Using AI in Marketing Will Allow for a Quicker Time to Market to a broader Audience
In general, the use of AI in advertising tends to reduce costs and optimize efficiency, but just as much as human companies do, it can directly affect the employment dynamics and demands on the workforce. Certainly there’s no doubt that AI in advertising will become even more popular as the tools become even more intuitive and diverse, humans respond to the trends, and companies adapt to these changes in order to remain competitive. But how will that be possible? Will people still be happy and willing to work at the same places? How quickly will the shift from traditional to new models happen?
Traditional advertising agencies are already using AI technology to provide analytical reports on the effectiveness of marketing campaigns. Such reports would likely be more accurate and provide valuable insight than ad agencies can provide on their own. However, the big question that arises is whether or not human beings will accept the same kinds of answers, which come from artificially intelligent programs. And it is precisely because of this tension between the customer and the business that an increasing number of businesses are starting to make use of an outside agency for the task of using artificial intelligence in their marketing. Whether they choose to hire a firm of researchers or simply outsource the task to someone else entirely depends on the type of business.
Those that are already online marketers tend to go the way of outsourcing, while those who have not yet begun to tap into the power of consumer data are more likely to integrate a technology into their marketing systems. Either way, online and offline marketers alike are taking advantage of AI to provide analytical tools and knowledge to assist them in making informed decisions about what strategies to pursue. These decisions can often prove to be crucial to the success of a given campaign.
When marketers incorporate AI into their system, they are able to take advantage of what’s known as deep personalization. In simpler terms, personalization is a process by which a particular piece of data is used to create personalized experiences for consumers. For example, a pregnant woman might be interested in learning whether or not she is a good candidate for certain medical treatments. If she is, she can request specific details from a predictive analytics company in order to narrow down her list of potential choices until she finds the one that’s right for her.
This example is a little farfetched, but it illustrates how predictive analytics and other AI technologies work together. Through the use of sophisticated machine learning algorithms, computer programmers build predictive analytics programs that can detect certain characteristics and behaviors from real-time consumer data. Once these characteristics and behaviors are detected, the program will be able to provide personalized options to consumers based on the analyzed data. It may be that the particular car a pregnant woman wants to drive is featured on a site about vehicle safety, or maybe she’s interested in learning whether or not a certain health condition impacts the likelihood that a person will be involved in an auto accident.
The beauty of this system is that the machine learning can be used not only to provide relevant suggestions, but also make personalized options available to consumers. However, as mentioned before, this isn’t always possible. Deep personalization requires large amounts of aggregate data, which most traditional websites are simply unable to provide. Unfortunately, most marketers have a limited understanding of what it takes to get their website, or a portion of their website, ready for the next stage in internet marketing: machine learning. There are some ways to solve this problem, however.
Machine learning is the process by which software identifies patterns from data, then uses that data to suggest different choices for a consumer. Deep personalization is impossible with anything other than large, complex databases; anything short of that will fall short of providing meaningful insights into how consumers think and behave. One of the best solutions to this problem is to leverage the power of digital marketing tools such as chat bots. These bots will be able to use their massive networks of users to identify unique consumer characteristics and use those features to offer personalized options.
Chat bots are not limited to offering personalization; they will also be able to use machine learning to recommend things based on their previous patterns. If a user goes to a shopping site and purchases a bottle of milk, the bot will remember that and suggest a milk delivery service if that is something that the user is interested in. In doing so, the bot has effectively used personalization, which was previously impossible on a smaller scale. There are many advantages to using artificial intelligence and chat bots in digital marketing. The first is likely to become clear as the field of artificial intelligence and digital marketing continues to grow; the second will become increasingly clear as more marketers understand the value in providing personal information to clients.
