AI Pricing: Navigating New Market Trends

In this session on AI pricing strategies, experts Joshua Bloom and Madhavan Ramanujam discussed the latest trends in pricing and the key factors to consider when developing your strategy .

1. We Are in a Time of Transition

From User-Based to Usage-Based and Outcome-Based Pricing

We’re currently in a time of transition, moving from traditional user-based pricing to more dynamic models like usage-based and outcome-based pricing. User-based pricing, which charges per user/ seat, is becoming less viable for AI products, especially those that automate tasks and reduce headcount.

 In contrast, usage-based pricing charges customers based on their actual use of the product. Simon-Kucher estimates that over two-thirds of AI-focused companies have already adopted this model, as it better reflects the value delivered by aligning costs with usage. 

Outcome-based pricing goes a step further; charging based on the results achieved through the product, such as cost savings or increased efficiency. This model is ideal for AI applications that deliver clear, measurable outcomes, providing a direct correlation between the value delivered and the price charged.

2. Value is King

Prioritize Value Creation Regardless of Pricing Model

Value creation should be at the center of any pricing strategy. Prices should be based on the perceived or actual value the application delivers to customers, including benefits like time savings, cost reduction, or productivity enhancements. Demonstrating the utility and ROI of your product is key to justifying higher price points.

3. Tailor Pricing to Industry and Use Case

Consider Augmentation vs. Automation

When developing pricing strategies, it’s essential to tailor them to specific industries and use cases. Begin by determining whether your solution is designed for augmentation or automation. Solutions that augment human tasks may be compatible with user-based pricing. In contrast, solutions that automate tasks and reduce headcount are generally better suited for usage-based or outcome-based models. This distinction is critical, as it can significantly impact long-term revenue potential. Misaligning your pricing model with the nature of your product can have lasting economic consequences, particularly with major accounts.

Additionally, different industries will have varying levels of openness to new or different pricing structures. Sectors with heavy AI adoption are likely to be more receptive to outcome-based pricing due to the clear, measurable benefits these models can provide. Conversely, industries without an influx of AI solutions may be more resistant to adopting new pricing models, preferring more traditional pricing until a more clear industry-standard has been set.

Understanding these preferences is essential for desiging a pricing strategy that aligns with the unique needs and expectations of each industry.

4. Strike the Right Balance with Attribution

Identify the Optimal Attribution Metric to Maximize Value Capture

One of the key challenges in implementing value-based pricing is accurately attributing the value generated by AI products. This becomes particularly complex when determining how much of the value/ outcome—such as cost savings or productivity gains—can be credited to the product versus other contributing factors like internal efforts or programs. The complexity is further amplified in sectors where human judgment and external variables play significant roles. Accurately attributing value is essential for setting effective outcome-based pricing, but it requires careful consideration to avoid overstating or understating the impact of your solution.

5. Regularly Reevaluate Pricing Strategies

Review Monthly, Adapt Quarterly, Shift Rarely

In this rapidly evolving market, pricing strategies should be continuously reevaluated to ensure they remain aligned with technological advancements, competitive pressures, and market expectations. Conducting monthly reviews can help maintain this alignment and keep your pricing strategy current. Additionally, continuous updates to packaging and features should be integrated into the R&D process and analyzed on a quarterly basis. 

While major strategic changes can be implemented every three to five years to adapt to new product developments and shifting market demands, they should be approached with caution. Significant pricing shifts are often met with resistance from customers. 

6. Implement Hybrid Models for Flexibility

Offer a Menu of Pricing Models

One of the best negotiation strategies a company can leverage is providing flexibility and options. Offering customers a choice between 2-3 pricing structures allows them to feel like they are getting a deal, shifting the conversation from a binary yes-or-no decision to a discussion about what works best for them. A hybrid pricing model can cater to a wide variety of customer segments by providing this flexibility. For example, an option of subscription or consumption-based models balances cost predictability with value, giving smaller companies the simplicity and predictability they need while offering larger enterprises the flexibility to accommodate more complex, usage-based pricing. 

This approach not only increases your likelihood of closing new deals but also opens the door for future pricing check-ins and value-focused conversations. 

Conclusion

Even the most advanced technology can’t achieve scale without a well-thought-out pricing strategy. Companies should consider adopting more dynamic pricing models, emphasizing value-based pricing, and continuously reassessing their strategies. Regardless of the pricing model, the strategy should be centered around creating value and providing customers with a sense of choice and partnership. Ultimately, a flexible and value-driven pricing approach is key to fostering long-term customer relationships and ensuring sustainable growth.

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