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Is machine learning the future of marketing?

by Loknath Das

machine learning

What will the future of marketing hold? Will it be entirely automated by smart AIs that fully understand human nuance? Probably not. Will it be entirely manual and managed only by individual people without the aid of technology? Definitely not.

As we’ll discuss shortly, the top influencers in marketing put their heads together on this very topic, and the results may surprise you. In any case, it’s safe to say that marketing probably isn’t going back to the old days of billboards, newspapers, and radio spots. The numbers don’t lie: the future of marketing is definitely digital.

The digital marketing space continues to grow: Online sales have doubled in the past five years, and more than two-third of adults in the U.S. shop online monthly. Revenue for online advertising recently surpassed that of television for the first time in history, and growth of traditional advertising such as TV and print are projected to stay flat while newspaper advertising continues to decline.

What all of this means is that marketers need to develop effective strategies to realize the opportunities digital provides. However, there are several factors that can either help or hinder your digital marketing efforts, and they all revolve around data and the customer journey.

Too much data, too few answers

Marketers must always strive to understand the needs of their customers, so digital marketing is driven by customer data. The good news is that there’s a wealth of data in every online search and click that can reveal insights about consumer behavior and demographics. Ideally, marketers would use this information to drive customer engagement that leads to increased revenues.

The problem is that data isn’t an easy-to-use solution to marketing challenges in and of itself; it needs to be collected, managed, and interpreted correctly for it to have any value at all. Even valuable data can go to waste when it isn’t integrated properly, and most marketing leaders spend up to half their budget on data analytics that ultimately lead to no company-wide improvements.

Data is also often mismanaged because of a lack of central ownership. This leads to significant digital skills gaps that are projected to cost businesses $3.3 billion by 2020 considering that much of the data marketers collect gets mismanaged and thus becomes irrelevant, redundant, or obsolete.

It’s always a bad investment when businesses spend money on data that goes nowhere. There needs to be a method to solve data management problems so marketers can realize the benefits of using data for digital marketing.

Customers are in control of their own journey

 Back in the day, advertising was a one-way street: Businesses sent advertising messages to customers to drive sales through one-way channels such as billboards, print, and broadcast. There was no dialogue between companies and consumers. People didn’t have the internet to allow them to find the best possible deal, nor did they have powerful social networks to let them know about others’ brand experiences. Nowadays, most of the buying process is customer-controlled.

In addition, consumers are growing intolerant of annoying and irrelevant advertising, and pop-ups and other unwelcome messages are now getting blocked with increasing frequency. In fact, 11 percent of global consumers now use ad blocking software, up 30 percent since last year. Google Chrome will soon have a built-in ad filter feature, as well. The use of ineffective online marketing communications isn’t just wasteful, it can also be toxic to your brand as consumers become annoyed and shut you out completely.

As a result, marketers now need to ensure that they’re reaching the right customer at the right time with the right message to drive brand engagement. Otherwise, they risk annoying or upsetting their customers, thus leading to brand abandonment.

Machine learning helps you use data to serve empowered consumers

In a perfect world, marketers would use insights from data to engage with empowered consumers and help them make smart purchasing decisions through digital marketing. However, the challenge marketers face is managing massive amounts of information to serve a fickle market that will punish them harshly if they make a mistake.

As brilliant as marketers are – and must be in these challenging times – it’s difficult to downright impossible for individuals to put their arms around the millions of data points that constantly stream in from their digital marketing campaigns every nanosecond. Thus, an automated process called machine learning is necessary to take all the data you collect, organize it, manage it, and use it to predict the best ways to reach people with messages to galvanize buying behavior most effectively.

Machine learning means using predictive analytics and intelligent automation to formulate data-driven predictions. It allows marketers to identify the likelihood of future outcomes based on historical data. In a recent survey of top marketing influencers, 97 percent said that the future of marketing will actually be a combination smart people armed with machine learning – in other words, that machine learning is the future of marketing. Some of the use cases for machine learning include:

  • Chatbots and Voice Assistants – The increasing use of conversational chatbots and voice assistants from Google, Amazon and Facebook highlights the importance of being able to intelligently create a relevant and engagingly conversational user experience based on empirical data.
  • User Engagement – The use of machine learning to build predictive analytics models, such as those created by Urban Airship and Microsoft Azure, can determine potential points of customer churn and proactively help businesses retain customers.
  • Natural Language Processing – Machine learning can be used to optimize bidding in digital advertising, mitigating data scarcity with highly accurate predictive models based on semantically similar keyword groups, such as the model used by QuanticMind.

The rise of digital marketing presents many challenges and opportunities for marketers. Those who manage data effectively to communicate with consumers appropriately will have an advantage over those who don’t. Machine learning offers marketers the ability to fully realize the benefits of digital marketing, build real user engagement rather than being filtered out…and ultimately grow their business and revenues by always being where their customers are.


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