ASAN

• Business Health & Retention: Overall Net Revenue Retention (NRR) improved to 97%, driven by strength in core (98%) and enterprise ($100k+, 98%) cohorts. In-quarter NRR has improved for five consecutive quarters.
• AI Product Momentum: AI Studio and AI Teammates drove approximately 25% of net new Annual Recurring Revenue (ARR), surpassing the full-year target. Over 25% of customers spending over $100,000 have adopted AI products.
• Agentic Work Management (AWM): Launching mid-September, AWM integrates AI Teammates, AI Studio, and Asana Dash into all paid tiers without changing pricing. This aims to embed AI directly into workflows rather than as separate purchases.
• New Product Lines: Introduced Asana Client Management, Service Management, and Command. These are built on the existing 'work graph' platform, allowing shared context and governance across human and agent teams.
• Operational Efficiency: R&D expenses were $50.7 million (23% of revenue). The company is leveraging AI to maintain robust product development without commensurate headcount increases. Sales and Marketing spend remains relatively flat despite upmarket focus.

• Q3 FY2027 Revenue: Expected between $217 million and $219 million (8%-9% YoY growth), including a $700,000 headwind from AWM packaging transition.
• Full Year FY2027 Revenue: Expected between $858.5 million and $863.5 million (approx. 9% YoY growth at midpoint).
• Operating Margin: Full-year non-GAAP operating margin expected to be approximately 10% ($84.5-$86.5 million operating income).
• Key Headwinds: Includes ~150 basis points of gross margin pressure in H2 due to lower-margin AI consumption costs and a ~$1.2 million revenue timing impact from shifting to consumption-based recognition.
• PLG Dynamics: Self-serve/PLG trends continue to create revenue growth headwinds (~100 bps in Q3, ~150 bps in Q4), though management expects this to normalize in FY2028.
• AI ARR Target: Revised full-year expectation that AI products will represent ~20% of Net New ARR (up from 15%).
• New Products: No significant revenue contribution expected from Client Management, Service Management, or Command in FY2027; these are viewed as growth drivers for FY2028.

The company reported total revenue of $216.4 million, representing a 10% year-over-year increase and exceeding the high end of guidance. Core customers (spending $5,000+ annually) generated 77% of Q2 revenue, with their revenue growing 11% year-over-year. The Technology sector returned to year-over-year growth for a second consecutive quarter. Non-Technology sectors continued to outpace overall company growth, contributing new logos across telecommunications, insurance, professional services, legal, and luxury retail. The United States market accelerated to double-digit growth (10% YoY), while International markets saw notable wins in EMEA.

• PLG/Self-Serve Decline: Continued weakness in the Product-Led Growth motion, characterized by low-quality leads ('tire kickers') and poor retention in the sub-$5,000 cohort, drags down consolidated NRR.
• Gross Margin Pressure: Transition to AI consumption-based models currently carries lower contribution margins than seat-based subscriptions, creating temporary gross margin compression.
• Revenue Recognition Variability: Shifting to consumption-based billing introduces variability in the timing of revenue recognition, potentially complicating quarterly forecasts.
• Execution Risk on New Products: Success depends on effective go-to-market execution for new verticals (Client, Service, Command) and convincing enterprises to consolidate spend onto the Asana platform against specialized competitors.

Q: How does Agentic Work Management (AWM) solve the 'agent discovery' problem? / A: Dan Rogers explained that AWM eliminates the need for users to manually search for agents. Instead, 'Dash' (the AI chief of staff) analyzes user inputs and work graph history to suggest relevant pre-built teammates automatically. This ensures agents surface based on the task at hand, reducing friction and embedding AI directly into daily workflows rather than requiring separate discovery efforts.

Q: What is driving the widening gap between Company-wide NRR (97%) and Core NRR (98%)? / A: Aziz Megji attributed the differential to the sub-$5,000 customer cohort, which is concentrated in self-serve channels and often falls outside the Ideal Customer Profile (ICP). While core and enterprise retention are strong (98%), weaker retention in the small-business segment pulls down the consolidated metric. Management is focusing acquisition spend on higher-fit ICPs to improve this mix.

Q: What is Asana's competitive advantage ('right to win') in new verticals like Service and Client Management? / A: Rogers emphasized that Asana is not building point solutions but extending its 'work graph' platform. Because Asana already holds the context, history, and governance of enterprise workflows, it can offer instant productivity via AI routing and resolution. This allows Asana to resolve tickets or manage client projects natively within the same system, avoiding data silos found in disconnected tools.

Q: How does the shift to consumption-based pricing affect forecasting and customer economics? / A: Management clarified that the shift creates a $1.2 million revenue timing headwind in H2 due to recognizing consumption revenue as requests are used rather than ratably. However, this does not change ARR, bookings, or cash flow. Forecasting may become more variable initially, but management believes the 'request' unit offers better predictability and value alignment for customers compared to token-based models.