How to Use AI to Achieve Business Outcomes in Marketing

Artificial Intelligence
Business Outcomes Using AI

Artificial intelligence (AI) has a lot of buzz behind it these days. And rightfully so. It can be a technological game changer for marketers and other business professionals. As I’ve told my University students in the past – she who learns fastest wins. Where AI provides a major competitive advantage is in the learning of “machine learning.” What would take a team of data scientist weeks to uncover could take a matter of hours with AI. Brands that leverage this speed will most likely outpace competitors and produce business outcomes more quickly across marketing and other disciplines.

The key to successful use of AI is data. Bad data in equals bad data out. However, good data in equals good data out. In addition, the more good data available to learn from the more accurate and poignant the results will be. Thus, driving more and better business outcomes.

Whether a brand is using AI for advertising and marketing or whether it’s using it for logistics, the bigger the quantity of quality data used in the algorithm equates to better output for making business decisions that drive outcomes. These decisions can be programmatic or made by a manager in real time post output.

From a marketing perspective there are three key business outcomes for content amplification using AI. They include awareness, consideration and conversion. In many cases these goals are siloed in other departments and there’s not too much coordination between them. In a world where AI is deployed this is not necessary at all. Brands can use AI to efficiently bridge these goals and optimize at each step of the buyer’s journey.

Awareness

This is where content marketers tend to spend the bulk of their time. Fifteen years ago, most marketers focused on the middle and bottom of the funnel mostly. That has changed drastically over the last ten years.

Awareness Content

In this category, AI can be used to optimize towards viewing and engaging with helpful content produced by a brand or media outlet and should drive trust. Technologically speaking, it uses big data to explore demographics, devices, regions, networks and others in order to select and optimize the most successful combinations.

Consideration

This type of content is amplified and shared by marketers who have determined that a particular user has engaged with and consumed awareness content. The best way to deliver this content is post-awareness content engagement in real-time. Meaning, it should be served up immediately after the top-funnel content is engaged with.

Consideration Content

While the example provided for earned content (third-party reviews) in the awareness stage above can be the first touch with a consumer, it can also be delivered in real-time during the consideration phase of the buyer’s journey. The idea is to deliver content which when engaged with shows intent and/or affinity for a brand.

Rather than “guessing” which content will deliver the consideration results desired, AI can do the optimization on the next step in real-time and learn what is the best next action to deliver consumer engagement. Ultimately, this drives optimized business outcomes in this step of the buyer’s journey.

Conversion

Most marketers don’t need much explanation on this bottom part of the buyer’s journey. Capturing email addresses and other first-party data is very valuable, not just for marketers, but for the AI that uses it for targeting and other things.

Conversion Content

This is the content marketers want to deliver after a consumer engages with consideration content. It can be done in real-time and/or via email over time. The end result of this engagement at this stage of the funnel delivers real business results. Using AI to optimize towards this outcome is a competitive advantage for brands marketing with this technology.

The reason AI is so good at driving business outcomes optimally and quickly is simple: she who learns fastest wins. The more good data is added to machine learning the better and faster is has the potential to learn. As mentioned above, what would take a team of data scientists weeks to uncover can be discovered in a matter of hours with AI. Thus, delivering real business outcomes most optimally.

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