You’re building an Agentic AI product or solution—now what? Sales. But getting your product into the hands of paying customers turns out to be a lot harder than you thought it would be. That’s a typical case of asking the customer-driven questions last.
Selling an Agentic AI solution requires understanding how it integrates into existing data and processes, how your monetization model should align with customer success, and fostering cross-functional approaches to enhance market positioning.
Leah Tharin, Product Leader, joined me on “What’s the BUZZ?” to discuss how founders can drive product-led growth for AI and agents, and what to expect.
Understanding Your Product's Place in the Ecosystem
It seems that every software vendor wants to build and sell AI agents. If you find yourself in the same situation in your organization, start by recognizing the complexity of your customer’s data environment. Many companies find themselves mired in outdated or disjointed systems that produce inefficiencies. Your product can provide a solution that seamlessly integrates into this existing ecosystem. The most effective way to do this is to communicate the value of your AI agents in terms of how they can tackle existing challenges.
By showing how your product can enhance cross-departmental workflows, you can earn trust and buy-in from various stakeholders. If the sales team can use your AI solution to automate parts of their process while ensuring that support and marketing teams have access to relevant data, you’ll be creating a holistic approach that reflects a deep understanding of your user’s environment. This integrated solution enhances your pitch significantly, making it clear that you are addressing real pain points rather than selling a standalone product.
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Explain the potential benefits and efficiency improvements of AI agents.
Develop strategies to address challenges and risks associated with the implementation of AI agents.
Assess the impact of data quality and bias on performance of AI agents.
Identify the opportunities AI agents create for business efficiency and innovation.
Design a comprehensive plan for integrating AI agents into business processes.
Aligning Monetization with Customer Success
The next major aspect to consider is monetization and its impact on customer success. Transparent, fair pricing models are key for long-term business relationships. Remember, ineffective pricing can hinder user experience. If you have a tiered pricing model that limits usage, it can deter potential customers from fully embracing your solution out of fear of unexpected charges.
» Keep it simple on the lower market. And if you go up market on the B2B side try to target it towards the outcome. The other thing is that you need to understand for enterprise solutions is: It is a solution you probably need to explain to these customers as well.. «
— Leah Tharin
Instead, consider adopting a model that aligns with your customers' desired outcomes. If users can see how your product remains accessible while providing value, they’ll be more inclined to commit and even pay more for enhanced capabilities. This approach promotes a mutual gain — as customers succeed using your solution, your business thrives. Focusing on outcome-driven pricing will help you create a model beneficial for both parties, offering clarity on expectations while promoting sustainable growth.
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Finally, successful AI solutions require cross-functional thinking. Fragmented departments often create hurdles that any new solution must overcome. When pitching your product, consider how different teams within an organization will interact with it. If a sales solution operates in a silo, it might complicate communication between support and marketing teams, ultimately failing to deliver the promised benefits.
Instead, strive to create an understanding that your AI solution is more than just a tool; it’s part of a holistic approach to improving workflows and customer experiences across various departments. Encourage potential users to adopt your approach, leading to beneficial changes across the organization. By addressing cross-functional needs, you not only increase your solution’s appeal but also paint a picture of how it can be integral to the company's overall strategy and efficiency.
Summary
Product leaders looking to build and sell AI agents should focus on three key areas: Understanding the integration challenges with existing data, creating monetization strategies that link success for both you and your customers, and lastly, fostering a cross-functional approach in your sales and marketing to drive adoption. By embracing these insights, you’ll be better equipped to navigate the ongoing evolution of AI and mold your business strategy for the future.
Assess your product and its place within the ecosystem, refine your monetization strategy, and work collaboratively across departments to maximize your product’s impact.
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