{
  "slug": "martech-stack-benchmarks",
  "title": "Martech Stack Benchmarks 2026: Utilization, Integration and AI Overlap",
  "generatedAt": "2026-07-14T00:01:00Z",
  "dataYearsCovered": [
    2024,
    2025,
    2026
  ],
  "lastVerified": "2026-07-14",
  "methodology": "Original editorial compilation of neutral factual paraphrases from five public evidence surfaces. Martech survey, product-landscape, and enterprise SaaS evidence remain separate. Missing-N percentages are supporting-only; enterprise SaaS figures are comparison-only. No blended utilization, unused-license, waste, savings, or revenue-leakage estimate is calculated.",
  "sources": [
    {
      "source_id": "gartner-2025",
      "source_domain": "gartner.com",
      "source_url": "https://www.gartner.com/en/marketing/topics/marketing-technology",
      "source_title": "Maximize ROI With Marketing Technology (Martech)",
      "source_quality": "official_survey_summary",
      "evidence_type": "official public summary of the 2025 Gartner Marketing Technology Survey",
      "population": "marketing organizations in Gartner's 2025 survey; respondent count not disclosed on the public page",
      "geography": "not disclosed on the public page",
      "period": "2025 survey; public page accessed July 14, 2026",
      "methodology": "Gartner's public topic page summarizes selected survey results and recommendations but does not expose the full sample or fieldwork details.",
      "caveat": "Supporting evidence only. The public page does not disclose N. Martech utilization is not the same measure as unused licenses or wasted spend."
    },
    {
      "source_id": "state-martech-2026",
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/state-of-martech-2026.pdf",
      "source_title": "State of Martech 2026",
      "source_quality": "primary_landscape_and_survey",
      "evidence_type": "product-landscape census methodology plus primary survey",
      "population": "15,505 mapped martech products; separate February 2026 survey of 208 marketing and marketing-operations leaders across about 70 AI use cases",
      "geography": "survey geography is not fully disclosed in the public report",
      "period": "product landscape and survey published May 5, 2026; AI category comparisons use the report's 2024 and 2026 surveys",
      "methodology": "Chiefmartec and MartechTribe maintained the product landscape and surveyed 208 leaders. The sample was 40% VP or above, 36% technology companies, 21% professional services, 61% pure B2B, and explicitly described as tech-forward/top-quartile.",
      "caveat": "The product map is not a count of purchases or active enterprise stacks. The N=208 survey is intentionally tech-forward and multi-select where stated, so it is not market-representative."
    },
    {
      "source_id": "martech-for-2026",
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims."
    },
    {
      "source_id": "flexera-2026",
      "source_domain": "flexera.com",
      "source_url": "https://resources.flexera.com/web/pdf/Flexera-State-of-IT-Asset-Management-Report-2026.pdf",
      "source_title": "Flexera 2026 State of ITAM Report",
      "source_quality": "primary_independent_panel_survey",
      "evidence_type": "global survey of IT asset-management professionals",
      "population": "512 professionals with IT asset-management responsibilities sourced from an independently maintained and vetted panel",
      "geography": "worldwide across industries and organizational contexts",
      "period": "fielded in early 2026",
      "methodology": "Flexera surveyed 512 ITAM professionals and rounded published percentages to whole numbers. The report is licensed CC BY 4.0.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Waste estimates are respondent estimates and cannot be converted into a marketing revenue-loss figure."
    },
    {
      "source_id": "zylo-2026",
      "source_domain": "zylo.com",
      "source_url": "https://zylo.com/2026-saas-management-index",
      "source_title": "2026 SaaS Management Index",
      "source_quality": "first_party_platform_telemetry",
      "evidence_type": "enterprise SaaS-management telemetry plus a separate IT-leader survey for cost-shock claims",
      "population": "telemetry covering 40M+ SaaS licenses and $75B+ in discovered and categorized spend; cost-shock questions use a separate survey of 218 IT leaders",
      "geography": "not disclosed on the public report page",
      "period": "2026 edition with year-over-year comparisons and nine years of underlying spend, license, and usage data",
      "methodology": "Zylo aggregates observed customer portfolio, license, usage, and spend data. Its public newsroom release separately identifies N=218 for unexpected-cost questions.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Zylo customer telemetry is not a probability sample of all organizations and must not be converted into a martech waste or revenue-leakage rate."
