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Software '26: Consumption-led Pricing (view performance)

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Bull / Bear Details has the investment thesis and bull/bear points. Overview is monitoring guidance (hiring, forums, second-order trends, search keywords, Google Trends, datasets).

Bull / Bear Details

Consumption-led software is poised for significant growth driven by the explosion of AI workloads, agentic interactions, and digital transformation, which inher

Thesis

Consumption-led software is poised for significant growth driven by the explosion of AI workloads, agentic interactions, and digital transformation, which inherently scales usage. However, this model faces persistent macroeconomic sensitivity, intense competition from hyperscalers, and increasing infrastructure investment requirements that can pressure margins and introduce volatility. The bull case is more compelling due to AI's structural tailwind.

Bull case

  • Exponential Demand from AI Workloads and Agentic Internet: The proliferation of AI agents, large language models, and machine-to-machine communication is creating an unprecedented surge in data generation, compute cycles, and API calls. Consumption-led software providers, whose revenue directly scales with these measurable units (e.g., data processed, requests, inferences, telemetry), are direct beneficiaries of this structural shift, translating AI adoption into tangible revenue growth.

  • Deepening Platform Integration and Expanding Customer Workloads: As enterprises consolidate their digital operations and AI initiatives onto unified platforms, consumption-based software companies are seeing increased multi-product adoption and expanded usage within existing customer bases. This deep integration makes platforms stickier, drives higher net dollar retention, and allows vendors to capture a larger share of customer IT spend as workloads naturally grow.

  • Broadening Addressable Market through Enterprise and Vertical Expansion: Consumption-led models are increasingly being adopted by large enterprises and across new industry verticals, moving beyond traditional SMB or developer-centric roots. This upmarket shift, coupled with expansion into international markets and specialized solutions (e.g., AI-native clouds, agentic commerce, restaurant tech), significantly expands the total addressable market and provides more stable, larger contracts.

Bear case

  • Inherent Revenue Volatility and Macroeconomic Sensitivity: The direct linkage of revenue to customer usage exposes consumption-led software to significant volatility. Macroeconomic slowdowns, customer cost optimization initiatives, or unpredictable usage patterns can lead to revenue fluctuations, making forecasting challenging and potentially impacting investor confidence, especially for companies with high customer concentration.

  • Intense Competitive Landscape and Pricing Pressure: The market for consumption-based software is highly competitive, with pressure from hyperscalers bundling their own services, open-source alternatives, and aggressive pricing from direct competitors. This intense environment can lead to pricing erosion, particularly for commoditized services, and necessitates continuous innovation and significant R&D investment to maintain differentiation and avoid margin compression.

  • Increasing Infrastructure Investment and Margin Headwinds: Scaling consumption-led platforms, especially to support burgeoning AI workloads, requires substantial and ongoing capital expenditure in data centers, GPUs, and network infrastructure. Rising component costs, carrier fees, and the need for rapid capacity expansion can lead to higher CapEx, pressure gross margins, and temporarily depress free cash flow, impacting profitability metrics.

LLM_Approved · Updated 2026-08-03

Overview

Hiring Trend Watchpoints

High-performing operators in Consumption-led Pricing are aggressively hiring for roles that directly drive or enable consumption, particularly those related to AI and cloud infrastructure. Expect significant demand for AI/ML Engineers, Data Scientists specializing in vector search and LLM observability (SNOW, MDB, DDOG), and Cloud Infrastructure/Platform Engineers focused on scaling and optimizing edge infrastructure (NET, FSLY, DOCN). Enterprise Sales and Solutions Architects are critical for upmarket expansion and complex AI deployments (SNOW, MDB, NET, DDOG, SHOP). Customer Success roles will focus on driving value realization and consumption, not just retention. Geographically, hiring will be concentrated in major tech hubs and leverage remote talent for specialized AI/ML roles. Confirming theme execution: Sustained increase in job postings for 'AI Engineer', 'Vector Database Specialist', 'LLM Ops', 'Edge Compute Architect', 'Enterprise Cloud Sales', and 'Consumption Optimization Specialist'. Warning of deterioration: Broad hiring freezes, a significant shift in customer success roles towards cost optimization rather than expansion, or a noticeable decline in AI/ML-specific hiring.

