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About Our Guest
Dan Faggella - CEO and Founder at Emerj
Dan is a speaker, writer, and entrepreneur who is focused on the creation and expansion of sentience and intelligence in technology.
Dan has written for TechCrunch, Boston Business Journal, VentureBeat, Xconomy, and VICE MotherBoard (among others), and has spoken at United Nations, World Bank, TEDx, Stanford, Columbia (Paris campus), MIT, and Harvard.
AI week HIGHLIGHTS
What is Artificial Intelligence (AI)? - (6:53)
Broadly speaking, AI is getting computers to do the kinds of things that beforehand only humans could do.
How is Artificial Intelligence different than Machine Learning? - (8:39)
AI follows a series of rules that are determined by human input, whereas machine learning is pattern recognition that’s a result of exposure to many data sets from the real world.
Predictive Analytics is not the “lowest hanging fruit” for most businesses looking to implement AI into their marketing strategy - (13.54)
Massive data sets are needed to effectively utilize predictive analytics, and most businesses today do not generate the volume of data needed to make use of this form of AI. Businesses like Amazon, Netflix, Facebook, Google etc., who’s entire model is based on predicting likes, preferences, and relevant search results, are best positioned to make use of predictive analytics.
Quick Summary of AI, machine learning, and predictive analytics - (17:11)
AI - using a computer to take human expertise building in the if then rules to come up with an output whenever you give it an input.
Machine learning - the process of using technology essentially to do some sort of pattern matching to decide is a scenario going to be one variable or another. If I show you a million images, can you classify them one way or another?
Predictive analytics - taking a mass amount of data and being able to predict what future behaviors are. But the caveat is that it takes a massive amount of data, so the impact for marketers is you need to be in a high volume or high transaction business to be able to start using that predictive analytics mechanism.
who's doing a good job actually integrating artificial intelligence into their marketing efforts - (3:49)
E-commerce and online media are skyrocketing above the competition.
How E-commerce is utilizing AI - (6:04)
Consumers’ online activity and engagement with products is easily tracked and can be amassed quickly for effective analysis.
How the Social Media and Online Content industries are adopting AI - (12:23)
These industries are using AI to find out what type of behavior tends to preclude certain desired outcomes, such as signing up for an email list or spending time with a certain type of content.
So the moral of the story is… - (14:48)
The industries that are leading the charge in terms of the adoption AI are the ones that are data-rich. They have a large enough subset of data to be able to understand customers' behaviors, to be able to present the right products and the right content, and that's manifesting itself in e-commerce, social media, and online content.
MOST SMALL AND MEDIUM SIZED BUSINESSES DON’T COLLECT ENOUGH DATA TO INTEGRATE AI INTO THEIR OVERALL BUSINESS MODEL - (6:04)
But that doesn’t mean these businesses can’t use certain tools that incorporate AI, just that sinking too many resources into AI might be counterproductive. A tool is something that you can simply plug in and it will work, and it’s easy enough that even a consumer can use it.
EXAMPLES OF MARKETING TOOLS THAT LEVERAGE AI - (8:11)
Listing ads on Facebook, Google, or Twitter is actually using AI. Optimizing your business in the search domain is another example of using AI.