    }
  ],
  "rows": [
    {
      "claim_id": "MTS-001",
      "slug": "martech-stack-benchmarks",
      "metric_category": "utilization",
      "figure": "49%",
      "claim": "Gartner's public 2025 summary reports martech utilization at 49%.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "gartner.com",
      "source_url": "https://www.gartner.com/en/marketing/topics/marketing-technology",
      "source_title": "Maximize ROI With Marketing Technology (Martech)",
      "source_section": "Build trust and safeguard your budget with a fully utilized martech stack",
      "source_quality": "official_survey_summary",
      "evidence_type": "official public summary of the 2025 Gartner Marketing Technology Survey",
      "population": "marketing organizations in Gartner's 2025 survey; respondent count not disclosed on the public page",
      "geography": "not disclosed on the public page",
      "period": "2025 survey; public page accessed July 14, 2026",
      "methodology": "Gartner's public topic page summarizes selected survey results and recommendations but does not expose the full sample or fieldwork details.",
      "caveat": "Supporting evidence only. The public page does not disclose N. Martech utilization is not the same measure as unused licenses or wasted spend. The page alternates between utilization and tools actively used; quote the 49% figure only with the missing-N limitation adjacent.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-002",
      "slug": "martech-stack-benchmarks",
      "metric_category": "performance",
      "figure": "15%",
      "claim": "Gartner's public summary says 15% of organizations qualified as martech high performers that met strategic goals and demonstrated positive ROI.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "gartner.com",
      "source_url": "https://www.gartner.com/en/marketing/topics/marketing-technology",
      "source_title": "Maximize ROI With Marketing Technology (Martech)",
      "source_section": "Align your martech strategy with business goals to drive performance",
      "source_quality": "official_survey_summary",
      "evidence_type": "official public summary of the 2025 Gartner Marketing Technology Survey",
      "population": "marketing organizations in Gartner's 2025 survey; respondent count not disclosed on the public page",
      "geography": "not disclosed on the public page",
      "period": "2025 survey; public page accessed July 14, 2026",
      "methodology": "Gartner's public topic page summarizes selected survey results and recommendations but does not expose the full sample or fieldwork details.",
      "caveat": "Supporting evidence only. The public page does not disclose N. Martech utilization is not the same measure as unused licenses or wasted spend.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-003",
      "slug": "martech-stack-benchmarks",
      "metric_category": "budget",
      "figure": "nearly 22%",
      "claim": "Gartner's public summary says martech accounted for nearly 22% of total marketing spend.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "gartner.com",
      "source_url": "https://www.gartner.com/en/marketing/topics/marketing-technology",
      "source_title": "Maximize ROI With Marketing Technology (Martech)",
      "source_section": "Martech audits are essential to improve outcomes and optimize costs",
      "source_quality": "official_survey_summary",
      "evidence_type": "official public summary of the 2025 Gartner Marketing Technology Survey",
      "population": "marketing organizations in Gartner's 2025 survey; respondent count not disclosed on the public page",
      "geography": "not disclosed on the public page",
      "period": "2025 survey; public page accessed July 14, 2026",
      "methodology": "Gartner's public topic page summarizes selected survey results and recommendations but does not expose the full sample or fieldwork details.",
      "caveat": "Supporting evidence only. The public page does not disclose N. Martech utilization is not the same measure as unused licenses or wasted spend.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-004",
      "slug": "martech-stack-benchmarks",
      "metric_category": "channel_complexity",
      "figure": "9 channels; 20% adding new ones",
      "claim": "Gartner's public summary says CMOs oversaw nine marketing channels on average and 20% were already adopting new channels.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "gartner.com",
      "source_url": "https://www.gartner.com/en/marketing/topics/marketing-technology",
      "source_title": "Maximize ROI With Marketing Technology (Martech)",
      "source_section": "Align your martech strategy with business goals to drive performance",
      "source_quality": "official_survey_summary",
      "evidence_type": "official public summary of the 2025 Gartner Marketing Technology Survey",
      "population": "marketing organizations in Gartner's 2025 survey; respondent count not disclosed on the public page",
      "geography": "not disclosed on the public page",
      "period": "2025 survey; public page accessed July 14, 2026",
      "methodology": "Gartner's public topic page summarizes selected survey results and recommendations but does not expose the full sample or fieldwork details.",
