Artificial intelligence (AI) is a buzz word that can be confusing and even scary. Some predict AI robots will replace humans, but in this article I will focus on what AI exists now and how it is helping or could be helping your social media strategy. AI empowered social media can assist in many areas such as content generation and optimization, 24/7 engagement, automated bidding and placement of social ads, enhanced audience targeting, automated analytics, personalization, and social listening.
AI and Big Data
Artificial intelligence is simply computer systems performing tasks that normally require human intelligence. In the world of big data AI comes in handy. Big data is the massive amounts of data so large and complex it can’t be processed with traditional data applications. This consists of structured data organized in databases and spreadsheets and unstructured data in free-form text, images and video in documents, articles and social media. IBM reports 2.5 quintillion bytes of data are created per day and over 80% is unstructured with much of that from social media.
An algorithm is a series of steps performed by a set of rules to perform a function. We’re most familiar with algorithms as the rules that decide what appears in social media feeds. We try to determine social network algorithm signals to increase our organic reach. Alternatives include paying for social ad placement or influencer marketing. AI can improve social ad campaigns and improve influencer marketing. AI in influencer marketing can aid in finding and vetting ideal micro-influencers for brands.
Automation is software that does things without human intervention. Examples include Amazon tracking shopping history to suggest similar items to automate cross selling. Automated testing pulls data to generate scheduled reports. Automated reminders help employees and customers through alerts and notifications. Drip marketing automates sending a series of communications on a schedule or by consumer trigger actions. Drip marketing has used email for years but also now uses chatbots in Facebook messenger.
Machine Learning is when computers learn from experience by modifying processes from new input. Machine learning can use algorithms to try random variables learning which work best to achieve a goal such as lowest cost per impression or acquisition. Programmatic advertising uses machine learning and automated bidding and placement for media buying. Deep Learning goes further with data processing on a neural network for faster more complex learning. Pattern recognition is a form of machine learning where a computer can be trained to detect patterns in text or visual data.
Natural Language Processing And Generation
Natural language processing (NLP) finds linguistic patterns to analyze and synthesize speech. This is how Hootsuite Insights determines sentiment of brand social media conversations. It can also help with crisis management. Dataminr uses NLP to monitor real time social conversations for crisis communication and real time marketing. Natural language generation (NLG) takes non-language inputs and generates spoken language. Phrasee uses NLG for AI-powered copywriting creating data-driven, human-sounding brand copy for Facebook and Instagram.
Image recognition or computer vision is software that can recognize people, animals and other objects. Brandwatch has an image detection and analysis tool that finds images containing a brand to report how, when, and where consumers are seeing it. CrowdRiff uses image recognition to discover user generated images (UGC). They combine this with brand owned images and performance data for content optimization. Pinterest has AI powered visual search called Pinterest Lens. Marketers can purchase search ads to appear in that search and use Shop the Look pins.
Predictive and Prescriptive Analytics
Predictive Analytics helps understand future performance based on current and historical data. Prescriptive analytics helps determine the best solution among various choices. Salesforce’s Einstein uses AI for customer and lead predictions and recommendations. Einstein analyzes sentiment and intent to route social conversations to the right person streamlining workflow. IBM’s Watson uses AI for campaign automation and marketing personalization. Virtual Assistants add human interface to software. Watson Assistant replaces tedious queries and spreadsheets with simple questions such as, “How did social media perform this month?”
Chatbots use AI to simulate human conversation through voice commands or text chats. Chatbots can be used for drip marketing automation, lead nurturing, onboarding, renewals, confirmations, and engagement. AI-empowered chatbots can also help lead customers through the sales funnel (AIDA). For awareness bots can initiate conversation at scale communicating one-to-one with 5 or 500 people. At the interest stage bots provide 24/7 engagement at the moment of interest. In the decision stage bots supply information, answer questions and send content. For the action stage smaller purchases can be completed by the bot or hand off more complex ones to a human.
AI-powered support can improve customer service via social media. ManyChat’s Facebook Messenger chatbots give customers convenience and speed. Simple chatbots spot keywords and respond with predetermined answers. AI-powered chatbots use NLP to create conversations like human agents. When problems get too complex chatbots can recognize this and hand off the conversation to a real agent. Some report chatbots could save businesses $11 billion in support costs by 2025.
Social Ad Optimization
Pattern89 uses AI to analyze billions of data points daily to discover what social ad dimensions drive customer behavior. Their AI analyzes every combination of placement, device, interests, age ranges, behaviors, demographics for custom optimization insights. Clinch provides personalized programmatic social media content across the customer journey. AI enables them to generate unlimited personalized ad versions with real-time optimization for text, image and video. Motiva AI works with Oracle’s Elogua marketing platform to scan campaigns and make performance recommendations, optimize time and frequency suggestions, run auto multivariate messaging experiments, and automatically discover new audience segments.
Privacy And Ethics
With the General Data Privacy Regulations (GDPR) in Europe and new U.S. regulations like the California Consumer Privacy Act (CCPA) marketers are concerned about compliance. Charles Taylor argues that AI could help with consumer privacy protection. For example, Anyclip AI identifies video events and actions for contextualized social media ad placement. Using this AI could allow custom targeted messages without accessing third party consumer data. AI could also improve targeting to insure ads don’t appear with objectionable content. AI can also help with issues like cyberbullying. Instagram is using AI to identify negative comments before they’re published asking users, “Are you sure you want to post this?”
For the social media professional AI can help improve your job.
Gartner describes AI as a way to automate manual time-consuming processes to free up time, so marketers can be more strategic and creative. Pattern89 sums up the advantages of AI saying “AI algorithms work quickly and thoroughly, and they understand more data than a human can analyze within a single lifetime.” According to Adobe, the top marketing uses of AI include analysis of data, personalization, optimization and testing, image recognition, automated campaigns, content creation, programmatic advertising, digital asset management, video recognition, creative work, and automated offers. How are you using AI to improve your social media performance?