Forum Watchlist

  • Reddit — r/cloudHigh

    Cloud spending trends, cost optimization strategies, multi-cloud adoption

  • Reddit — r/MachineLearningHigh

    AI workload deployment, vector database performance, LLM integration challenges

  • Reddit — r/sysadminMedium

    Observability tool comparisons, infrastructure scaling issues, performance benchmarks

  • Developer Forum — MongoDB CommunityMedium

    Atlas usage patterns, Vector Search adoption, developer feedback on AI features

  • Industry Forum — Cloudflare DevelopersMedium

    Workers AI usage, edge compute applications, AI agent traffic management

Second Order Trends

1. AI-Native Workloads Driving Exponential Consumption: The shift from AI training to inference and the proliferation of AI agents are creating an 'infrastructure multiplier,' leading to unprecedented data volumes and compute demands, directly benefiting consumption-based models. Companies are explicitly building 'AI-native clouds' (DOCN) and 'agentic control planes' (SNOW) to capture this. 2. Platform Consolidation through AI: AI capabilities are becoming a key differentiator for platform consolidation. Customers are choosing unified platforms that offer integrated AI (vector search, LLM observability, AI agents) to replace multiple point solutions, driving larger deals and stickiness (MDB, DDOG, SNOW). 3. Monetization of 'Work Done' vs. Idle Capacity: Companies like Cloudflare (NET) are emphasizing efficiency in AI inference, monetizing 'work done' rather than just renting idle GPUs, which could become a competitive advantage against traditional hyperscalers. This points to a future where efficient, multi-tenant AI infrastructure is highly valued. 4. Hybrid Cloud & On-Prem Resurgence (AI-driven): For regulated industries or specific data sovereignty needs, the importance of hybrid and on-prem deployments is being renewed, with AI workloads also driving demand in these environments (MDB). This expands the addressable market for flexible consumption models. 5. Supply Chain & CapEx as a Differentiator/Headwind: The ability to secure and efficiently deploy data center capacity and components (especially GPUs/memory) is becoming a critical factor. For some (DOCN, NET), aggressive CapEx is a strategic investment; for others (TOST, FSLY), rising component costs are a margin headwind. This highlights the physical constraints underlying digital consumption. 6. 'Pay Per Crawl' and IP Monetization in the Agentic Web: As AI agents scrape the internet, new monetization models like Cloudflare's 'Pay Per Crawl' (NET) are emerging to help publishers monetize their IP, shifting revenue streams from traditional ad-driven traffic to direct AI interaction.

Search Keywords Brand Product

  • Snowflake Data Cloud
  • Snowflake Intelligence
  • Cortex Code
  • Datadog Observability
  • Datadog LLM Observability
  • MongoDB Atlas
  • MongoDB Vector Search
  • Cloudflare Workers
  • Cloudflare AI Gateway
  • Shopify Merchant Solutions
  • Shopify Universal Commerce Protocol
  • Toast POS
  • Toast Payments
  • Twilio Flex
  • Twilio Voice AI
  • Dynatrace Platform
  • Elastic Cloud
  • JFrog Artifactory
  • Klaviyo Marketing Automation
  • Amplitude Analytics
  • Braze Customer Engagement
  • DigitalOcean Droplets
  • Fastly Edge Cloud
  • Fastly Security

Search Keywords Policy Regulatory

  • FedRAMP High certification
  • data sovereignty laws
  • AI content rights
  • carrier pass-through fees
  • memory chip tariffs

Search Keywords Event Phrases

  • Shopify Unite
  • Twilio SIGNAL
  • AWS re:Invent
  • Google Cloud Next
  • Microsoft Build

Google Trend Product Category Intent

• cloud cost optimization • AI inference platforms • vector database solutions • LLM monitoring • serverless compute pricing • usage-based billing software • e-commerce platform fees • restaurant payment processing

Google Trend Consumer Intent

• AI agent development • data consumption trends • cloud spending trends • developer tools AI • digital transformation spending

