find hidden opportunities.
Avoid Overwhelming Followers – Prevent excessive posting frequency that may overwhelm and disengage audiences. Maintain healthy posting cadence.
Optimizing when social content gets published can be the difference between lackluster results and viral success.
Personalizing Content for Followers
AI and ML make it possible to tailor social media content to specific followers by:
Adapting Messaging – Modify post messaging for known follower demographics like age, gender, interests, etc.
Using Historical Data – Reference each follower’s past engagement and content preferences to inform personalization.
Leveraging CRM Data – Incorporate customer relationship data to segment and customize content.
Recognizing Loyal Followers – Spotlight and recognize highly engaged long-term followers to boost satisfaction.
Recommending Relevant Content – Suggest social posts that align with followers’ interests based on profiles.
Segmenting Followers – Categorize audiences into granular segments to assign personalized content.
Sending Targeted Ads – Deliver customized social media ads to hyper-specific persona groups for relevance.
Adding Personal Details – Insert individual follower names, handles, photos and details for more meaningful connections.
Personalized social content tailored to individual followers drives much higher engagement and satisfaction.
Developing a Cohesive Content Strategy
For maximum success, AI software should be part of a holistic social media and content strategy involving:
Document Brand Standards – Detail parameters and guidelines for messaging, visuals and content formats.
Set Content Marketing Goals – Define goals for social media content like brand awareness, conversions, etc. to focus efforts.
Map Content to Buyer’s Journey – Devise content tailored to each stage of the customer journey from discovery to advocacy.
Build & Manage Editorial Calendar– Plan social content themes, topics and formats on a calendar and track progress.
Establish Workflows – Construct efficient processes for requesting, creating, approving, and distributing social content.
Coordinate Campaigns – Align social posts with campaigns happening across other marketing channels.
Have Humans Fine-Tune – Allow time for a human review of AI content before publishing to identify improvements.
Analyze Performance Data – Review engagement analytics, clicks, conversions and KPIs by post to guide ongoing efforts.
Continuously Optimize – Take insights from analytics to provide ongoing feedback for the AI to refine outputs.
AI generation drives volume and personalization, while human guidance focuses quality and relevance.
Tools to Streamline Social Media Management
Robust social media management platforms help streamline AI content processes:
Social Media Scheduling – Schedule and publish content efficiently across platforms with tools like Hootsuite.
Brand Monitoring – Monitor brand mentions and sentiment with software like Sprout Social.
Graphic Design & Video – Create on-brand visual assets with Canva, Adobe and more.
Performance Analytics– Track engagement data and KPIs using Facebook Analytics, Iconosquare etc.
Team Collaboration – Enable smooth team workflow and content sharing with Teamwork or Asana.
Multi-Channel Publishing – Syndicate content across social channels as well as websites and blogs with solutions like MeetEdgar.
CRM Integrations – Sync social analytics with CRM and marketing automation platforms.
Audience Insights – Leverage social listening and analytics tools to understand followers and guide personalization with solutions like BuzzSumo.
Robust tools enable efficiently managing at scale the influx of content AI enables.
Key Metrics for Evaluating Success
Analyze a range of quantitative metrics as well as qualitative indicators to evaluate AI content performance:
Engagement Rate – What % of followers engage through clicks, comments, shares, etc? Look for upward trends.
Reach – How many unique accounts did the content reach? Aim for consistent growth.
Impressions – Total impressions measures potential views. Monitor which content generates the most.
Conversions – Are posts driving traffic, downloads, purchases, signups and other conversions?
Sentiment – Gauge how followers are reacting to content through positive, negative or neutral comments.
Follower Growth – Content that attracts and engages new followers indicates success.
Competitor Benchmarking – Compare engagement and metrics versus competitors.
Social Listening – Monitor follower conversations for happiness with the brand.
Cost Per Click/Conversion – Calculate positive ROI from social content.
Analyze metrics in a dashboard to continually optimize and prove the value of AI content.
Risks to Consider
While the benefits are immense, beware of these potential AI content pitfalls:
- Irrelevant or creepy over-personalization that alienates audiences
- Bias and inaccuracies in data can lead to inappropriate content
- Over-automation can make social channels seem robotic rather than human
- AI-generated text may contain grammar, spelling or syntax errors
- Some AI tools still create low-quality placeholder images rather than realistic visuals
- AI tends to struggle with deeper meaning, nuance, empathy and relationship building
- Automated high volume posting can come across as spammy
- Rogue AI could theoretically go haywire and post profanity or nonsense
Proper human oversight and governance is crucial to address issues like bias and build trust.
Real-World Examples
Let’s look at just a few impactful examples of companies getting results with AI social media content:
- TGI Fridays uses AI to manage localized social content for franchise locations, saving $40,000/month
- Spotify increased social followers 188% YoY with AI-generated video content
- Oreo’s AI-created Facebook posts drove a 225% increase in engagements
- The North Face effectively targeted dormant customers on social via AI-optimized messaging
- Hubspot generated 150,000 views in 72 hours for an AI video announcing new software features
These impressive results prove that AI content can become an invaluable competitive advantage on social channels.
Key Takeaways
Here are the core themes to remember about using AI to generate viral social media content:
- AI platforms create content for social channels hundreds of times faster than humans
- AI allows easy experimentation to determine the highest-performing content formats and styles
- Text, images, video and mixed formats each have strengths to consider
- Conduct ongoing performance analysis to continuously improve the AI
- AI excels at creating high volumes of content, but human guidance is still critical
- AI content works best when part of a holistic strategy encompassing process, technology, data, teams and objectives
- To connect with audiences, balance automation with empathy and personality
- Patience is required – it takes time for AI content to start delivering full results
Adopting these best practices will enable your brand to tap into the immense potential of AI for taking social media results to new heights.
