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AI in Product Marketing: Going Beyond Content Creation
In her recent talk for Aventi Group, Liza Adams –– CMO, AI expert, and skilled public speaker –– discussed the many ways AI can be relevant in PMM. And, while we know by now that AI can help us create content faster and more efficiently, it also has the potential to enhance the quality of our work significantly. A study by the Harvard Business School, which Liza referenced, showed that integrating AI into workflows not only expedites task completion by 25.1% but also enhances task quality by an impressive 40%.
When we tap into these capabilities, especially in their more advanced applications, AI has the potential to be a strategic partner in fostering sustainable growth. What are some ways PMMs can use AI that go beyond content creation? That includes collaboration and ideation, thought leadership, strategy, personas, and even strategic work such as competitive and win-loss analyses.
Liza gave several case studies to demonstrate her point, one of which we will summarize below. Others can be found on her LinkedIn profile, along with many other valuable resources on AI in product marketing.
Case Study: Strategic Decision-Making through AI-Driven Analysis
For Company X, a growing B2B tech firm, the executive team was at a crossroads. The CEO was adamant about targeting the [Industry Vertical 1] sector, while the CFO championed [Industry Vertical 2] for its financial potential, and the CPO saw [Industry Vertical 3] as the optimal path due to product alignment. The need for a unified strategy was clear, and the product marketing team, with its deep vertical industry understanding and market insights, developed an approach and framework to guide this crucial decision.
The AI-Driven Framework Approach
To move through the segmenting dilemma, Company X’s product marketing team proposed an AI-driven framework. This framework would serve as the basis for evaluating different market segments against a set of criteria, allowing for a data-driven and weighted analysis to help align the executive team.
A matrix was created with various evaluation criteria laid out on the rows, representing key decision-making factors such as market size, growth potential, competitive intensity, and product-market fit. These criteria were assigned different weights to reflect their relative importance to the company’s strategic goals.
Curating the Data
The product marketing team then faced the daunting task of data curation. They spent a couple of weeks gathering and formatting data from analyst reports for market size and growth, customer review sites for competitive intensity, CRM systems like HubSpot for sales and marketing alignment, and internal databases for partner strength and customer references.
With the data in place, the team harnessed the power of AI to analyze it. By prompting an AI tool like ChatGPT, the team could process the data and generate insights
AI Analysis and Heat Map Visualization
The AI was prompted to apply a forced ranking methodology, where the largest market size was scored highest and the smallest lowest, and similarly for growth rates. This resulted in a heat map that visually represented the strengths and weaknesses of each vertical based on the data-driven analysis. This was done for all the evaluation criteria. ChatGPT output a heatmap covering each of the criteria and the total across all criteria for each of the vertical industries, showing the top verticals.
The Discussion
The real value emerged when this analysis was brought before the executive team. The heat map served as a catalyst for a rich and robust discussion, where perspectives were shared, weights were debated, and adjustments were made. This conversation was not just about the numbers; it was about understanding each executive’s viewpoint and aligning it with the company’s overarching strategy.
Achieving Strategic Consensus
The result was more than just a selection of target verticals; it was a unified vision. Through this AI-driven framework and the ensuing discussion, Company X’s executive team could select two to three verticals to pursue, with a consensus that was informed, strategic, and aligned with each leader’s understanding and expectations. In this way, AI helped Company X with far more than simply creating content –– it enabled them to compare apples to apples and make an informed strategic decision as to which segments they should target.
The Smart Approach with AI in Product Marketing
As we’ve seen through the lens of Liza Adams’ strategic methodology and the journey of Company X, the intelligent application of AI in product marketing goes beyond mere computational speed and task automation. Rather, it’s about harnessing AI’s analytical prowess to cut through the noise, distill clarity from complexity, and bring alignment to diverse perspectives.
The case study underscores a pivotal narrative in the evolution of product marketing: the transition from hard work to smart work. AI is not a replacement for the nuanced understanding of market leaders; instead, it is a tool that amplifies their expertise, a collaborator that enriches strategic discussions, and a guide that navigates through the vast sea of data to unearth actionable insights.
In embracing AI, we commit to a smarter way of working—one where every decision is informed by data, every strategy is aligned with market dynamics, and every marketing initiative is optimized for impact. This is the promise of AI in product marketing: a promise of not just more efficient work, but of higher quality, greater relevance, and, ultimately, sustainable growth that aligns with the long-term vision of the company.
Embrace the future today by integrating AI into your product marketing strategy. Whether you’re looking to achieve greater efficiency, foster sustainable growth, or simply want to learn more about AI’s potential in product marketing, Aventi Group is here to guide you. Connect with us to discover how you can transform your product marketing with data-driven precision and personalized strategies that resonate with your market.
