Conversation-Based vs. Resolution-Based AI Pricing: The Best Model for Modern Customer Service

Imagine transforming the way your business connects with customers—faster, smarter, and more personal than ever before. That’s the power of AI in customer service. But here’s the catch: the pricing model you choose can make or break your success. It affects not only your costs but also how happy your customers are and how smoothly your operations run. In this article, we’ll compare two popular pricing models: conversation-based and resolution-based pricing.

What is Conversation-Based Pricing?

Conversation-Based Pricing charges businesses based on the number of customer interactions (or conversations) initiated, regardless of the resolution outcome.

Key Features:

• Predictable and Transparent Costs: Businesses can easily forecast their expenses based on expected conversation volumes.

  
  

• Agent Seats Included: Many conversation-based pricing models include unlimited agent seats at no extra charge, reducing costs as your team scales. This is however, not the case with resolution-based pricing models. 

  
  

• Proactive Engagement: Teams are encouraged to prioritize customer satisfaction and relationship-building without penalty for follow-ups or ongoing conversations.

  
  

How is a Conversation Defined?

In Conversation-Based Pricing, a “conversation” typically refers to a single, continuous interaction between a customer and a support system. This includes all messages exchanged during that interaction, whether it’s resolved entirely by AI, involves human assistance, or requires multiple back-and-forth exchanges. Conversations are usually considered complete when there is a defined period of inactivity (e.g., 24 hours) or when the issue is marked as resolved.

An outbound conversation, on the other hand, is initiated by the business rather than the customer. This could include proactive outreach such as follow-ups, notifications, or engagement campaigns. Once the customer responds, the conversation follows the same rules as inbound interactions, with all messages counted as part of the same conversation until it is resolved or reaches a period of inactivity.

By standardizing the definition of a conversation, this pricing model ensures clarity for businesses. 

Example of How It Works

Imagine a business using Conversation-Based Pricing at $0.59 per conversation. Over a month, their customers initiate 1,200 conversations. Whether these conversations are resolved entirely by AI or require a combination of AI and human assistance, the cost remains the same:

1,200 conversations × $0.59 = $708.

This straightforward pricing structure ensures businesses pay only for the interactions initiated, without worrying about how they are resolved.

“I was skeptical at first, but this new pricing model won me over. It’s transparent, predictable, and aligns perfectly with CX leaders’ goals.” - Charlene Mulholland Stanton, Partnerships Lead, Swap

Conversation-Based pricing empowers businesses to focus on delivering exceptional customer service, knowing that their costs will remain predictable.

What is Resolution-Based Pricing?

Resolution-Based pricing charges businesses based on resolved issues, where the vendor determines what qualifies as “resolved.”

Key Features:

• Tied to Resolutions: Costs are linked to cases marked as resolved, often defined by criteria such as customer confirmation or inactivity (subject to differ depending on the vendor). 

  
  

• Additional Costs for Agent Seats: Businesses usually pay extra for agent seats to manage conversations unresolved by AI. 

  
  

How is a Resolution Typically Defined?

In Resolution-Based Pricing, a “resolution” is typically defined as an issue resolved entirely by AI, with no human intervention. This could include:

• Customer Confirmation: The customer explicitly states their issue is resolved after interacting with the AI.

  
  

• Inactivity: The conversation is automatically marked as resolved after a set period of customer inactivity (e.g., 48 hours).

  
  

• Predefined Guidelines: The issue meets specific vendor-defined requirements, such as completing an automated workflow or receiving a system-determined classification of resolution.

  
  

While this may appear straightforward, subjective definitions can lead to disagreements between businesses and vendors about whether an issue was truly resolved. Disputes can arise in situations such as:

• Customer Perception vs. Vendor Standards: A customer may not feel their issue is fully addressed, but the vendor’s criteria automatically mark the case as resolved. This can lead to frustrated customers, reputational damage, and increased costs from reopening unresolved issues.

  
  

• Incomplete Resolutions: The AI may resolve part of the customer’s inquiry but fail to address the full scope of their concern, leaving the customer dissatisfied while the vendor still considers it resolved.

  
  

• Edge Cases and Complex Scenarios: Certain interactions, such as escalations or multi-step resolutions, may blur the line between resolved and unresolved, leading to conflicting interpretations.

  
  

• Automated Classification Errors: Vendors may rely on automated systems to categorize resolutions, but these systems can misclassify conversations, marking them resolved when they’re not.

  
  

Key Challenges 

• Paying for separate CRM and Ticketing Tools: Many businesses must maintain separate CRM and ticketing platforms, which can cost between $75 and $200 per user, adding significantly to monthly expenses. These systems rarely talk to each other leading to significant loss of data. 

  
  

• Additional Costs for Agent Seats: Even with AI handling a portion of interactions, businesses often need agent seats for unresolved cases. Depending on the CX tool, these can range from $50 to $200 per seat, further increasing costs.

  
  

• Budgeting Complexity: The combination of variable resolution costs, CRM and ticketing expenses, and agent seat fees makes it difficult to predict and control total monthly costs.

  
  

These subjective elements make it challenging for businesses to rely on Resolution-Based Pricing as a clear and fair cost model. Discrepancies in how resolutions are defined and counted can lead to overcharging and strained vendor-client relationships.

Example of How It Works

Imagine a business using Resolution-Based Pricing at $1.19 per resolved issue. Over a month:

• 1,200 customer interactions are initiated.

  
  

• 50% (600) of these interactions are considered resolved entirely by AI, according to the vendor's criteria.

  
  

The cost is calculated as follows: 600 resolved issues × $0.99 = $594.

