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The Top 3 Use Cases Right Now for Artificial Intelligence in Marketing

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If you’re a marketer who wants to use artificial intelligence, the internet certainly isn’t doing you any favors.

There’s tons of hype about AI, but little substance on the subject of how you might actually use marketing AI systems and solutions.

We’ve spent a few years testing AI solutions, implementing AI for clients and talking to solutions providers about what’s possible.

So we thought it would be helpful to outline the biggest use cases for AI in marketing that we’re seeing right now.

This isn’t a comprehensive list of what AI can do, but it is a guide to what we think marketers ought to be doing with AI.

1. Cut Down Reporting Time

Internal reports are a pain.

On one hand, some brands have analytics tools configured, but fail to extract the most valuable insights from their data. 

Other brands, however, learn plenty from their analytics data, but spend hours of effort and analysis to create reports.

Artificial intelligence can solve either problem (or both). 

Solutions like PaveAI and Automated Insights exist to automatically generate written reports from Google Analytics data with little or no human intervention. 

In some cases, AI solutions may even be configured to automatically write reports from other systems as well, such as Narrative Science’s integration with Tableau. 

AI reporting has two major benefits for brands.

One, it saves a ton of time.

For instance, at PR 20/20, the agency that powers the Marketing AI Institute, we used natural language generation (NLG), an AI technology, to cut the analysis and production time of Google Analytics reports by 80%.

Two, AI can surface insights that humans might miss—or make it easier to draw connections between data points.

Written reports are generally easier to digest than charts and tables.

Text analysis draws connections between data points that we might have missed just browsing through numbers. It also frees us up to think about the relationships between data. 

This can result in clearer analysis and decision-making for the executives, managers and marketers consuming these reports.

2. Boost Ad Performance

We’ve also seen brands use AI to boost ad performance.

Using a solution like Albert, companies are able to optimize their advertising across channels.

Albert automatically targets audiences and buys media, then tests and optimizes those efforts at scale.

It’s just a more efficient way to manage digital advertising than using an all-human team.

It seems to work, too: A Harley-Davidson dealership in New York used the tech to increase sales leads by almost 3,000%.

Part of the system’s success was due to finding lookalike audiences who were also interested in buying from this particular dealership.

These were people who fit the description of previous customers who were of high value.

The artificial intelligence system then targeted these lookalike customers, which ultimately accounted for 50% of the total growth in sales leads.

Keep in mind: in our experience, many AI ad solutions require a high minimum ad spend per month, so these tools might be restricted to brands with larger budgets.

But for the brands that can afford them, they can provide a huge competitive advantage.

3. Improve Content Marketing

AI can also make your content marketing better.

There are a number of content marketing areas that AI can tackle:

One is optimization, or making your existing content better.

A solution like Acrolinx is used by brands such as Facebook and Nestle to create better content. The Acrolinx AI platform “reads” all of a brand’s content, then recommends ways to improve it.

Another way to improve content marketing with AI is by predicting what will work best next time you publish.

Scoop.it is an AI solution that uses a 35 million page database to determine what types of content resonate most with a brand’s audience.

These insights help marketers then predict what content will drive results with that audience, then promote this content to them.

Cortex is another solution that uses machine learning to predict what content works best.

The system assesses content, then recommends the optimal image colors, publication schedule, promotion cost and more based on historical data of what performs well.

Boomtrain is one other system that uses predictive algorithms to increase clicks, engagement and revenue.

This solution delivers to consumers the content they’re most likely to engage with, and delivers it via email, push notifications and the web.

Right now, we’re bullish on AI’s ability to reduce reporting time, boost ad performance and improve content marketing.

But there are plenty of other valuable use cases. We connect the dots for you every day at the Marketing AI Institute.

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