Google Trend Macro Policy Terms

• cloud regulation • AI data privacy • digital services tax

Top datasets to track

1. Public Cloud Spending Forecasts Type: Industry Data · Provider: Gartner, IDC, Synergy Research Group Cadence: Quarterly/Annually Why it matters: Indicates overall market growth for cloud services, directly impacting consumption-led software. Suggested query: Gartner cloud spending forecast 2026 Confidence: High

2. Enterprise AI Adoption Rates Type: Industry Data · Provider: Deloitte, IBM, McKinsey AI surveys Cadence: Annually/Bi-annually Why it matters: Tracks the shift from AI pilots to production, which drives consumption for data platforms, observability, and edge compute. Suggested query: Enterprise AI adoption survey 2026 Confidence: High

3. Thinknum: Job Postings for Key AI/Cloud Roles Type: Alternative Data · Provider: Thinknum Cadence: Weekly/Monthly Why it matters: Leading indicator of company investment in AI, cloud infrastructure, and enterprise sales, signaling future consumption drivers. Suggested query: Job postings for 'Vector Search Engineer' OR 'LLM Ops' OR 'Cloud FinOps' for SNOW, MDB, DDOG, NET Confidence: High

4. US Census Bureau Retail E-commerce Sales Type: Economic Data · Provider: US Census Bureau Cadence: Quarterly Why it matters: Provides macro context for Shopify's Merchant Solutions and overall digital commerce activity. Suggested query: US retail e-commerce sales Q2 2026 Confidence: High

5. Consumer Edge / Similarweb: Enterprise Software Spend Data Type: Alternative Data · Provider: Consumer Edge, Similarweb Cadence: Monthly/Quarterly Why it matters: Direct insight into customer spending patterns on consumption-based software, including potential cost optimization or expansion. Suggested query: Enterprise spend on Datadog Confidence: Medium

Industry Publications
[{"name": "The New Stack", "domain": "thenewstack.io", "why": "Cloud-native, DevOps, AI infrastructure, developer tools"},{"name": "TechCrunch", "domain": "techcrunch.com", "why": "Startup and tech innovation, funding rounds for AI/cloud"},{"name": "ZDNet", "domain": "zdnet.com", "why": "Enterprise tech, cloud, security, digital transformation"},{"name": "Gartner Blogs", "domain": "blogs.gartner.com", "why": "Analyst insights on cloud spending, AI adoption, observability"},{"name": "Retail Dive", "domain": "retaildive.com", "why": "E-commerce, retail tech, POS systems, merchant solutions"}]

LLM_Approved · Updated 2026-08-03

Key Metrics3 rows
MetricCadenceWhat It SignalsUpdate Source
Net Revenue Retention (NRR) Rate for Consumption-Led SoftwareAnnuallySustained NRR above 120% indicates strong customer value, expanding usage, and successful monetization of consumption, signaling a bullish trend. Declining NRR is bearish.LLM_Approved
Percentage of Total Cloud Software Revenue from Usage-Based ModelsAnnuallyAn increasing percentage indicates a growing adoption and preference for consumption-led pricing in the broader cloud software market, signaling a bullish trend. Stagnation or decline is bearish.LLM_Approved
Global Cloud Data Storage and Compute Consumption Growth (Year-over-Year)Annually (for forecasts), Quarterly (for provider-specific data)Accelerating growth in underlying cloud resource consumption directly fuels revenue for consumption-led software, indicating strong demand and a bullish outlook. Deceleration is bearish.LLM_Approved

Bessemer Venture Partners State of Cloud Report (aggregated industry data) · Updated 2026-08-03

