AI in social media marketing is inevitable at this point. The volume of social content required from publishers is more than most are capable of creating on a consistent basis. The most reasonable fix is to relieve the pressure on a frustrated staff by handing things off to automation.
Enter: AI. Good automation can be a game changer, and there are a lot of places you can use it effectively.
Why you need AI in social marketing
Can a single human mind organize all this? There’s no way limited human capacity can process this much data. Social media platforms use invisible algorithms built on Artificial Intelligence to keep up.
Two tasks that AI can start taking over for you NOW
1. Schedule your posts efficiently.
Unless you can afford a 24/7 team that never takes a day off (or a constantly rotating pool of social media managers), you must schedule your posts in advance. Instead, you can use AI to make these decisions based on every past interaction you have accumulated. Then, the same AI can implement these decisions or offer suggestions for your human staff whenever there is room for increased efficiency.
2. Track the public’s emotions
The next step if figuring out how to track the effectiveness and how much you can spend. Usually, this is measured by examining conversion and click-through rates. However, not all types of clout can be measured through sales – and never is this as accurate as in the publishing industry.
Emotion AI is a new form of analyzing the reactions and feelings of your readers. It uses AI-powered natural language processing to see what’s on your readers’ minds based on their comments and sharing behavior.
Read the rest of this article here.
Economics: It’ll save you money
Aside from streamlining workflows and giving hyper-personalized customer experiences, AI will significantly cut marketing costs. Don’t believe us? Check out how AI in content marketing is changing the economics of the space — and why that’s a great thing for brands.
The shifting economics of content marketing
AI is making it easier for content marketers to demonstrate their value. Machine learning enables marketers to crank out more high-quality content in less time and on budget. Here are ways it can streamline the process and impact your bottom line.
- Staffing: Don’t worry! Robot overlords aren’t going to take over content marketing jobs. But AI does free up marketers from tasks that can be automated.
- Writing: AI can be used for simple, informational blogs. It’s popular for political races, sports, and breaking news. If you’re in these niches, AI prevents the need to hire more reporters or journalists.
- Strategy and management: It’s difficult for humans to predict how readers will behave with certainty. While nothing is ever certain, AI will take a hard look at your data for actionable improvements and future strategies.
- Tedious tasks: AI automatically does tedious information-gathering for marketers. It also offers suggestions for improvements based on this data. Some AI can even implement changes automatically, saving marketers time and money.
- Audience targeting: AI helps you target your ideal audience of interested and engaged potential buyers, streamlining the lead generation process for more revenue.
Read the rest of this article here.
Make content distribution a no-brainer
Data informed decision-making is a basic tenet of business in today’s world. At some point, though, data paralysis sets in. What data so we need to listen to? How much are we capable of sorting? AI’s ability to process huge amounts of data can help social media teams quickly identify their most valuable content.
Artificial intelligence can:
- Predict trending topics that newsrooms should write about based on social media trends.
- Identify which stories will resonate with audiences based on real-time engagement and content consumption.
- Editorially curate and personalize the website and mobile app experiences based on individual preferences
True Anthem’s AI can predict the performance of a piece of content and then distribute the right content to the right audiences at the right time. The publisher can set rules for post frequency, volume, and reposts.
These rules are refined through testing. Because this is a machine-learning program, the algorithm becomes better at predicting content performance over time. The performance results get fed back into the system, improving the AI’s capability. In short, the more you use it, the better the data gets, and the more successful the program will be.
Read the rest of this article here.
