By Joshua Nite

Using AI for content is a little like using a crowbar for a hammer. Yes, it can get the job done, but it’s going to be a messy process with uneven results. AI is a great tool for researching content, even generating outlines and rough drafts, but it should be used sparingly on the content drafting side of things.

Where AI really shines in marketing is in data analysis. AI and machine learning algorithms are very good at spotting trends in large data sets. 

As we marketers lose some of our most useful data tools, AI and machine learning can help us pick up the pieces. 

Here’s the current state of generative AI for marketing data, and how it looks to evolve in the near future.

How generative AI unlocks the potential of marketing data

Marketers have no shortage of customer data on hand — quite the opposite. The challenge is to: 

• Analyze massive amounts of data for meaningful insights.
• Put these insights to work in a timely fashion.

Fortunately, generative AI can help with multiple aspects of these challenges.

Insight generation

AI algorithms can generate insight from data more efficiently and thoroughly than people can. AI can analyze massive data sets to uncover hidden patterns that might not show up in traditional analytics tools. 

As AI grows more sophisticated, it is also able to take on unstructured data that historically would have required human analysis. Text, images, and behavioral markers can all be a quantifiable part of your customer data set. 

Advanced behavior-based segmentation

Traditionally, marketers have relied on demographic attributes to create segments, with a reliance on third-party data. Generative AI algorithms can take a more nuanced approach by analyzing customer behavior to identify segments that are likely to convert given a specific intervention.

For example, the algorithm might detect a pattern that 75% of people converted after going to a particular page on your site, then receiving a specific series of follow-up offers.  You could market directly to this new segment, testing new offers that fit with the pattern of those who have already converted. 

Behavior-based segmentation gives marketers more insight into the who and why of their customers that goes far beyond age, gender or job title. 

Personalization in real-time at scale

Personalization is the cost of entry for marketers now. A recent study from Adobe found that 73% of customers expect personalization before and after making a purchase. But personalization at scale and in real-time requires superhuman capabilities. 

By analyzing vast amounts of data, AI algorithms can identify patterns and preferences unique to each individual or persona and identify trigger points. Then, AI-powered tools can dynamically generate personalized content and deliver it automatically when a trigger is spotted. 

Whether it’s hyper-relevant personalized product recommendations, dynamic email …read more

Source:: Top Rank Blog

Author: Aaron