Upcoming Catalysts23 rows
CatalystEstimated TimingEstimated Date StartEstimated Date EndWhy It MattersTicker Or Theme SpecificSource TypesContributing TickersMention CountBase ScoreSource WeightSpecificity WeightMacro BridgeMacro Bridge MultiplierTheme ScoreDate AggregatedManual OverrideBridge Mention CountTheme Base ScoreTheme Importance ScoreCatalyst SourceCatalyst IDTranscript DateSource Type
Q2 2026 earnings season for consumption-led software companies, providing critical updates on product revenue growth, AI monetization, and forward guidance.August 20262026-08-012026-09-05Earnings reports offer the most current and comprehensive data on customer consumption patterns, the financial impact of AI adoption, and management's outlook, directly influencing investor sentiment and valuations across the entire theme.Themetheme_composerSNOW, DDOG, MDB, NET, DOCN, TWLO, TOST, SHOP, FSLY, ESTC, FROG, KVYO, AMPL, BRZE149.12571.181.01.01076.82942026-08-03False12.8496336.2475Theme composer
Accelerated adoption and monetization of AI workloads by enterprises, driving increased consumption of compute, storage, and platform services across various software vendors.Throughout Q3 2026, with key updates in August/September 2026 earnings reports.2026-08-012026-09-30The shift of AI initiatives from prototyping to production directly translates into higher usage volumes for consumption-led software platforms, impacting revenue growth for a broad range of constituent tickers. This validates the core thesis of the theme.Themetheme_composerSNOW, DDOG, MDB, NET, DOCN, TWLO, ESTC, FROG, KVYO, AMPL, BRZE119.12091.181.01.01076.26162026-08-03False12.207260.4248Theme composer
Launch and successful monetization of new agentic AI products and features, such as dedicated drive-thru solutions, AI crawl control, and advanced voice AI capabilities.Throughout 2026, with updates in Q2 earnings (August 2026) and company product announcements.2026-08-012026-12-31Specific AI product innovations demonstrate the ability of companies to capture new value from the evolving AI landscape, directly translating into increased usage and higher average revenue per user (ARPU) as customers adopt these advanced, consumption-based features.Themetheme_composerTOST, SHOP, NET, TWLO40.00821.180.921.00.8862026-08-03False10.672272.9738Theme composer
Expansion of consumption-led software platforms into the U.S. federal government and other regulated industries, driven by certifications like FedRAMP High and strategic acquisitions.Throughout Q3 2026, with potential contract announcements and updates in Q2 earnings.2026-08-012026-09-30Entry into the public sector and regulated industries opens up a large, sticky, and often higher-value addressable market, providing new avenues for consumption growth and validating the security posture of these platforms.Themetheme_composerDDOG, MDB29.24071.181.0Regulatory/Policy, Economic1.6881840.05572026-08-03False10.228645.5207Theme composer
Timely ramp-up and utilization of expanded data center capacity and infrastructure investments, particularly for AI inference workloads.Ongoing throughout 2026 and 2027, with initial ramp and commentary expected in Q2 2026 earnings (August 2026).2026-08-012027-12-31For infrastructure-heavy consumption models, meeting the surging demand for AI inference and other high-volume workloads requires significant and timely capacity expansion. Successful utilization of this infrastructure is critical for achieving revenue growth targets and maintaining profitability.Themetheme_composerDOCN, FSLY, NET30.00311.180.851.00.31022026-08-03False10.427442.8641Theme composer
Achievement of DigitalOcean's projected revenue growth rates: 21% for full-year 2026, an exit rate of 25%+ by Q4 2026, and 30% for full-year 2027.21% revenue growth for the full year 2026 with an exit growth rate of 25% plus by Q4 and reaching 30% growth in 20272026-01-012027-12-31These targets reflect the success of the Agentic Inference Cloud strategy and upmarket shift. Meeting or exceeding them would be bullish, validating the company's growth trajectory and investment strategy, while missing them would be bearish.TickerDOCN (ticker)DOCN_1d0731cd2026-02-24earnings_transcript
Successful activation and revenue ramp-up of 31 megawatts of new data center capacity across three new facilities.The smallest of our 3 new facilities will start ramping revenue in the second quarter. The remaining [indiscernible] start ramping revenue in the second half of 2026.2026-04-012026-12-31This capacity is essential to meet the strong demand from AI native customers and drive the projected revenue acceleration. Successful deployment and utilization are bullish, while delays or underutilization could negatively impact growth and margins.TickerDOCN (ticker)DOCN_e5fe7f862026-02-24earnings_transcript
DigitalOcean will repurchase or redeem the remaining $312 million balance of its outstanding 2026 convertible notes.before or at the maturity in December of '26.2026-02-252026-12-31This action will resolve a significant near-term financial obligation, strengthening the balance sheet and reducing financial risk. Successful resolution is bullish for financial stability and investor confidence.TickerDOCN (ticker)DOCN_60b970b52026-02-24earnings_transcript
Release of new product innovations, including machine-friendly APIs, auto-scaling, and auto-sharding capabilities, specifically designed to enhance MongoDB's appeal and functionality for AI agents.throughout this coming year2026-03-022027-01-31These innovations are critical for MongoDB to solidify its position as the preferred data platform for AI and agentic applications, potentially driving increased adoption and consumption from AI-native companies and enterprises building AI workloads.TickerMDB (ticker)MDB_185764de2026-03-02earnings_transcript
Acceleration of MongoDB's partner growth engine, focusing on deepening relationships with hyperscalers, strategic system integrators for modernization efforts, and key players in the AI native ecosystem.During the upcoming year2026-03-022027-01-31A more robust partner ecosystem can significantly expand MongoDB's reach, accelerate customer acquisition, and drive adoption of its platform for both core and AI workloads, impacting revenue growth and market share.TickerMDB (ticker)MDB_a20b25252026-03-02earnings_transcript
