Enterprise AI
November 15, 2023

6 Ways You Can Use AI To Create Better Content, with Miguel Guerrero, CEO of Otis AI

Miguel Guerrero, CEO of Otis AI, shares 6 ways to use AI for better content: diving into data, segmentation, crafting content, precise targeting, engagement analysis, and feedback loops.
Written by Ankur Patel
This is a summary of an episode of Pioneers, an educational podcast on AI led by our founder. Join 2,000+ business leaders and AI enthusiasts and be the first to know when new episodes go live. Subscribe to our newsletter here.

Imagine an orchestra where every musician was playing at the same time, competing for the limelight. It would be awful. That's what’s going on in today’s content landscape—a symphony of stale, vanilla voices where messages get lost in the noise.

Marketers and content producers today are familiar with this problem, and have been dabbling with various AI tools to help. But, it’s very overwhelming to understand all of the tools available and keeping up with the rapid enhancements in AI.

I sat down with Miguel Guerrero, Founder and CEO of Otis AI, on this week’s episode of Pioneers to break down the challenging topic of content saturation, and crafted a blueprint to help you understand what’s going on right now when it comes to using AI to produce and distribute better content.

"It's all about leveraging data," says Miguel. This isn't just crunching numbers; it's about crafting narratives from insights—knowing who's ready to listen and who's merely browsing. With the right data, you're not just broadcasting; you're engaging in a targeted conversation, investing marketing dollars with precision.

Otis AI's approach is like a scalpel in a world of sledgehammers.

"Visibility isn't enough," Miguel notes. "It's about connecting with the right people, with context, with relevance."

Otis thrives by tailoring suggestions, a technique mastered by giants like Netflix and Amazon. And now, Otis brings this power to emerging brands, helping them shine amidst the holiday ad blitz—not by outspending, but by outsmarting.

So, what can you learn from all of this? Let’s break it down:

Dive into Data

Use AI to enhance your understanding of customers by:

  • Applying machine learning algorithms to analyze customer data and uncover patterns that human analysis might miss.
  • Implementing AI for predictive analytics to not just forecast behaviors but also to suggest actionable marketing interventions.
  • Deploying AI to integrate first and third-party data, ensuring a holistic view that dynamically updates customer profiles in real time.

Pros and Cons:

  • Pros: AI can process vast datasets faster and with more nuanced insights than traditional methods.
  • Cons: AI systems require clean, well-organized data and can be costly to implement.

Segment and Conquer

Enhance segmentation using AI by:

  • Utilizing AI to dynamically segment customers based on real-time data rather than static customer lifecycle stages.
  • Employing machine learning to refine behavioral segmentation, predicting future actions rather than reacting to past ones.
  • Automating the tailoring of marketing campaigns with AI to adjust the messaging for each segment based on continuous learning.

Pros and Cons:

  • Pros: AI-driven segmentation can adapt to changes in customer behavior, keeping campaigns relevant.
  • Cons: There may be a steep learning curve in setting up and managing AI systems for dynamic segmentation.

Craft Content

Revolutionize content creation by:

  • Using AI for real-time A/B testing, where algorithms can test and switch content in live environments to immediately determine the best performers.
  • Exploiting advanced NLG tools that not only generate content but also adapt tone and style to fit different customer segments.
  • Developing AI-driven chatbots that learn from interactions to provide increasingly personalized content over time.

Pros and Cons:

  • Pros: AI enhances content personalization and relevance, improving engagement and conversion rates.
  • Cons: May reduce the unique voice or brand personality if not monitored and adjusted by human marketers.

Target with Precision

Sharpen targeting precision through AI by:

  • Leveraging AI in programmatic advertising to not just target but also predict the best times and places for ad placements.
  • Enhancing retargeting campaigns with AI can predict and act on the likelihood of a user returning to complete a purchase.
  • Incorporating AI in geofencing to not only target based on location but also predict when a customer is most likely to be in a certain location.

Pros and Cons:

  • Pros: AI targeting is more efficient, reducing wasted ad spend and improving the chances of conversion.
  • Cons: Risk of privacy concerns and the perception of invasive marketing if targeting feels too precise.

Analyze Engagement

Deepen engagement analysis using AI:

  • Applying AI to heatmaps to not only track clicks but also to predict which areas will become hotspots based on user behavior trends.
  • Using AI to measure scroll depth and time spent on the page to dynamically adjust content placement and format for maximum engagement.
  • Employing AI to analyze social interactions, learning from shares and comments to create content that is more likely to go viral.

Pros and Cons:

  • Pros: AI provides a more nuanced understanding of user engagement, leading to content that resonates more deeply.
  • Cons: AI analysis can be complex and may require skilled personnel to interpret and act on the data.

Build Feedback Loops

Strengthen feedback loops through AI:

  • Automating the collection and analysis of surveys with AI to identify trends and sentiment in customer feedback more quickly.
  • Using AI for sentiment analysis to not just understand the tone of feedback but to predict customer needs and address them proactively.
  • Creating AI-moderated community forums that can identify the most valuable user-generated ideas and highlight them for feedback.

Pros and Cons:

  • Pros: AI can handle large volumes of feedback efficiently, ensuring no customer insights are missed.
  • Cons: There's a risk that AI might misinterpret nuances in language, leading to incorrect conclusions without human oversight.

In the marketing “concert hall”, AI is not just an instrument; it's the conductor, the compass, and the architect behind every successful campaign. From diving deep into data to crafting content with precision, AI empowers marketers to cut through the noise and resonate with the right audience.

Miguel has shown us that it’s not about adding to the content chaos—it's about being smart, strategic, and personal. AI is the key to unlocking targeted conversations and turning insights into action. This is not the future; it's the present, and it's time to embrace AI in your marketing strategy to stay ahead in the game.

Join the pioneers leading the charge by watching our full discussion, and take the first step towards revolutionizing your content with AI.

Want to learn more about where AI meets great content? Check out our episode on how CEOs can use it to produce revenue-generating content with Jeff Coyle, Co-Founder and CSO of MarketMuse.

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