Embedded AI Makes Sense for Marketers

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Embedded AI Makes Sense for Marketers

Anyone who has read about big data has come across this famous IBM quote: “Every day we create 2.5 quintillion bytes of data—so much that 90 percent of the world’s data today has been created in the last two years alone.” What you may not realize, though, is that it was expressed in the context of a 2011 CMO Study.

Already five years ago, CMOs found themselves drowning in data, and the numbers just keep going up, making it a real challenge to put all that data to use.

“Last year we collected eight zettabytes of data, which is an incredible amount of data that is only going to grow,” Seng Sun, CEO of SunView Software said in an interview. Merely having huge volumes on data is not helpful if marketers don’t know to use it for actionable insight. That’s why they are turning to AI that uses machine learning to point out the direction to take based on their data. “Big data, machine learning, and AI are interconnected,” he declared.

While data analytics have been around for a while, they have been primarily concerned with historical information—generating reports on what has happened in a defined space. Sun offered the example of analytics revealing the stats of how many cars sold the previous month. But what the dealer is really after is a prediction for how many will sell in the next month. AI makes it possible to get the answers to predictive questions.

That helps to explain the growing popularity of AI for marketers. Among the companies contributing to this trend, of course, is Salesforce with its September release of Einstein, with the tagline “AI for everyone.” September was also the month in which SunView Software released its latest iteration of software with intelligence embedded inside the application. It will enable a “much more efficient and effective decision making process,” Sun says, as it works in real time without having to bring in a data specialist. “The more data you have, the better it is going to get.”

He offers an analogy to how children advance in reading skills. When they first learn to read, they have to sound out words, so it takes them quite a while to get through a sentence. But as they progress, they develop a “visual dictionary” in their heads that enables them to read through familiar words much more quickly. That’s pattern recognition at work. For machine learning, “the more it knows, the better the solution it will suggest for you.”

Sun notes that marketers are earlier adopters of solutions real time insight because they know that the effectiveness of their campaigns depends on timeliness. IT departments tend to lag behind because they “have been very reactive for many years” and keep a lot of data around in a dormant state. However, he believes they will come to realize that AI is worth pursuing for any amount of stored data that can yield valuable insight.

While the increase in the size of data appears daunting to humans, it makes machine learning work more efficiently and effectively. As the volume, variety, and velocity of data keeps growing, the Ai’sembedded AI solution makes sense for businesses today.

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