Achievement of feature parity between MongoDB Enterprise Advanced (EA) and Atlas.throughout fiscal '272026-03-022027-01-31Bringing EA to feature parity with Atlas can enhance its competitiveness, especially in regulated industries and for customers preferring on-premise deployments, potentially driving stronger growth and larger multi-year deals for the EA business.TickerMDB (ticker)MDB_258e54732026-03-02earnings_transcript
Material revenue contribution from widespread production deployment of customer-facing agentic AI applications by large enterprises.still early, Matt, just to be clear, because the security governance, observability, there are many, many aspects to the agents and what kind of outcomes they deliver if it is agents at scale. But we feel that we are ready and just yesterday, Matt, I was with a Fortune 25 firm. And when we outlined what we already have, where MongoDB can not only act as an operational data layer, but can also act as a long-term memory and some of the things that we are building right now they got really, really excited as they think about rolling out production agents at scale. So early but I'm seeing very encouraging signs, and we are ready.2026-08-012027-01-31This would significantly accelerate Atlas revenue growth beyond current core workload drivers, validating MongoDB's strategic positioning as the data platform for the AI era and positively impacting valuation and investor sentiment.ThemeMDB (ticker)MDB_4850795d2026-05-28earnings_transcript
MongoDB achieving FedRAMP High certification for its U.S. federal offerings.this year2026-06-012027-01-31This certification will allow MongoDB to properly sell and serve U.S. federal customers, unlocking a significant new market (large TAM) and driving increased revenue from this vertical.TickerMDB (ticker)MDB_28ffb3cc2026-05-28earnings_transcript
EA and other revenue performance in the second half of fiscal '27, with the potential to exceed or fall short of the 'approximately flat' projection due to the unpredictable timing of large multiyear deals.second half of the year2026-08-012027-01-31Exceeding the 'approximately flat' projection would signal stronger-than-expected demand for on-premise/hybrid deployments and large multiyear deals, positively impacting total revenue and investor sentiment. Falling short would be bearish.TickerMDB (ticker)MDB_6a191a5a2026-05-28earnings_transcript
Successful refinement and execution of MongoDB's go-to-market strategy to effectively intercept and scale with AI-native companies, moving them from self-serve to managed accounts.work in progress2026-05-012027-01-31A successful strategy would accelerate customer acquisition and revenue growth from the rapidly expanding AI-native segment, validating MongoDB's product fit and go-to-market efficiency for this critical customer cohort.TickerMDB (ticker)MDB_ac3a311f2026-05-28earnings_transcript
Completion of Snowflake's intended acquisition of Natoma.intended acquisition of Natoma2026-06-012026-09-30This acquisition is expected to extend Snowflake's agentic control plane into everyday applications, enhancing AI governance and potentially driving new growth opportunities and customer adoption, impacting product capabilities and competitive positioning.TickerSNOW (ticker)SNOW_02751c2d2026-05-27earnings_transcript
Successful implementation and adoption of AI cost governance features (e.g., cost limits, token restrictions) for Snowflake Intelligence and Cortex Code.we are creating the controls that one needs in order to keep costs manageable as things continue expanding.2026-05-012027-01-31Effective cost controls are crucial to mitigate 'sticker shock' and encourage broader enterprise adoption of AI products, directly influencing customer spending, retention, and ultimately, Snowflake's revenue and investor sentiment.TickerSNOW (ticker)SNOW_9276e08c2026-05-27earnings_transcript
Snowflake's ability to achieve and maintain its guided non-GAAP product gross margin of 75% for fiscal year 2027, despite the lower gross margin profile of AI products.for FY '272026-02-012027-01-31Successfully maintaining gross margins would demonstrate strong operational efficiency and cost management, positively impacting profitability and investor confidence. Failure could lead to margin pressure and negative investor sentiment.TickerSNOW (ticker)SNOW_13ac63802026-05-27earnings_transcript
Twilio's actual reported revenue, organic revenue, non-GAAP income from operations, gross profit dollar growth, and free cash flow for the full year 2026 compared to its guidance.Full year 20262026-01-012026-12-31Achieving or exceeding these financial targets, especially the double-digit organic revenue growth orientation and strong profitability, will significantly impact valuation and investor sentiment.TickerTWLO (ticker)TWLO_fc7eecb62026-02-12earnings_transcript
Continued acceleration in the adoption and volume of RCS messaging, particularly for marketing-oriented use cases and small businesses.gaining traction2026-04-262027-04-26Strong RCS growth could drive messaging revenue, enhance Twilio's competitive differentiation with rich messaging experiences, and improve customer engagement, positively impacting sentiment.TickerTWLO (ticker)TWLO_dcc5d7c32026-02-12earnings_transcript
Twilio's ability to successfully execute its AI innovation roadmap, deliver memory-driven orchestration and agentic interactions, and establish itself as a foundational infrastructure layer for AI agents.today and in the future2026-04-262028-12-31This is crucial for long-term revenue growth, competitive advantage in the AI era, and solidifying its position within the 'Agentic Utilities' and 'AI-Ready Design' themes, driving significant valuation upside.TickerTWLO (ticker)TWLO_e2738c932026-02-12earnings_transcript
Twilio providing its complete full year 2027 financial guidance during its Q4 2026 earnings call.Q4 '26 earnings call next year2027-01-012027-02-28This guidance will set market expectations for Twilio's future growth and profitability, influencing long-term valuation and investor sentiment.TickerTWLO (ticker)TWLO_b293e1d52026-02-12earnings_transcript
Expiration of $4.5 billion share repurchase authorizationthrough March 20272027-03-012027-03-01With $1.3 billion remaining, the pace of buybacks impacts share count and reflects management's view on the stock's valuation and capital allocation priorities.TickerSNOW (ticker)SNOW_e0cf25352025-12-03

