In a recent YouTube video from Monetizely's channel titled "How To Do Rapid SaaS AI Software Packaging With GenAI," the presenter demonstrates a streamlined approach to creating effective product packaging strategies using artificial intelligence. The video walks through a practical example of leveraging AI to generate multiple packaging variants for a hypothetical contact center product, providing SaaS executives with a valuable framework that can be applied to their own products.
The Key Principles of Effective Packaging
Before diving into the AI implementation, the presenter outlines five essential principles for effective package design:
- Market Segment Alignment - Packages should be tailored to specific market segments so that "when someone from that segment looks at that package, they know that this is for me."
- Revenue Capture - Ensure you're capturing the high end of the revenue curve. As the presenter states, "when there are customers that have high willingness to pay, you capture that money because that is where most of the money gets made."
- Clear Differentiation - Packages should be "well differentiated between each other and don't cannibalize each other."
- Growth-Oriented Design - Structure packages to facilitate "high upsell, high net retention rate because that is how most software businesses are built."
- New vs. Existing Customer Consideration - Recognize that "what works for an incoming customer may not be what will work for an existing customer, given how much more an existing customer will have to pay to just get a few more features."
These principles serve as the foundation for the AI-assisted packaging strategy demonstrated in the video.
Setting Up Your AI-Powered Packaging Strategy
The process begins with organizing your product information in a structured format. The presenter shows a spreadsheet containing:
- Feature List - A comprehensive list of product features with descriptions and identification of core features (those required for the product to function)
- Channel Information - The platforms or mediums through which the product operates
- Segmentation Data - Clear definition of target segments (in this case, SMB, mid-market, and enterprise), including qualitative descriptions and quantitative boundaries
"In most companies, you will have some amount of segmentation like this," the presenter explains, showing how SMB customers might need something "out of the box," while mid-market requires channel consolidation and some automation, and enterprise customers demand compliance features, governance, and more sophisticated automation.
Generating Packaging Variants with AI
The core of the approach involves creating a detailed prompt for an AI system like Claude. The presenter shares a prompt template that instructs the AI to act as a "senior pricing strategist" and generate three distinct packaging variants based on different strategic objectives:
- Market Penetration - Making entry-level plans attractive to maximize customer acquisition
- Upsell Revenue Maximization - Incorporating add-ons to drive ongoing revenue growth
- Upfront Deal Value Maximization - Creating packages that increase initial contract values
The prompt includes specific rules about feature allocation (ensuring core features appear in all packages) and asks the AI to follow the packaging principles outlined earlier.
Analyzing AI-Generated Packaging Options
The results demonstrate the power of this approach. For each strategic objective, the AI generates a complete packaging structure with:
- Tiered packages (e.g., Essentials, Professional, Scale)
- Logical feature distribution across tiers
- Rationale explaining the strategy behind each variant
"It's bifurcated the features on its own into core features, AI automation, which is sensible, advanced channels that is also sensible," the presenter notes, highlighting how the AI has intelligently organized the features.
The presenter then analyzes the different variants, noting that the upfront deal value maximization approach might lead to "heavy discounting and people being unhappy with core and advanced," while the upsell revenue maximization model offers "enough add-ons for you to customize and tailor fit this plan for different segments."
From AI Suggestions to Strategic Decisions
The real value of this approach isn't letting AI make your pricing decisions, but rather using it to overcome "writer's block" and generate strategic options for consideration.
"Maybe I'll pick the essentials from this one and the other plans from this to create my final structure," the presenter explains, demonstrating how executives can mix and match elements from different AI-generated variants to create an optimal packaging strategy.
The result is a data-informed starting point that facilitates productive discussions with stakeholders: "It gives you something ready to have a discussion about rather than creating this on your own in the first blush and gets you to an answer much faster."
Embracing AI as a Strategic Partner
The video concludes with an important perspective on the role of AI in strategic pricing decisions. Rather than replacing human judgment, the approach positions AI as an enabler that accelerates the decision-making process.
"I would encourage you to actually use this because we are only going to a place where we are going to have more AI usage rather than less," the presenter advises, suggesting that familiarizing yourself with these approaches now will prepare you for a future where AI plays an increasingly prominent role in pricing and packaging.
For SaaS executives looking to streamline their packaging process while maintaining strategic control, this AI-assisted approach offers a powerful middle ground—leveraging technology to generate options while preserving the essential human judgment needed to make final decisions.