Zendesk: Will Zendesk's Resolutions-Driven Strategy Resonate With Customers?

Analyst(s): Keith Kirkpatrick Publication Date: April 1, 2025 What is Covered in this Article: Zendesk Relate 2025 gathered 2,000+ participants and introduced the Zendesk Resolution Platform, emphasizing AI-driven customer issue resolution. The Resolution Platform integrates AI agents, Copilot enhancements, Generative Search, Knowledge Builder, Action Builder, and AI governance tools. Zendesk announced the Employee Service Suite for internal support, leveraging HRIS integrations and task automation. Acquisition of Local Measure strengthens Zendesk's voice and contact center capabilities with AWS-powered solutions. Zendesk shifts to outcome-based pricing for AI agents, starting at $1.50 per resolution, aiming to align costs with measurable customer value. The News: Zendesk Relate 2025 brought together more than 2,000 participants across Zendesk's customer and partner ecosystem and marked the announcement of the company's Zendesk Resolution Platform, an AI-powered customer experience engine designed to prioritize the efficient resolution of customer issues. The Zendesk Resolution Platform is built on five key components: new AI agents and upgrades to the Copilot feature; new Generative Search and Knowledge Builder features built on the company's Knowledge Graph; Action Builder & App Builder functions; AI reasoning and governance controls; and new measurement and insight functions. AI Agents & Copilot Upgrades: The AI Agent Builder enables semantic language to describe business processes and flows to create agentic workflows. Meanwhile, the Copilot features allow agents to operate inside tools like Slack and Jira, pulling from internal knowledge to offer rich, context-aware help without coding. Knowledge Graph & Generative Search: With Generative Search capabilities, Zendesk's Knowledge Graph has been enhanced. This enables users or AI agents to access over 50,000 active knowledge bases with source references intact. The Knowledge Builder function enables the creation of help articles using historical ticket data and incorporates translation functionality to multiple languages. Action Builder & App Builder: Action Builder is designed to connect workflows across platforms like Salesforce and Microsoft Teams using drag-and-drop tools. App Builder allows custom app creation within Zendesk using natural language prompts. AI Governance & Reasoning Controls: The Zendesk Resolution Platform incorporates new tools designed to provide explainability and granular controls over agent behavior and actions, engendering greater transparency and trust in AI agents. Measurement & Insights: These tools are designed to ensure organizations can assess the Resolution Platform's performance. They incorporate AI to review 100% of interactions and highlight areas for improvement, whether from human agents or bots. In addition, the Insights Hub is designed to leverage the platform's data to provide smart recommendations that drive CX improvements. Serving Employees and Assets With the Zendesk Platform In addition to the Resolution Platform, Zendesk also announced Employee Service Suite, a n offering to support internal teams like HR and IT. Built on the same platform as Zendesk's customer-facing offering, it includes HRIS integrations, service catalogs, and task automation. Later in the year, Zendesk also expects to announce its IT Asset Management offering, letting customers track and manage staff equipment, licenses, and tools all within Zendesk. Leveraging Local Measure to Strengthen Voice and Contact Center Capabilities Zendesk also strengthened its voice and contact center capabilities, highlighting the acquisition of Local Measure, which is expected to close this year. Powered by AWS, Zendesk for Contact Center is positioned as an alternative to traditional CCaaS platforms, leveraging Zendesk's data, insights, and automation to enable better CX. Will Zendesk's Resolutions-Driven Strategy Resonate With Customers? Analyst Take: Like most of its competitors, Zendesk is banking on generative AI and agentic AI to make the company's offerings more powerful, efficient, and easy to use. The release of its new Resolution Platform is evidence that the company is fully leaning into AI as a core enabling technology to drive successful resolutions, whether through a self-service AI agentic strategy or as an assistive technology designed to enable and empower human customer support agents. The emphasis on driving resolutions dovetails with the company's goal of transitioning its customer base from a traditional seat license-based pricing model to an outcome-based model. Under this approach, customers will only be charged if the company's technology can resolve a customer's issue without requiring a human to intervene. Linking Cost to Value In September 2024, Zendesk announced plans to adopt an outcome-based pricing model for its AI agents, marking a significant shift from traditional human-centric pricing methods. This move reflects the growing role of AI agents in customer experience (CX), sales, and marketing operations. Outcome-based pricing benefits vendors and customers by guaranteeing value and aligning costs with results. Under this model, customers would only pay for the successful outcome of an interaction, with pricing starting at $1.50 per resolution and declining as volume increases. This approach more transparently links the cost of AI agents with real-world business value. It ensures the vendor's solution stays current and aligned with the customer's business processes and needs. Outcome-based pricing also eliminates the perception that the vendor is stimulating the usage of AI agents to drive up its fees, regardless of whether the technology is driving improvement to the business. This may be the perception of consumption-based pricing. Under that model, customers may be paying for AI to handle interactions that are unable to be resolved, Challenges with Outcome-based Pricing While outcome-based pricing appears to be a solid way for Zendesk to differentiate its offering from competitors and clearly link the cost of its services with real-world value, it will likely need to provide additional clarity on a few considerations to convince customers that the pricing model makes sense. Clear parameters on what constitutes a resolved interaction will be required. The parameters are fairly clear on simple tickets, such as completing a product return. However, for multi-step processes, concise guardrails around whether customers are being charged for each step in a process or the overall outcome will need to be defined to help customers assess and predict potential costs. Another key consideration is ensuring that customers understand the value of the $1.50 per resolution pricing. Resolving a simple task for $1.50 may be appealing to the customer. Still, if a task is especially complex, Zendesk may want to adjust pricing or consider other options (such as converting that $1.50 per interaction into a tokenized value). This would enable them to recapture the cost of resolving more complex interactions more easily and transparently without taking a financial hit for incurring compute costs that are not recaptured in a catch-all, per-resolution fee. Zendesk will also need to provide some mechanism for helping customers manage their budgets for AI agents, particularly as these deployments roll out without any historical data around usage. Customers are used to the predictability of seat license-based pricing. They will need to have some way of ensuring that utilization does not exceed certain financial thresholds, even if a greater number of resolutions does reduce costs. Ultimately, Zendesk is taking a bold step into a new world where software can increasingly have a directly measurable impact on business performance, and for that, they should be commended. As the company continues to roll out new features and pricing details, I suspect other vendors will be closely watching to see the impact on current customers and prospects. You can read the full press release detailing Zendesk's announcements on the company's website . Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article. Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole. Other insights from The Futurum Group: Zendesk to Acquire Local Measure to Strengthen Its AI-Driven Contact Center Solutions How AI is Transforming the Economics of Customer Service Will Outcomes-Based Pricing Become the Preferred Pricing Model for AI Agents in 2025?