      "caveat": "Supporting evidence only. The public page does not disclose N. Martech utilization is not the same measure as unused licenses or wasted spend.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-005",
      "slug": "martech-stack-benchmarks",
      "metric_category": "landscape_size",
      "figure": "15,505 products",
      "claim": "The 2026 Marketing Technology Landscape mapped 15,505 products.",
      "evidence_scope": "martech_landscape",
      "hero_eligible": true,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/state-of-martech-2026.pdf",
      "source_title": "State of Martech 2026",
      "source_section": "Page 18 / report page 13: 2026 Marketing Technology Landscape",
      "source_quality": "primary_landscape_and_survey",
      "evidence_type": "product-landscape census methodology plus primary survey",
      "population": "15,505 mapped martech products; separate February 2026 survey of 208 marketing and marketing-operations leaders across about 70 AI use cases",
      "geography": "survey geography is not fully disclosed in the public report",
      "period": "product landscape and survey published May 5, 2026; AI category comparisons use the report's 2024 and 2026 surveys",
      "methodology": "Chiefmartec and MartechTribe maintained the product landscape and surveyed 208 leaders. The sample was 40% VP or above, 36% technology companies, 21% professional services, 61% pure B2B, and explicitly described as tech-forward/top-quartile.",
      "caveat": "The product map is not a count of purchases or active enterprise stacks. The N=208 survey is intentionally tech-forward and multi-select where stated, so it is not market-representative.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-006",
      "slug": "martech-stack-benchmarks",
      "metric_category": "landscape_growth",
      "figure": "+121 / +0.79%",
      "claim": "The mapped martech landscape grew by a net 121 products, or 0.79%, from 15,384 to 15,505.",
      "evidence_scope": "martech_landscape",
      "hero_eligible": true,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/state-of-martech-2026.pdf",
      "source_title": "State of Martech 2026",
      "source_section": "Page 18 / report page 13: landscape year-over-year change",
      "source_quality": "primary_landscape_and_survey",
      "evidence_type": "product-landscape census methodology plus primary survey",
      "population": "15,505 mapped martech products; separate February 2026 survey of 208 marketing and marketing-operations leaders across about 70 AI use cases",
      "geography": "survey geography is not fully disclosed in the public report",
      "period": "product landscape and survey published May 5, 2026; AI category comparisons use the report's 2024 and 2026 surveys",
      "methodology": "Chiefmartec and MartechTribe maintained the product landscape and surveyed 208 leaders. The sample was 40% VP or above, 36% technology companies, 21% professional services, 61% pure B2B, and explicitly described as tech-forward/top-quartile.",
      "caveat": "The product map is not a count of purchases or active enterprise stacks. The N=208 survey is intentionally tech-forward and multi-select where stated, so it is not market-representative.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-007",
      "slug": "martech-stack-benchmarks",
      "metric_category": "landscape_churn",
      "figure": "1,488 added; 1,367 removed",
      "claim": "Behind the 121-product net increase, the 2026 landscape added 1,488 products and removed 1,367.",
      "evidence_scope": "martech_landscape",
      "hero_eligible": true,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/state-of-martech-2026.pdf",
      "source_title": "State of Martech 2026",
      "source_section": "Page 18 / report page 13: product additions and removals",
      "source_quality": "primary_landscape_and_survey",
      "evidence_type": "product-landscape census methodology plus primary survey",
      "population": "15,505 mapped martech products; separate February 2026 survey of 208 marketing and marketing-operations leaders across about 70 AI use cases",
      "geography": "survey geography is not fully disclosed in the public report",
      "period": "product landscape and survey published May 5, 2026; AI category comparisons use the report's 2024 and 2026 surveys",
      "methodology": "Chiefmartec and MartechTribe maintained the product landscape and surveyed 208 leaders. The sample was 40% VP or above, 36% technology companies, 21% professional services, 61% pure B2B, and explicitly described as tech-forward/top-quartile.",
      "caveat": "The product map is not a count of purchases or active enterprise stacks. The N=208 survey is intentionally tech-forward and multi-select where stated, so it is not market-representative.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-008",
      "slug": "martech-stack-benchmarks",
      "metric_category": "category_churn",
      "figure": "176 removed; 139 added; net -37",
      "claim": "The Content Marketing subcategory recorded 176 removals and 139 additions in 2026, a net decline of 37 products.",
      "evidence_scope": "martech_landscape",
      "hero_eligible": true,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/state-of-martech-2026.pdf",
      "source_title": "State of Martech 2026",
