How AI Can Be Used for Social Media Marketing
It happened in seemingly the blink of an eye. One moment, social media was the place to post pictures of your cat or that burger you ate on the weekend. The next, it had become the world's third-largest advertising channel, ahead of print media and trailing only paid search and television.
Social media advertising will grow 17 percent in 2020, and 13 percent in 2021, according to Zenith Media's Advertising Expenditure Forecasts. As this channel matures, marketers will increasingly look to artificial intelligence and machine learning to give them an edge over competitors and target customers with greater precision. AI-driven tools can do things the old marketing analytics tools can't do — like make sense of how those growing number of social media posts are structured.
The Challenges of Using AI With Unstructured Data
The millions of terabytes of data floating around the internet can be divided into three categories: structured, unstructured, and semi-structured. Structured data is data that can be easily sorted into relational databases comprising columns and rows, like in an Excel spreadsheet, and analyzed using Structured Query Language (SQL). Semi-structured data comprises things like email that have some structured data — such as date, sender and recipient addresses, and subject line — and some unstructured, such as the body of an email.
Unstructured data is the exact opposite of structured data. It does not have a recognizable structure and cannot easily be sorted into columns and rows. This makes it incredibly difficult to run data analytics, which would be fine if not for the fact that 80 percent to 90 percent of the world's online data, including most Facebook and Twitter posts, is unstructured.
Bernard Marr, a best-selling author and futurist who specializes in data analytics, notes that unstructured data can be a treasure trove of marketing intelligence. However, the problem with unstructured data is that it typically contains large blocks of text, making it difficult to develop AI models that can identify patterns. Artificial intelligence is getting better at analyzing and sorting unstructured data, but a significant degree of human involvement is still required.
Using AI in Social Media Marketing
As AI models improve, businesses will be empowered to use insights from unstructured data to make better marketing decisions.
Here are three examples of how your business might use AI in social media marketing analytics and ad campaigns.
1. Segment customers. AI gives you the ability to analyze your social media followers, divide them into segments, and target them with paid social media ads that suit their profile and tastes. AI-driven segmentation removes human bias from the equation, protecting you from making false generalizations about users based on demographics. Best of all, it lets you be as specific as you want, enabling you to target customers based on an infinite number of overlapping characteristics, such as 40-something urban males who have an Android phone.
2. Find the right keywords. Once you have your customer segments in place, it's time to find the keywords, phrases, and content that generate high conversion rates within each segment. You might discover, for instance, that 40-something male Android users are more likely to respond favorably to ads about mobile download speeds than their iPhone owning peers.
3. Find the right timing. Continuing on from our last point, AI tools can help you identify the times of day, week, or year that your target audience is most likely to be engaged. If your audience is spread across multiple time zones, you can segment by geo-location and target each group at peak-engagement times.
AI is evolving as a major disruptive force across all types of industries, empowering businesses to target customers, reduce churn — the failure to retain customers over time — and increase the effectiveness of advertising campaigns. Before making the leap, you should ask if your marketing team is ready to use AI.
To find out if you're ready to use AI in social media, you should begin by assessing how much data you have access to, the quality of that data, and how easily you can access it. After that, find the right tools to help you mine that data for insights that will help boost sales and improve your bottom line.
Keyence has more than 40 years of success using data-guided business practices. To learn more about using AI and data in your marketing, download the Ki digital brochure.
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