Procurement Software: AI Visibility Market Discovery Index

Benchmark Summary

Questions This Section Answers

• Who led the Procurement Software benchmark in October 2026, and by how much?
• Which brands recorded significant declines from the July 2026 baseline?
• Did any brand post a significant increase over the baseline period?

Coupa led the Procurement Software benchmark in October 2026 with valid recommendation coverage of 56.9%, ahead of SAP Ariba at 51.5%, a gap of 5.4 percentage points. Measured against the July 2026 baseline, no brand recorded a significant increase in valid recommendation coverage. Six of the ten tracked brands recorded significant declines over that period: Coupa (down 8.7 points), GEP SMART (down 7.2 points), Ivalua (down 7.3 points), Procurify (down 8.8 points), SAP Ariba (down 11.1 points), and Zip (down 7.3 points). SAP Ariba posted the largest baseline-to-current decline. Four brands held stable across the baseline period: Jaggaer, Kissflow Procurement, Precoro, and Tradeshift. Within the most recent month, valid recommendation coverage rose for all ten tracked brands from September 2026 to October 2026, with Coupa posting the largest single-month increase, up 16.0 points, from 40.9% to 56.9%. The benchmark collected 800 prompt-surface observations in October 2026 and produced 445 qualified observations after qualification.

Current Benchmark at a Glance

August 2026 recorded 476 qualified observations and September 2026 recorded 460, both higher than the current month. Qualified surface breadth refers to the number of canonical AI/search surface families with at least one qualified observation: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. The benchmark maintained coverage across all six families in every month of the series.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Procurement Software

Research Scope and Qualification

Questions This Section Answers

• How many prompt-surface observations qualified for the public benchmark?
• Why are brand-level percentages calculated on qualified observations rather than the full collection?

The public benchmark is narrower than the raw collection universe by design. Brand-level percentages use the qualified observations as the public denominator, not the raw collection.

For additional detail on the research approach, see AI Visibility Market Discovery Methodology.

Current Brand Standings

Questions This Section Answers

• Where does each brand land on presence, valid recommendation coverage, and top-three rate?
• How far ahead of SAP Ariba did Coupa finish in October 2026?
• Which brands combine meaningful recommendation coverage with weak rank-one rates?

How to Read the Standings

• Presence rate: the share of qualified observations where the brand is mentioned at all.
• Valid recommendation coverage: the share of qualified observations where the brand receives a valid recommendation.
• Top-three rate: the share of qualified observations where the brand appears among the top three recommended options.
• Rank-one rate: the share of qualified observations where the brand is the first recommendation.
• Net sentiment: the balance of positive over neutral and negative mentions, scaled from 0 to 1.

For formulas and denominator rules, see AI Visibility Market Discovery Metric Definitions.

Recommendation Coverage Movement

Questions This Section Answers

• How did valid recommendation coverage change for each brand between July and October 2026?
• Why did coverage rise for all ten brands month over month while most stayed below their July baseline?

Measured month over month, from September 2026 to October 2026, valid recommendation coverage rose for all ten tracked brands: Coupa up 16.0 points, SAP Ariba up 12.6 points, Jaggaer up 11.1 points, Procurify up 9.9 points, GEP SMART up 9.0 points, Precoro up 7.8 points, Ivalua up 5.0 points, Zip up 4.3 points, Tradeshift up 1.4 points, and Kissflow Procurement up 1.0 point. The data describes the output distribution recorded in that month; it does not establish a cause. Most brands remained below their July 2026 baseline levels despite the month-over-month increase.

Largest Increase: Coupa

Coupa's valid recommendation coverage rose from 40.9% in September 2026 to 56.9% in October 2026, up 16.0 percentage points, beyond normal month-to-month variation. Measured against the July 2026 baseline, Coupa declined from 65.6% to 56.9%, down 8.7 percentage points. Top-three rate rose from 34.6% in September 2026 to 46.3% in October 2026, while rank-one rate rose from 17.4% to 23.4%. Presence rate held close to the baseline, at 93.0% in October 2026 versus 95.7% in July 2026.