If you also consider that you’ll most likely need to pay for a CRM and ticketing platform, the math will look like this:

600 Resolved Issues @ $0.99 = $594
CRM Seats (4 users @ $125 each) = $500
Ticketing Platform (4 users @ $100 each) = $400

Total Monthly Cost = $594 + $500 + $400 = $1,494

In addition to this cost, businesses will often still need to pay for agent seats to handle unresolved interactions that require human assistance (ranging anywhere from $50 - $200 per seat depending on the CX tool used). These additional seat costs represent a significant increase in the overall expense of Resolution-Based Pricing compared to other models.

To learn how consolidating these costs with Kustomer’s unified platform can save your business money and simplify operations, check out The Future of Customer Service: One Unified Platform for Everything.

Resolution-Based Pricing can appear outcome-focused, but its subjective nature, variability, and potential for added costs often make it less predictable and more expensive for businesses.

Key Differences Between the Models

Benefits of Conversation-Based Pricing 

1. Predictable Costs

Conversation-Based Pricing allows businesses to easily budget for customer service operations. With costs tied to interaction volume, organizations can plan confidently without worrying about fluctuating resolution rates or timelines.

According to the 2024 State of Pricing in Customer Service, 68% of CX leaders identified cost predictability as a top priority when evaluating pricing models for customer service AI. This highlights the growing demand for models like Conversation-Based Pricing, which offer stability and ease of forecasting.

Why It Matters: The financial stability from the predictable nature allows you to focus on delivering exceptional service, optimizing team performance, and scaling your operations strategically, knowing your costs will remain manageable.

2. Improved Customer Experience

This model enables customer-focused engagement, allowing businesses to connect with customers in the way that works best for them—whether through AI, a human agent, or a seamless combination of both. With Conversation-Based Pricing, you can prioritize delivering the right experience for each customer without worrying about additional costs for follow-ups or complex interactions.

Why It Matters: As a CX leader, you can focus on creating positive, lasting relationships with customers, knowing that every engagement is optimized for their needs and adds value without driving up costs.

3. Operational Efficiency

Conversation-Based Pricing empowers businesses to maximize efficiency by leveraging AI to handle a significant portion of customer conversations. This reduces the need for large headcounts while ensuring your team can scale effectively during spikes or busy seasons. With Kustomer, you can onboard additional team members temporarily without incurring extra costs for software licenses, keeping operations flexible and cost-effective.

Why It Matters:This efficiency allows your team to focus on complex customer needs. During high-demand periods, you can scale up your support team without worrying about prohibitive software costs, ensuring both operational agility and exceptional customer service.

4. Simplicity and Transparency

Conversation-Based Pricing is straightforward and objective, making it easier for businesses to align their customer service strategies with their financial goals. Unlike Resolution-Based Pricing, there’s no ambiguity over what counts as a chargeable interaction.

“Kustomer’s new pricing model is smooth, I love that AI is included in every package with zero surprises or overage fees.” - Tanner Chatterley, CEO OrderProtection.com

Why It Matters: Conversation-Based Pricing gives you clarity and control by tying costs directly to conversations, not subjective resolution criteria. As a CX leader, you can confidently budget, prioritize customer experience improvements, and avoid unexpected fees. This predictability and transparency enable you to focus on achieving your financial and service objectives without distractions.

Real-World Comparison

Scenario: Monthly Costs for 1,200 Conversations, 500 Outbound Conversations

*Per resolution pricing based on average cost of Customer Support AI Providers using this metric

Analysis

• Conversation-Based Pricing: At $708, businesses pay a predictable cost for all 1,200 interactions, regardless of how they are resolved. This model eliminates ambiguity and ensures businesses only pay based on the number of conversations initiated.

  
  

• Resolution-Based Pricing (50% Resolved): The cost rises to $994, reflecting charges for 600 resolved issues at $0.99 each, plus $400 for 4 agent seats to handle unresolved interactions. This introduces variability and additional expenses.

  
  

• Resolution-Based Pricing (100% Resolved): Even in the best-case scenario where all 1,200 interactions are resolved by AI, the cost climbs to $1,588— over double the cost of Conversation-Based Pricing.

  
  

Key Takeaway

The comparison breakdown highlights that Conversation-Based Pricing offers clear cost advantages. At $708 for 1,200 interactions, it remains predictable and cost-efficient, regardless of resolution outcomes. In contrast, Resolution-Based Pricing introduces variability, with costs rising to $896 when only 50% of interactions are resolved, and $1,388 even when all interactions are resolved. This demonstrates how Conversation-Based Pricing ensures consistent costs and avoids the added expenses tied to resolution-based models.

Conclusion

Choosing the right pricing model depends on the needs and priorities of your customer service operations. Conversation-Based Pricing stands out for its simplicity, transparency, and ability to align costs directly with interactions, offering predictability that many teams value. Resolution-Based Pricing, while outcome-focused, may suit businesses that prioritize linking costs to specific resolutions, though it can come with greater variability and additional complexities. Similarly, seat-based pricing remains a viable option for some businesses.

Ultimately, understanding the trade-offs between these models is key to making an informed decision that supports both your operational goals and customer experience strategy. Consider what matters most to your team—cost consistency, scalability, or alignment with resolution outcomes—and select the model that best fits your needs.

At Kustomer, we want to be your partner in your AI transformation. Whether you’re exploring Conversation-Based Pricing or looking to consolidate tools and services, we’re here to help guide you through this process. Book a demo today to explore your options, and for more on the benefits of consolidation, you can read this article.