The 5 Ps of Marketing AI: Unleashing the Power of Artificial Intelligence

In marketing, you've likely encountered Philip Kotler's classic 4Ps or stumbled upon discussions about variations like the 6 or 7 Ps. But have you heard of the 5 Ps of Marketing AI?

It is a compelling and modern framework for the age of artificial intelligence crafted by Paul Roetzer and Mike Kaput. This innovative model emerged from their quest to answer a critical question: How can marketers effectively leverage AI?

Back in 2016, they started interviewing AI-powered marketing technology companies to understand the industry's AI adoption status. These insightful conversations served as the foundation for their framework. Applying the framework, they conducted over 400 interviews with marketing professionals, exploring which marketing activities had the highest potential to be optimized with AI (keeping in mind the time and cost-saving potential of AI).

The outcome? In 2021, they unveiled a scoring model pinpointing the best use cases for AI and technologies across each of the 5 Ps, concluding that AI has a very high potential for boosting the marketing activities of those interviewed.

Now, let's go through some important use cases of their research. I’ve added the scores from Roetzer's and Kaput's surveys indicating the value marketers perceived for the different purposes (5 being the top score).

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Planning – Building Intelligent Strategies

A solid marketing strategy lays the groundwork for success. In this category, some crucial use cases stand out like choosing keywords and topic clusters for content optimization (3.78/5). AI can analyze vast amounts of data to identify trending keywords and relevant topics. Using AI tools to analyze search trends, social media discussions, and competitor content in real-time makes it easier to find optimal keywords and topic clusters for content creation. AI can also analyze existing online content for gaps and opportunities (3.75/5) and score leads based on conversion probabilities (3.69). The last one is music to the ears of sales teams.

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Production – Creating Intelligent Content

Creating data-driven content (3.82/5) earned the highest score in this category. AI's ability to process data and identify audience preferences simplifies creating content tailored to specific demographics. For instance, AI algorithms can analyze customer behavior and preferences, enabling the generation of content that resonates with the target audience. Additionally, optimizing website content for search engines (3.77/5) becomes more efficient with AI. Instead of hiring an agency for an SEO audit, AI can analyze trends, suggest improvements, and automate adjustments for better search engine visibility, leading to substantial cost savings. Another interesting use case was predicting content performance before deployment (3.70/5), where AI analyzes historical data to forecast how well specific content types or topics will perform.

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Personalization – Powering Intelligent Consumer Experiences

The most applicable use case in this category was recommending highly targeted content to users in real-time (3.96/5). AI's ability to scan large amounts of data and interpret user behavior enables the prediction of content that is interesting to them. AI can create customer segments and "nano-target" them with matching content, based on their interests and motivations. Determining offers that motivate individuals to action (3.74/5) was another highly valued use case, allowing customers to receive better cross-marketing offers that can lead to additional sales or grow the basket size in eCommerce. Additionally, presenting individualized experiences on the web and/or in-app (3.74/5) holds high potential, suggesting that web pages or in-app content may look very different for every user in the future.

Promotion – Managing Intelligent Cross-Channel Promotions

Adapting audience targeting based on behavior and look-alike analysis (3.92/5) scored high in this category. AI's ability to analyze user behavior refines audience targeting and identifies look-alike audiences. For instance, leveraging AI algorithms to analyze customer interactions and behaviors allows for adapting targeting strategies to reach audiences with similar characteristics. Another powerful use case was predicting winning creatives before launch without A/B testing (3.81/5). Thanks to AI's vision and ability to recognize pictures, it can scan through thousands of ads in seconds, finding correlations, patterns, and insights of colors, fonts, call-to-actions, settings etc. to forecast the most likely winning content before launch.

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Performance – Turning Data into Intelligence

Measuring ROI by channel, campaign, and overall (3.91/5) is a crucial aspect where AI applications shine. While marketing ROI can be tricky, often upper-level management is highly interested in understanding the returns on marketing investments. AI applications can improve traceability and verification regarding the campaign or channel that generated the sale. Discovering insights into top-performing content and campaigns (3.86/5) and forecasting campaign results based on predictive analysis (3.80/5) were also appreciated activities, yet they are similar to what we discussed earlier. AI's ability to analyze performance metrics and identify patterns from historical campaign data can help with predicting future outcomes and success factors to refine strategies.

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Conclusion

As we step into a new age where AI disrupts the entire marketing industry, having a modern theoretical framework like the 5 Ps is important. Understanding the high-value use cases for boosting and optimizing performance while cutting down on unnecessary marketing expenses positions marketers for success in this AI-driven era. This article became a bit longer than I anticipated, but I will continue to share easily digestible chunks of AI in the marketing and business context in the future.