      "source_section": "Content Marketing category analysis",
      "source_quality": "primary_landscape_and_survey",
      "evidence_type": "product-landscape census methodology plus primary survey",
      "population": "15,505 mapped martech products; separate February 2026 survey of 208 marketing and marketing-operations leaders across about 70 AI use cases",
      "geography": "survey geography is not fully disclosed in the public report",
      "period": "product landscape and survey published May 5, 2026; AI category comparisons use the report's 2024 and 2026 surveys",
      "methodology": "Chiefmartec and MartechTribe maintained the product landscape and surveyed 208 leaders. The sample was 40% VP or above, 36% technology companies, 21% professional services, 61% pure B2B, and explicitly described as tech-forward/top-quartile.",
      "caveat": "The product map is not a count of purchases or active enterprise stacks. The N=208 survey is intentionally tech-forward and multi-select where stated, so it is not market-representative.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-009",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ai_adoption",
      "figure": "30% to 50%",
      "claim": "Advertising and Promotions AI use-case adoption rose from 30% in the report's 2024 survey to 50% in its 2026 survey.",
      "evidence_scope": "martech_dual_survey_missing_2024_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/state-of-martech-2026.pdf",
      "source_title": "State of Martech 2026",
      "source_section": "Page 35 / report page 30: AI adoption by martech category",
      "source_quality": "primary_landscape_and_survey",
      "evidence_type": "product-landscape census methodology plus primary survey",
      "population": "15,505 mapped martech products; separate February 2026 survey of 208 marketing and marketing-operations leaders across about 70 AI use cases",
      "geography": "survey geography is not fully disclosed in the public report",
      "period": "product landscape and survey published May 5, 2026; AI category comparisons use the report's 2024 and 2026 surveys",
      "methodology": "Chiefmartec and MartechTribe maintained the product landscape and surveyed 208 leaders. The sample was 40% VP or above, 36% technology companies, 21% professional services, 61% pure B2B, and explicitly described as tech-forward/top-quartile.",
      "caveat": "The product map is not a count of purchases or active enterprise stacks. The N=208 survey is intentionally tech-forward and multi-select where stated, so it is not market-representative. The comparison uses separate report surveys and does not prove a causal effect. The 2024 comparator denominator and composition are not disclosed in the extracted evidence, so use the change directionally.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-010",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ai_adoption",
      "figure": "28% to 49%",
      "claim": "Commerce and Sales AI use-case adoption rose from 28% in the report's 2024 survey to 49% in its 2026 survey.",
      "evidence_scope": "martech_dual_survey_missing_2024_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/state-of-martech-2026.pdf",
      "source_title": "State of Martech 2026",
      "source_section": "Page 35 / report page 30: AI adoption by martech category",
      "source_quality": "primary_landscape_and_survey",
      "evidence_type": "product-landscape census methodology plus primary survey",
      "population": "15,505 mapped martech products; separate February 2026 survey of 208 marketing and marketing-operations leaders across about 70 AI use cases",
      "geography": "survey geography is not fully disclosed in the public report",
      "period": "product landscape and survey published May 5, 2026; AI category comparisons use the report's 2024 and 2026 surveys",
      "methodology": "Chiefmartec and MartechTribe maintained the product landscape and surveyed 208 leaders. The sample was 40% VP or above, 36% technology companies, 21% professional services, 61% pure B2B, and explicitly described as tech-forward/top-quartile.",
      "caveat": "The product map is not a count of purchases or active enterprise stacks. The N=208 survey is intentionally tech-forward and multi-select where stated, so it is not market-representative. The comparison uses separate report surveys and does not prove a causal effect. The 2024 comparator denominator and composition are not disclosed in the extracted evidence, so use the change directionally.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-011",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ai_adoption",
      "figure": "79% to 89%",
      "claim": "Content and Experience AI use-case adoption rose from 79% in the report's 2024 survey to 89% in its 2026 survey.",
      "evidence_scope": "martech_dual_survey_missing_2024_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/state-of-martech-2026.pdf",
      "source_title": "State of Martech 2026",
      "source_section": "Page 35 / report page 30: AI adoption by martech category",
      "source_quality": "primary_landscape_and_survey",
      "evidence_type": "product-landscape census methodology plus primary survey",
      "population": "15,505 mapped martech products; separate February 2026 survey of 208 marketing and marketing-operations leaders across about 70 AI use cases",
