Some of the most exciting applications of Artificial Intelligence (AI) live in the marketing and advertising arena, and we’ve only hit the tip of the iceberg. Social media, with its wealth of data and proven ad ecosystems, is a perfect fit for AI application.
Before we dive into the areas where AI will have a greater impact in the near future, here are a couple of classifications:
- Artificial Intelligence: First coined in 1956 by John McCarthy, AI involves machines that can perform tasks that are characteristic of human intelligence. Planning, understanding language, recognizing objects and sounds, learning, and problem solving all fall under this banner.
- Machine Learning: The application of AI that gives machines and algorithms the ability to learn.
Below are five areas where AI impacts social media and advertising:
One element of targeting that is still left relatively untapped is object recognition. AI will be the driving force that exposes this massive targeting opportunity. While facial recognition has become mainstream, object recognition is still finding its footing. In 2016, Snapchat filed paperwork to secure a patent for object recognition. Today, Snapchat is recognizing food, pets and more.
Here’s a simple example of how this technology works:
- A user decides to snap a selfie with a coffee cup
- Then the user looks for an appropriate filter
- After swiping through various filters, Snapchat recognizes the coffee and serves up a compelling filter from a coffee brand
- Then the user snaps her friends with the branded filter
- Finally, the user’s friends start using the filter themselves
Object Recognition, in this hypothetical situation, has driven an authentic branded experience for the user and her followers. Object Recognition becomes even more exciting when the sheer volume of images that exist on social media is added. Imagine this— after analyzing a user’s image inventory, object recognition technology could calculate their individual fashion style. This style feeds into their overall profile which brands can tap into to provide personalized ad messaging. The potential upside in using this technology to help brands better target consumers is massive.
Over 2 billion messages are sent between people and businesses each month on Facebook’s Messenger app. However, being personal may not be scalable for some large brands on social. When a company receives thousands of messages per day, the ability to authentically respond becomes expensive. Chatbots are able to supplement customer service efforts making response efforts manageable. Many complaints on social media are redundant. AI powered Chatbots are perfect for this role, allowing humans to focus on more complex inquiries.
Creative uses for Chatbots are also on the rise. Chatbots are even starting to enhance in-store experiences. While at the grocery store, people can interact with a Chatbot to get a recipe based on the contents of their shopping carts. Chatbots will continue to be a driving force for bespoke branded experiences.
As Machine Learning evolves, its predictive ability will sharpen, making high-risk high-reward marketing actions more palatable. Now, insert the highly popular, yet famously unpredictable area of Influencer Marketing.
In 2017, 89% of marketers found Influencer Marketing to be effective. However, the challenge of finding the perfect influencer, along with predicting an ROI, leaves many brands cautious. AI takes a lot of the risk, time, and mystery behind influencer marketing out of the equation. AI is able to sift through influencer content and audience engagement levels, match budget and audience, and produce a go-to-market strategy with the best likelihood of an ROI— taking the guesswork out of a highly subjective process.
Game-changing insights don’t come knocking on the front door. Marketers need to know what to look for before arduously mining insights across billions of unique customer journeys. With the ability to sift through larger and more complex data sets, previously unrealized opportunities are uncovered. As a result, Marketers can start leveraging these insights instead of hammering away at the underlying data. Facebook recognizes this opportunity with the launch of Automated Insights.
For example, if there are hidden patterns in social and digital behavior that make customers high-risk to churn, AI can discover them. Once marketers can recognize consumers that are likely to lapse, it may be possible to prevent the lapse from happening.
Social Optimization Tools
On Facebook, big brands come with big budgets and even bigger expectations, all while operating in an extraordinarily competitive ad auction. This means smart optimizations are critically important.
To help aid advertisers quest for maximum efficiency, Facebook recently rolled out a tool called Budget Optimizer. Previously, Facebook optimized ad creative within ad sets (audiences)— the top performing creative naturally would get the lion’s share of impressions. Now with Budget Optimizer in play, Facebook can optimize budget between ad sets – assigning budget to audiences based on real time performance. There are many test-and-learn opportunities for advertisers with these new automated optimization levers.
The future looks bright for AI on social media. From better ad optimization, to new audience opportunities, AI will continue to transform social advertising for the better.