We’ve seen how the internet dramatically sped up communication and business transactions, and most recently, how smartphones have become the primary means of reaching and communicating with the most desirable consumers. Now, it’s artificial intelligence that will revolutionize marketing.
AI’s rising role in marketing may seem far-fetched, especially when Hollywood has taught us to expect AI to look like The Terminator. Perhaps that’s why it’s so hard to recognize actual AI when we see it. The reality is that AI is already here, and it’s powering many of the products and services that we interact with on a daily basis.
Some agencies and marketers are already embracing AI. They are the early adopters—and they are the ones who are in the best position to benefit from this business revolution. At Sizmek, we have more than a decade of AI experience, so we’ve used our expertise to pinpoint the four main categories of AI that are likely to have the biggest impact on marketing in the next five years.
Predictive analytics combines data science, statistics, and various AI tools to analyze data. Predictive analytics feeds off of enormous datasets—the more data available to analyze, the more accurate the predictions. In fact, datasets will become so large, you’ll need to use AI techniques to even make sense of it all. According to Forrester, AI-powered predictive analytics will “drive the insights revolution,” which will be vital to increasing ROI—for example, mining customer data to find and prioritize new leads or predicting consumer preferences to deliver more satisfying customer experiences.
Natural language processing, also known as NLP, is about teaching machines to understand the way people talk and write. AI-powered NLP can do more than just recognize words or phrases; it can also recognize the tone of a conversation or an article. NLP is visible to most consumers through virtual digital assistants such as Apple’s Siri or Amazon’s Alexa.
Marketers are already leveraging NLP via online chatbots that streamline customer engagement and enhance brand experiences. NLP can also be used to understand when the online conversation about a brand or product is positive—like a rave review, or when it’s negative—like complaints about customer service.
You see recommender systems—also known as recommendation engines—on many of the largest web properties. For instance, every time Amazon suggests a product to buy or Netflix tells you what you might want to watch. AI behind the scenes uses what you’ve bought, watched, or clicked on in the past to figure out what else you might like.
Marketers can use recommender systems to turbocharge dynamic creative ads. By looking at what content a consumer has engaged with in the past, a recommender system will serve up specific ad unit elements based on the predicted likelihood of a click. And this will ultimately increase the odds of a meaningful consumer experience.
Image recognition uses AI both to identify what’s in pictures and to look for visual patterns people can’t detect on their own. For example, many mobile apps include image recognition to help consumers identify products, find similar items, or identify pictures of their friends in online photos.
Imagine being able to find every online photo containing your logo or your flagship product, and analyzing those photos to figure out whether they reveal actionable insights. Where and when does your logo show up most often? Who is most likely to take a picture of your product? In general, are the people who take these photos your best customers or your biggest critics?
Courtesy of https://sizmek.com/blog/ai-academy1/