      "geography": "survey geography is not fully disclosed in the public report",
      "period": "product landscape and survey published May 5, 2026; AI category comparisons use the report's 2024 and 2026 surveys",
      "methodology": "Chiefmartec and MartechTribe maintained the product landscape and surveyed 208 leaders. The sample was 40% VP or above, 36% technology companies, 21% professional services, 61% pure B2B, and explicitly described as tech-forward/top-quartile.",
      "caveat": "The product map is not a count of purchases or active enterprise stacks. The N=208 survey is intentionally tech-forward and multi-select where stated, so it is not market-representative. The comparison uses separate report surveys and does not prove a causal effect. The 2024 comparator denominator and composition are not disclosed in the extracted evidence, so use the change directionally.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-012",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ai_agents",
      "figure": "90.3%",
      "claim": "The Martech for 2026 report says 90.3% of its tech-forward participants used AI agents somewhere in the martech stack.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "AI agents in the martech stack",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-013",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ai_deployment",
      "figure": "23.3%",
      "claim": "The Martech for 2026 report says 23.3% of participants had AI agents in full production.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "AI agent deployment status",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims. Do not infer that every other respondent was in one mutually exclusive status without the original response table.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-014",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ai_autonomy",
      "figure": "80.6%",
      "claim": "The Martech for 2026 report says 80.6% used AI agents in assistant-only mode.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "Page 57: AI agent autonomy",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-015",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ai_stack_effect",
      "figure": "85.4% enhanced existing functionality",
      "claim": "The Martech for 2026 report says 85.4% used AI to enhance existing functionality.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "Page 59: enhance, add, or replace functionality",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-016",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ai_stack_effect",
      "figure": "42.7% new; 30.1% replaced",
      "claim": "The Martech for 2026 report says 42.7% added new functionality while 30.1% replaced existing functionality with AI.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "Page 59: enhance, add, or replace functionality",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims. The question allowed multiple selections, so the values are not shares of one exclusive whole.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-017",
      "slug": "martech-stack-benchmarks",
      "metric_category": "integration_method",
      "figure": "56.3% custom; 47.6% prebuilt; 40.8% iPaaS",
      "claim": "The Martech for 2026 report lists custom integrations at 56.3%, prebuilt integrations at 47.6%, and iPaaS at 40.8%.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "Pages 47-49: integration methods",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims. The question allowed multiple selections.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-018",
      "slug": "martech-stack-benchmarks",
      "metric_category": "data_integration",
      "figure": "37.9%",
      "claim": "The Martech for 2026 report says 37.9% connected cloud warehouse or lakehouse data directly to AI agents.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "Page 50: cloud warehouse or lakehouse connection to AI agents",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-019",
      "slug": "martech-stack-benchmarks",
      "metric_category": "barrier",
      "figure": "56.3%",
      "claim": "Poor data quality was the most-selected AI and data challenge in the Martech for 2026 report, at 56.3%.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "Page 51: AI and data challenges",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims. The question allowed multiple selections.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-020",
      "slug": "martech-stack-benchmarks",
      "metric_category": "barrier",
      "figure": "52.4%",
      "claim": "Organizational and process readiness was selected by 52.4% in the Martech for 2026 report.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "Page 51: AI and data challenges",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims. The question allowed multiple selections.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-021",
      "slug": "martech-stack-benchmarks",
      "metric_category": "barrier",
      "figure": "50.5%",
      "claim": "Integration friction was selected by 50.5% in the Martech for 2026 report.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "Page 51: AI and data challenges",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims. The question allowed multiple selections.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-022",
