Working with AI
Humans and AI applications form a very complementary team when it comes to social media marketing. While scientists are working to improve AI’s understanding of language, it is at a disadvantage when it comes to the actual engagement, as humans are still much better at talking to humans than machines are. And humans are at a disadvantage when attempting to sift through massive quantities of data very quickly. In this case, each weakness is the strength of the other. While AI may not perfectly assess the nuance of human communication every time, it can quickly determine whether a tweet was sent from a real person and what tool was used to send it, filtering out noise that adds no value for a human social media team. AI can tell you if a sender is in genuine need of assistance, or responding to your most recent social media promotion. AI can help social teams find the good stuff quickly, so that they can respond to things that are worth their time and ultimately manage the workload.
Companies are already using AI in social media, sometimes in surprising ways. I have detailed the many benefits chatbots have brought as they’ve found their footing in the enterprise. Primarily, chatbots have improved customer service, handling the smaller issues while leaving big customer complaints to customer service reps. AI can get even more granular in identifying potential opportunities for user engagement. A company called Post Intelligence has developed an AI application called PI that tracks social trends along with a given user’s history of recent posts to predict their level of engagement, recommend content and even generate social media posts. Pinterest, another social media giant, acquired Kosei, a company that facilitates personalized recommendation modeling, using data to provide product recommendations to Pinterest users that are more likely to be relevant to them. Social media company LinkedIn acquired Bright.com in 2014. Bright uses machine learning to better match employers with job candidates. LinkedIn uses the Bright algorithm to assess hiring patterns, location, work experience and other data to score candidates for employers.
When considering deploying AI to help with social media engagement or other marketing efforts, there are some things to keep in mind. There are many AI solutions, so it is important to select a use case that is vital to the business. If piloting an AI solution, the project should connect to the core of the business to the extent possible, so that results are optimized and the value added is widely understood within the organization. Also remember, as in the LinkedIn and Pinterest examples, don’t overlook AI that may facilitate or grow B2B sales. Also consider the value of the existing structured data that lives in CRM applications. The power of using AI in social media marketing often comes from incorporating unstructured data from social media platforms and structured data that a company already owns to extract actionable intelligence. For social media AI applications to flourish, they must interface, at least to some extent, with a company’s business analytics and business intelligence IT applications.
Social media AI applications can uncover insight and introduce much greater efficiency into a company’s social media operations, provided there is an understanding of what they can and cannot do, and the relative strengths and weaknesses associated with them. If used strategically, incorporating AI into a company’s social media and business intelligence efforts can go a long way to driving customer centricity within the organization.
This article was first published on Futurum Research.