LLM_Approved · Updated 2026-08-03

NotesTable

Market Commentary

DateTypeCommentDetailSentimentTickers
2026-08-03Theme Refresh SynthesisThe Software '26: Consumption-led Pricing theme is strongly validated by AI's proliferation. AI workloads are driving increased usage across data, observability, and edge platforms, accelerating revenue for many constituents. This amplifies the usage-based model, though consumption volatility and AI infrastructure costs remain key considerations.

Market Commentary

Positive with caveatsSNOW, DDOG, MDB, NET, DOCN, TWLO, SHOP, TOST, FSLY

LLM_Approved · Updated 2026-08-03

Constituents

  • DDOGT13.5%
    — Datadog, Inc.
  • DOCNT2
    — DigitalOcean Holdings, Inc.
  • SHOPT2
    — Shopify Inc.
  • FSLYT3
    — Fastly, Inc.
  • MDBT3
    — MongoDB, Inc.
  • NETT3
    — Cloudflare, Inc.
  • SNOWT3
    — Snowflake Inc.
  • TOSTT3
    — Toast, Inc.
  • TWLOT3
    — Twilio Inc.
  • DTT2
    · no notes yet
  • AMPLT3
    · no notes yet
  • BRZET3
    · no notes yet
  • ESTCT3
    · no notes yet
  • FROGT3
    · no notes yet
  • KVYOT3
    · no notes yet