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3 Striking Ways Artificial Intelligence Matters to Your Marketing Initiatives

by Jason Flaks | May 15, 2017

It’s hard to think of artificial intelligence or AI as anything more than a science fiction story, one that usually doesn’t go well for the humans. But the reality of artificial intelligence and machine learning – and make no mistake, it’s a reality – is the benefit and value these technologies bring to the everyday.

Artificial intelligence, or AI, has significantly expanded since its beginnings in the 1950s. And AI’s sub-specialization, machine learning, has spurred advancements in a broad range of industries in just the last decade, especially in marketing. Despite what you may see in the press, there is far more to AI and machine learning than just IBM Watson.

A Brief History of AI and Machine Learning

While most people have an understanding of what artificial intelligence is, it’s worth taking a moment to understand both what it and machine learning are to truly understand the benefits they have to marketing.

Artificial intelligence is both the theory as well as the development of computer systems that act like humans. So instead of following a specific set of instructions, they use heuristic reasoning to recognize objects they may have never seen before or make decisions.

Machine learning, on the other hand, is a subset of AI. It’s one of the mechanisms by which artificial intelligence can be realized. At its core, machine learning is the programming and process of computers adapting and learning from data and information.

The field of AI isn’t new. In fact, computer scientists have been actively working and advancing AI since the early 1950s, when Alan Turing developed the Turing Test. It’s in the last decade, though, when we’ve seen the most rapid developments in the field of AI, largely thanks to machine learning advancements.

With gaming taking a large lead with AI, thanks to devices like the XBox Kinect, multiple fields have benefited from what we now understand about a machine’s ability to learn and predict outcomes based on data. One of the biggest benefactors to these advancements is marketing.

Top 3 Benefits of AI on Marketing

Marketing can certainly use all the help it can get. In a very short time, we’ve gone from only a few potential channels to reach a company’s potential audience, to literally hundreds. Which are the best? What’s the best message? How do we identify the tactics that are most effective?

These are the areas where AI and machine learning excel. There are an ever increasing number of areas in which AI and marketing are making huge strides, but here are three of the biggest areas with the farthest reaching benefits to the industry.

1 – Enhancements in Testing

General Electric gif science tech future GIFOne of the most crucial strategies leading to improved marketing results is testing. Understanding what works for the target audience, and testing to make improvements can lead to significant ROI and conversions.

Yet some estimate that as little as 1 in 8 A/B tests results in actionable changes with significant results.

Holding many marketing groups back from testing as much as they would like is resourcing, plain and simple. There isn’t enough staff, hours in the day, or dollars allocated to marketing budgets to do the amount of testing that would be effective at scale.

Enter machine learning. In 2016, Unbounce co-founder Oli Gartner announced the creation of Conversion Equation. It’s a machine learning equation that predicts ways to improve conversion on your website.

The equation steps through a website, in real time, and makes suggestions on what should change to improve conversions, with specific instructions, freeing up marketers to better understand their markets and explore new initiatives.

2 – Social Semantics

Social networks are like large neural networks to machine learning, the kinds of things computer systems use to develop the predictive analysis marketing needs them for.

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One example is Facebook’s DeepFace. This algorithm uses facial recognition to identify individuals with nearly the same rate of accuracy as a human, and recommend that site users tag specific friends based on that recognition.

Another example is advanced chatbots. While many chatbots follow a structured script, advanced chatbots are beginning to leverage neural networks. These chatbots learn language like a child does, over time and with examples. When it’s struggling with a particular concept, you provide it with more examples instead of re-writing the underlying code.

3 – Speech and Language Recognition

 GIFAdvancements in AI and marketing go far beyond the reaches of websites and social media. These technologies can help humans understand one another better, and help marketers understand the language patterns that are most effective when speaking with a prospective client.

Skype Translator, for instance, can translate conversations between participants based on its learning from massive amounts of data inputs. And speech recognition is critical to all of the new digital assistants now available, like the Amazon Echo, Siri, and Google Home.

Much like website testing, improvements to call center operations can be slowed by resource availability. A single person can only listen in on one conversation at a time, limiting a company’s ability to identify sales and opportunities or understand which agents need more help. Products like Marchex’s Speech Analytics use AI and machine learning to help identify issues that need to be addressed or optimize calls for conversion.


Despite predictions by science fiction authors and filmmakers, AI has the potential to advance a number of industries, from healthcare to entertainment to marketing. With the ability to process far more data than a marketing staff could ever hope to review and understand, machine learning stands to help marketers refine and improve on messaging and tactics across and within channels to create a better user experience and draw in more qualified, and more profitable, leads.



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