Conga AI Market Strategy Report - Contract Management Software

Answer Capsule

Conga holds a mid-tier position in the contract management software category, with 15.77% valid recommendation coverage in September 2026, placing it in a three-way tie for fifth place alongside Agiloft and ContractSafe. The brand is visible but under-recommended relative to its presence, appearing in 26.14% of qualified AI responses while converting only a portion of that presence into actual recommendations. Conga's clearest win is its recovery to baseline coverage after the August compression, while its most significant weakness is a rank-one recommendation rate of just 0.21%, indicating the brand is almost never the first choice AI systems name. The clearest opportunity lies in converting its substantial presence on Google AI Overviews, where it holds 36.96% coverage, into stronger top-three placement across other platforms.

Who This Report Is For

This report is for Conga's marketing, product marketing, and go-to-market leadership teams responsible for understanding how AI systems recommend contract management software to buyers during the discovery and consideration process.

Report Card

Executive Summary

Conga holds a stable but unspectacular position in the contract management software category. The benchmark shows the brand at 15.77% valid recommendation coverage in September 2026, essentially unchanged from its 15.4% July baseline and up 12.3 points from its August low of 3.5%. Conga recorded 76 valid recommendations from 482 qualified observations, placing it in a three-way tie for fifth with Agiloft and ContractSafe.

The brand's raw mention presence rate of 26.14% is substantially higher than its recommendation coverage, indicating that Conga appears in AI responses regularly but is not always converted into a named recommendation. Positive mentions account for 18.26% of observations, with no negative mentions recorded, giving Conga a net sentiment score of 0.6984. The brand's strongest platform signal comes from Google AI Overviews, where it achieves 36.96% valid recommendation coverage, well above its category average of 15.77%.

Conga's clearest weakness is its rank-one rate of 0.21%, meaning the brand is named as the single first recommendation in only one of 482 qualified observations. Its top-three rate of 5.60% also trails several competitors with similar or lower coverage levels. The brand shows presence without recommendation conversion, particularly on ChatGPT, where it appears in 28.30% of responses but achieves only 9.43% valid recommendation coverage.

What Conga Is Winning

Conga's most defensible position is its recovery to baseline coverage. The brand rose 12.3 points from 3.5% in August 2026 to 15.8% in September 2026, landing 0.4 points above its July baseline of 15.4%. This makes Conga one of only two brands in the tracked set, alongside DocuSign, to hold coverage at or above July levels.

The brand also demonstrates meaningful strength on Google AI Overviews. Conga achieves 36.96% valid recommendation coverage on that platform, more than double its category-wide rate, with a top-three rate of 15.22%. This suggests the brand has a source footprint that Google's AI Overviews system retrieves and synthesizes effectively.

Conga maintains a clean sentiment profile with zero negative mentions across all 482 qualified observations. Its net sentiment score of 0.6984 reflects a mix of 88 positive and 38 neutral mentions, with no cautionary or negative framing present in the dataset.

Where Conga Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Where is the gap between Conga's AI presence and its recommendation coverage largest?
• How severe is Conga's rank-one shortfall compared with category leaders?
• Which platform shows the clearest gap between Conga's presence and its recommendation placement?

Conga's most significant gap is the distance between presence and recommendation. The brand appears in 26.14% of qualified AI responses but is recommended in only 15.77%, a conversion gap of more than 10 points. This pattern is most pronounced on ChatGPT, where Conga holds 28.30% presence but only 9.43% recommendation coverage, meaning the brand is frequently mentioned as context or comparison material rather than as a named option.

The rank-one gap is severe. Conga achieves a rank-one rate of 0.21%, tied with Agiloft for the second-lowest in the category and far behind Ironclad's 18.05% and DocuSign's 16.80%. When Conga is recommended, its average rank is 4.0, placing it in the middle of shortlists rather than at the top. The brand's top-three rate of 5.60% is also below what its coverage level would suggest, indicating that even when Conga earns a recommendation, it tends to appear lower in the list.

Copilot represents a notable platform gap. Conga holds only 5.13% valid recommendation coverage on Copilot, with zero top-three placements and an average recommended rank of 8.0 when it does appear. The brand is present in 17.95% of Copilot responses but rarely earns recommendation placement.

Biggest Opportunity

Questions This Section Answers

• What is Conga's clearest path from being referenced to being recommended?
• Which evidence sources should Conga prioritize to improve cross-platform recommendation coverage?

Conga's clearest path from reference to recommendation lies in converting its Google AI Overviews strength into a broader cross-platform recommendation pattern. The brand already achieves 36.96% coverage on that platform, suggesting the public evidence layer supports Conga as a legitimate option. The gap is that this strength does not transfer to ChatGPT, Copilot, or Gemini, where coverage falls to 9.43%, 5.13%, and 8.62% respectively.