      "slug": "martech-stack-benchmarks",
      "metric_category": "barrier",
      "figure": "26.2%",
      "claim": "Cost observability and budget control was selected by 26.2% in the Martech for 2026 report.",
      "evidence_scope": "martech_supporting_missing_n",
      "hero_eligible": false,
      "comparison_only": false,
      "source_domain": "martechday.com",
      "source_url": "https://content.martechday.com/martech-for-2026.pdf",
      "source_title": "Martech for 2026",
      "source_section": "Page 51: AI and data challenges",
      "source_quality": "primary_survey_missing_n",
      "evidence_type": "Chiefmartec and MartechTribe AI and Data in Marketing survey",
      "population": "tech-forward marketing and martech participants; respondent count not disclosed in the accessible report",
      "geography": "not disclosed in the accessible report",
      "period": "2025 survey published December 2, 2025",
      "methodology": "The report asks participants about AI agents, integrations, data sources, autonomy, and barriers. Several questions allow multiple selections.",
      "caveat": "Supporting evidence only. N is not disclosed and the authors say participants skew more tech-savvy than average. Percentages must not be presented as market-representative or hero claims. The question allowed multiple selections.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-023",
      "slug": "martech-stack-benchmarks",
      "metric_category": "saas_waste_comparison",
      "figure": "20%",
      "claim": "Flexera respondents at beginner, intermediate, and advanced ITAM maturity each estimated SaaS software waste at 20%.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "flexera.com",
      "source_url": "https://resources.flexera.com/web/pdf/Flexera-State-of-IT-Asset-Management-Report-2026.pdf",
      "source_title": "Flexera 2026 State of ITAM Report",
      "source_section": "Page 36, Figure 21: estimated wasted spend across the IT estate",
      "source_quality": "primary_independent_panel_survey",
      "evidence_type": "global survey of IT asset-management professionals",
      "population": "512 professionals with IT asset-management responsibilities sourced from an independently maintained and vetted panel",
      "geography": "worldwide across industries and organizational contexts",
      "period": "fielded in early 2026",
      "methodology": "Flexera surveyed 512 ITAM professionals and rounded published percentages to whole numbers. The report is licensed CC BY 4.0.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Waste estimates are respondent estimates and cannot be converted into a marketing revenue-loss figure.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-024",
      "slug": "martech-stack-benchmarks",
      "metric_category": "saas_waste_direction_comparison",
      "figure": "43% increased; 42% same; 15% decreased",
      "claim": "In Flexera's 2026 survey, 43% said SaaS wasted spend increased, 42% said it stayed the same, and 15% said it decreased over the previous year.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "flexera.com",
      "source_url": "https://resources.flexera.com/web/pdf/Flexera-State-of-IT-Asset-Management-Report-2026.pdf",
      "source_title": "Flexera 2026 State of ITAM Report",
      "source_section": "Page 38, Figure 22: how wasted spend changed",
      "source_quality": "primary_independent_panel_survey",
      "evidence_type": "global survey of IT asset-management professionals",
      "population": "512 professionals with IT asset-management responsibilities sourced from an independently maintained and vetted panel",
      "geography": "worldwide across industries and organizational contexts",
      "period": "fielded in early 2026",
      "methodology": "Flexera surveyed 512 ITAM professionals and rounded published percentages to whole numbers. The report is licensed CC BY 4.0.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Waste estimates are respondent estimates and cannot be converted into a marketing revenue-loss figure.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-025",
      "slug": "martech-stack-benchmarks",
      "metric_category": "visibility_comparison",
      "figure": "43% to 36%",
      "claim": "Flexera reports that complete visibility across IT environments declined from 43% in 2025 to 36% in 2026.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "flexera.com",
      "source_url": "https://resources.flexera.com/web/pdf/Flexera-State-of-IT-Asset-Management-Report-2026.pdf",
      "source_title": "Flexera 2026 State of ITAM Report",
      "source_section": "Visibility gap across cloud, SaaS, and AI",
      "source_quality": "primary_independent_panel_survey",
      "evidence_type": "global survey of IT asset-management professionals",
      "population": "512 professionals with IT asset-management responsibilities sourced from an independently maintained and vetted panel",
      "geography": "worldwide across industries and organizational contexts",
      "period": "fielded in early 2026",