Largest Decline: SAP Ariba

SAP Ariba posted the largest baseline-to-current decline in valid recommendation coverage, falling from 62.6% in July 2026 to 51.5% in October 2026, down 11.1 percentage points. Within the latest month, coverage moved from 38.9% in September 2026 to 51.5% in October 2026, up 12.6 percentage points, beyond normal month-to-month variation. Top-three rate declined from 44.9% in July 2026 to 39.6% in October 2026, down 5.3 percentage points, and rank-one rate declined from 19.6% to 16.9%, down 2.7 percentage points. Presence rate remained comparatively close, at 90.6% in July 2026 and 87.4% in October 2026.

Category Leader: Coupa

Coupa remained the category leader in October 2026 with valid recommendation coverage of 56.9%, ahead of SAP Ariba at 51.5%. Coupa's lead over SAP Ariba widened from 2.0 percentage points in September 2026 to 5.4 percentage points in October 2026, as both brands' coverage increased from their September 2026 lows. Coupa posted a single-month increase in October 2026 after declines in August and September 2026.

Recommendation Placement Snapshot

Questions This Section Answers

• How do top-three and rank-one rates compare for Coupa, SAP Ariba, and Procurify?
• Can two brands with similar recommendation coverage have very different rank-one rates?

Coverage alone does not show how prominently a brand is recommended. While Coupa and SAP Ariba lead in valid recommendation coverage, their top-three and rank-one rates reveal how often they appear in the most prominent positions.

Coupa's top-three rate of 46.3% in October 2026 and rank-one rate of 23.4% led the category, with SAP Ariba next at 39.6% and 16.9% respectively. Close coverage can still hide different first-position rates: Precoro at 33.9% coverage carried a 3.4% rank-one rate in October 2026, versus Procurify at 36.6% coverage and a 4.5% rank-one rate.

Buyer-Intent Distribution

Questions This Section Answers

• Which buyer-intent classes are represented in the qualified observations?
• Does the benchmark contain any Pricing & Value or Multi-Brand Comparison signals?

The qualified observations in each month fell into the Brand Recommendation class of discovery.

All qualified observations in the current public series fell into the Brand Recommendation class. The current public series measures that class of discovery and does not yet contain qualified observations in the Pricing & Value or Multi-Brand Comparison classes.

Historical Measurement Record

Questions This Section Answers

• What does the month-by-month record show about the leader's coverage across the series?
• Which measurement period produced the largest coverage movement?

This is an evergreen benchmark URL. New measurements are added to the same report.

Evidence and Source Layer

Questions This Section Answers

• What source-level evidence is retained for each prompt observation?
• Does a citation in an AI response prove that the source caused the recommendation?

The benchmark is built from prompt-level observations that retain the query, AI/search surface, answer, brand outcome, recommendation placement, sentiment, and, where exposed, citations or attributable evidence sources. Source presence is evidence about the information environment. It is not automatically proof that the source caused the recommendation.

Scope Boundaries

This public benchmark does not measure market share, attributable sales, every possible AI response, organic-search ranking, social mention volume, private or sponsored channels, or causality from a metric movement alone. Price, value, and head-to-head comparison have no public signal in this data series.

Top 10 Cited Domains

Questions This Section Answers

• Which domains were cited most often across AI platform responses in October 2026?
• How concentrated are citations across the top 10 domains versus the full set?
• Which tracked brands' own domains appear among the most-cited sources?

Across all AI platform responses in October 2026, the benchmark recorded 5,548 citations drawn from 1,445 unique domains.

Citations are broadly distributed: the top 10 domains together account for a modest share of the 5,548 total citations, and 1,445 unique domains were recorded overall. Three tracked brands' own domains appear in the top 10: ivalua.com at rank 6, coupa.com at rank 8, and precoro.com at rank 9. Across the top 10, general platforms (YouTube, Google, Reddit, Facebook) sit alongside analyst sources (Gartner), trade press (Procurement Magazine), review sites (G2), and official brand sites, indicating that AI recommendations in this vertical draw on a mixed information environment rather than a single source type.

About This Benchmark

The LLM Authority Index AI Visibility Market Discovery Index tracks how often brands appear in AI-generated responses across major AI/search surfaces, using a structured research methodology applied to a defined prompt universe each month.

• AI Visibility Market Discovery Methodology
• AI Visibility Market Discovery Metric Definitions
• AI Visibility Market Discovery Research Standards
• Modeled AI Visibility Authority Value

Get a Company-Level Authority Index

The public industry benchmark shows category-level standings. A company-level Authority Index can go deeper.

Get my free AI Company Index