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How Is Artificial Intelligence Used in Analytics?

How Is Artificial Intelligence Used in Analytics?


Analytics powers your marketing program, but how much value are you really getting out of your data?

Artificial intelligence can help.

AI is a collection of technologies that excel at extracting insights and patterns from large sets of data, then making predictions based on that information.

That includes your analytics data from places like Google Analytics, automation platforms, content management systems, CRMs, and more.

In fact, AI exists today that can help you get much more value out of the data you already have, unify that data, and actually make predictions about customer behaviors based on it.

That sounds great. But how do you actually get started?

This article is here to help you take your first step.

At Marketing AI Institute, we’ve spent years researching and applying AI. Since 2016, we’ve published more than 400 articles on the subject. And we’ve published stories on 50+ AI-powered vendors with more than $1 billion in total funding. We’re also tracking 1,500+ sales and marketing AI companies with combined funding north of $6.2 billion.

This article leans on that expertise to demystify AI.

And, it’ll give you ideas on how to use AI for analytics and offer some tools to explore further.

What Is Artificial Intelligence?

Ask 10 different experts what AI is, and you’ll get 10 different answers. A good definition comes from Demis Hassabis, CEO of DeepMind, an AI company that Google bought.

Hassabis calls AI the “science of making machines smart.” Today, we can teach machines to be like humans. We can give them the ability to see, hear, speak, write, and move.

Your smartphone has tons of AI-powered capabilities. These include facial recognition that unlocks your phone with your face (AI that sees). They also include voice assistants (AI that hears and speaks). And, don’t forget, predictive text (AI that writes).

Other types of AI systems even give machines the ability to move, like you see in self-driving cars.

Your favorite services, like Amazon and Netflix, use AI to offer product recommendations.

And email clients like Gmail even use AI to automatically write parts of emails for you.

In fact, you probably use AI every day, no matter where you work or what you do.

“Machine learning” powers AI’s most impressive capabilities. Machine learning is a type of AI that identifies patterns based on large sets of data. The machine uses these patterns to make predictions. Then, it uses more and more data to improve those predictions over time.

The result?

Technology powered by machine learning gets better over time, often without human involvement.

This is very different from traditional software.

A typical non-AI system, like your accounting software, relies on human inputs to work. The system is hard-coded with rules by people. Then, it follows those rules exactly to help you do your taxes. The system only improves if human programmers improve it.

But machine learning tools can improve on their own. This improvement comes from a machine assessing its own performance and new data.

For instance, an AI tool exists that writes email subject lines for you. Humans train the tool’s machine learning using samples of a company’s marketing copy. But then the tool drafts its own email subject lines. Split-testing occurs, then the machine learns on its own what to improve based on the results. Over time, the machine gets better and better with little human involvement. This unlocks possibly unlimited performance potential.

Now, imagine this power applied to any piece of marketing technology that uses data. AI can actually make everything, from ads to analytics to content, more intelligent.

How Is AI Used in Analytics?

Here are just a few of the top use cases we’ve found for artificial intelligence in analytics today.

1. Find new insights from your analytics.

Artificial intelligence excels at finding insights and patterns in large datasets that humans just can’t see. It also does this at scale and at speed.

Today, AI-powered tools exist that will answer questions you ask about your website data. (Think “Which channel had the highest conversion rate?”) AI can also recommend actions based on opportunities its seeing in your analytics.

Some tools to check out here include:

2. Use analytics to predict outcomes.

AI systems exist that use analytics data to help you predict outcomes and successful courses of action.

AI-powered systems can analyze data from hundreds of sources and offer predictions about what works and what doesn’t. It can also can deep dive into data about your customers and offer predictions about consumer preferences, product development, and marketing channels.


3. Unify analytics and customer data.

AI is also used to unify data across platforms. That includes using the speed and scale of AI to pull together all your customer data into a single, unified view. AI is also capable of unifying data across different sources, even hard-to-track ones like call data. 


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