      "methodology": "Flexera surveyed 512 ITAM professionals and rounded published percentages to whole numbers. The report is licensed CC BY 4.0.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Waste estimates are respondent estimates and cannot be converted into a marketing revenue-loss figure.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-026",
      "slug": "martech-stack-benchmarks",
      "metric_category": "governance_comparison",
      "figure": "64%",
      "claim": "Flexera reports that 64% of surveyed ITAM teams managed SaaS licenses.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "flexera.com",
      "source_url": "https://resources.flexera.com/web/pdf/Flexera-State-of-IT-Asset-Management-Report-2026.pdf",
      "source_title": "Flexera 2026 State of ITAM Report",
      "source_section": "Visibility gap across cloud, SaaS, and AI",
      "source_quality": "primary_independent_panel_survey",
      "evidence_type": "global survey of IT asset-management professionals",
      "population": "512 professionals with IT asset-management responsibilities sourced from an independently maintained and vetted panel",
      "geography": "worldwide across industries and organizational contexts",
      "period": "fielded in early 2026",
      "methodology": "Flexera surveyed 512 ITAM professionals and rounded published percentages to whole numbers. The report is licensed CC BY 4.0.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Waste estimates are respondent estimates and cannot be converted into a marketing revenue-loss figure.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-027",
      "slug": "martech-stack-benchmarks",
      "metric_category": "unused_licenses_comparison",
      "figure": "36%",
      "claim": "Zylo reports that organizations left an average of 36% of SaaS licenses unused against its recommended utilization levels.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "zylo.com",
      "source_url": "https://zylo.com/2026-saas-management-index",
      "source_title": "2026 SaaS Management Index",
      "source_section": "License waste remains a persistent challenge",
      "source_quality": "first_party_platform_telemetry",
      "evidence_type": "enterprise SaaS-management telemetry plus a separate IT-leader survey for cost-shock claims",
      "population": "telemetry covering 40M+ SaaS licenses and $75B+ in discovered and categorized spend; cost-shock questions use a separate survey of 218 IT leaders",
      "geography": "not disclosed on the public report page",
      "period": "2026 edition with year-over-year comparisons and nine years of underlying spend, license, and usage data",
      "methodology": "Zylo aggregates observed customer portfolio, license, usage, and spend data. Its public newsroom release separately identifies N=218 for unexpected-cost questions.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Zylo customer telemetry is not a probability sample of all organizations and must not be converted into a martech waste or revenue-leakage rate.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-028",
      "slug": "martech-stack-benchmarks",
      "metric_category": "portfolio_comparison",
      "figure": "$55.7M; 305 apps",
      "claim": "Zylo's 2026 benchmark reports average annual SaaS spend of $55.7 million and an average portfolio of 305 applications.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "zylo.com",
      "source_url": "https://zylo.com/2026-saas-management-index",
      "source_title": "2026 SaaS Management Index",
      "source_section": "Portfolios Make Room for New AI Investments—But It Comes at a Cost",
      "source_quality": "first_party_platform_telemetry",
      "evidence_type": "enterprise SaaS-management telemetry plus a separate IT-leader survey for cost-shock claims",
      "population": "telemetry covering 40M+ SaaS licenses and $75B+ in discovered and categorized spend; cost-shock questions use a separate survey of 218 IT leaders",
      "geography": "not disclosed on the public report page",
      "period": "2026 edition with year-over-year comparisons and nine years of underlying spend, license, and usage data",
      "methodology": "Zylo aggregates observed customer portfolio, license, usage, and spend data. Its public newsroom release separately identifies N=218 for unexpected-cost questions.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Zylo customer telemetry is not a probability sample of all organizations and must not be converted into a martech waste or revenue-leakage rate.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-029",
      "slug": "martech-stack-benchmarks",
      "metric_category": "pricing_risk_comparison",
      "figure": "78%",
      "claim": "In Zylo's separate survey of 218 IT leaders, 78% reported unexpected charges tied to consumption-based or AI pricing in the previous 12 months.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "zylo.com",
      "source_url": "https://zylo.com/2026-saas-management-index",
      "source_title": "2026 SaaS Management Index",
      "source_section": "Unexpected SaaS costs are disrupting budgets",
      "source_quality": "first_party_platform_telemetry",
      "evidence_type": "enterprise SaaS-management telemetry plus a separate IT-leader survey for cost-shock claims",
      "population": "telemetry covering 40M+ SaaS licenses and $75B+ in discovered and categorized spend; cost-shock questions use a separate survey of 218 IT leaders",
      "geography": "not disclosed on the public report page",
      "period": "2026 edition with year-over-year comparisons and nine years of underlying spend, license, and usage data",
      "methodology": "Zylo aggregates observed customer portfolio, license, usage, and spend data. Its public newsroom release separately identifies N=218 for unexpected-cost questions.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Zylo customer telemetry is not a probability sample of all organizations and must not be converted into a martech waste or revenue-leakage rate.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-030",
      "slug": "martech-stack-benchmarks",
      "metric_category": "pricing_risk_comparison",
      "figure": "61%",
      "claim": "In Zylo's separate survey of 218 IT leaders, 61% said unplanned SaaS cost increases forced them to cut projects.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "zylo.com",
      "source_url": "https://zylo.com/2026-saas-management-index",
      "source_title": "2026 SaaS Management Index",
      "source_section": "Unexpected SaaS costs are disrupting budgets",
      "source_quality": "first_party_platform_telemetry",
      "evidence_type": "enterprise SaaS-management telemetry plus a separate IT-leader survey for cost-shock claims",
      "population": "telemetry covering 40M+ SaaS licenses and $75B+ in discovered and categorized spend; cost-shock questions use a separate survey of 218 IT leaders",
      "geography": "not disclosed on the public report page",
      "period": "2026 edition with year-over-year comparisons and nine years of underlying spend, license, and usage data",
      "methodology": "Zylo aggregates observed customer portfolio, license, usage, and spend data. Its public newsroom release separately identifies N=218 for unexpected-cost questions.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Zylo customer telemetry is not a probability sample of all organizations and must not be converted into a martech waste or revenue-leakage rate.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-031",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ownership_comparison",
      "figure": "81% business units; 15% IT",
      "claim": "Zylo reports that business units controlled 81% of SaaS spend while IT directly managed 15%.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "zylo.com",
      "source_url": "https://zylo.com/2026-saas-management-index",
      "source_title": "2026 SaaS Management Index",
      "source_section": "Visibility is declining as SaaS ownership continues to decentralize",
      "source_quality": "first_party_platform_telemetry",
      "evidence_type": "enterprise SaaS-management telemetry plus a separate IT-leader survey for cost-shock claims",
      "population": "telemetry covering 40M+ SaaS licenses and $75B+ in discovered and categorized spend; cost-shock questions use a separate survey of 218 IT leaders",
      "geography": "not disclosed on the public report page",
      "period": "2026 edition with year-over-year comparisons and nine years of underlying spend, license, and usage data",
      "methodology": "Zylo aggregates observed customer portfolio, license, usage, and spend data. Its public newsroom release separately identifies N=218 for unexpected-cost questions.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Zylo customer telemetry is not a probability sample of all organizations and must not be converted into a martech waste or revenue-leakage rate.",
      "audited_at": "2026-07-14"
    },
    {
      "claim_id": "MTS-032",
      "slug": "martech-stack-benchmarks",
      "metric_category": "ai_spend_comparison",
      "figure": "+108% overall; +393% at 10,001+ employees",
      "claim": "Zylo reports that AI-native application spend grew 108% overall and 393% in organizations with more than 10,000 employees.",
      "evidence_scope": "enterprise_saas_comparison",
      "hero_eligible": false,
      "comparison_only": true,
      "source_domain": "zylo.com",
      "source_url": "https://zylo.com/2026-saas-management-index",
      "source_title": "2026 SaaS Management Index",
      "source_section": "AI Is Transforming How Software Is Built, Priced and Managed",
      "source_quality": "first_party_platform_telemetry",
      "evidence_type": "enterprise SaaS-management telemetry plus a separate IT-leader survey for cost-shock claims",
      "population": "telemetry covering 40M+ SaaS licenses and $75B+ in discovered and categorized spend; cost-shock questions use a separate survey of 218 IT leaders",
      "geography": "not disclosed on the public report page",
      "period": "2026 edition with year-over-year comparisons and nine years of underlying spend, license, and usage data",
      "methodology": "Zylo aggregates observed customer portfolio, license, usage, and spend data. Its public newsroom release separately identifies N=218 for unexpected-cost questions.",
      "caveat": "Enterprise SaaS comparison only, not martech data. Zylo customer telemetry is not a probability sample of all organizations and must not be converted into a martech waste or revenue-leakage rate. The year-over-year telemetry describes spend change, not business value or causal ROI.",
      "audited_at": "2026-07-14"
    }
  ]
}