The strategic priority should be understanding which evidence sources drive Google AI Overviews recommendations and whether those same sources can be strengthened to influence other platforms. Conga's presence on ChatGPT at 28.30% indicates the brand is retrievable, but the framing of that presence is not converting into recommendation placement. Closing the gap between being mentioned and being recommended on ChatGPT and Copilot represents the highest-leverage opportunity for improving overall recommendation coverage.

Competitive Landscape

Questions This Section Answers

• Where does Conga rank against competitors on placement quality rather than raw coverage?
• Which competitors hold the top-three and rank-one positions Conga lacks?

DocuSign and PandaDoc hold dominant recommendation-stage strength in the contract management software category, with Ironclad close behind on placement quality. Conga sits in the mid-tier cluster, tied with Agiloft and ContractSafe at 15.8% coverage but trailing those brands on certain placement metrics.

Average recommended rank covers rank-eligible recommendations only.

Conga's position in the table shows a brand with mid-tier coverage but bottom-tier placement quality. Its top-three rate ties with ContractSafe at 5.60%, but its rank-one rate of 0.21% is among the lowest in the category. The brand's average recommended rank of 4.00 places it behind ContractSafe and Icertis, meaning that when Conga is recommended, it tends to appear lower in the shortlist than competitors with similar coverage levels.

Prompt Evidence

Google AI Overviews / Best Contract Management Software Discovery Prompt: "contract management software" Result: Conga appeared in a recommendation-shaped answer with valid recommendation credit, contributing to its 36.96% coverage on this platform.

ChatGPT / Best Contract Management Software Discovery Prompt: "contract management software" Result: Conga was mentioned in 28.30% of ChatGPT responses but achieved only 9.43% valid recommendation coverage, indicating frequent presence without recommendation conversion.

Copilot / Best Contract Management Software Discovery Prompt: "contract lifecycle management software" Result: Conga appeared in 17.95% of Copilot responses but earned valid recommendation credit in only 5.13%, with an average recommended rank of 8.0 when recommended.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map the specific prompts and evidence sources where Conga appears as context rather than recommendation, with particular focus on ChatGPT and Copilot conversion gaps.

Phase 2: Recommendation Readiness Plan Identify which competitors take the top-three slots Conga could occupy and what framing attributes AI systems associate with Conga versus those competitors.

Phase 3: Owned Answer Layer Buildout Develop owned content that positions Conga as a recommended option for contract management software discovery prompts, mirroring the framing that drives its Google AI Overviews strength.

Phase 4: Citation / Authority Layer Development Strengthen the external source footprint that supports Conga's recommendation eligibility, focusing on the evidence types that convert presence into placement.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track whether improvements in the citation and answer layers move Conga from mid-tier coverage toward top-three placement rates comparable to its Google AI Overviews performance.

Why This Matters

AI systems are increasingly shaping which contract management software vendors appear on buyer shortlists. Conga's presence in 26.14% of AI responses shows the brand is part of the conversation, but its 0.21% rank-one rate means it is almost never the first choice AI systems present to buyers. In a category where DocuSign, PandaDoc, and Ironclad dominate top placement, being mentioned without being recommended positions Conga as a secondary option rather than a primary contender.

The next move is targeted correction of the prompt, page, and citation layers that determine whether Conga converts its existing presence into recommendation placement. The brand's Google AI Overviews performance proves the evidence layer can support Conga as a recommended option. Extending that pattern across other platforms is the difference between being listed and being chosen.

Core Metrics

Sentiment Score

Questions This Section Answers

• How is Conga's net sentiment score calculated and why does it matter?
• Why does classifying mentions matter more than counting total share of voice?

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For Conga, this calculation is (88 × 1 + 38 × 0 + 0 × -1) / 126, producing a net sentiment score of 0.6984.

This score matters because unclassified mention counts are misleading. Conga's 126 total mentions include 38 neutral references where the brand appears without any positive or negative framing, and those neutral mentions do not represent recommendation strength. Share of voice is a diagnostic metric, not a business KPI; appearing in more responses means little if those appearances do not convert into recommendations. A positive recommendation, neutral reference, cautionary mention, and competitor-displaced mention are not equal, and counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, because the gap between Conga's 26.14% presence rate and its 15.77% recommendation coverage only becomes visible when mentions are separated from recommendations.

Sentiment by Platform

Questions This Section Answers

• Which platform gives Conga its strongest recommendation signal and why?
• Which AI platforms mention Conga as context without converting that presence into recommendations?

Methodology

1. Report orientation: This AI Company Market Strategy Report analyzes Conga's recommendation-stage visibility within the contract management software category, based on the LLM Authority Index AI Market Discovery Index public benchmark for September 2026.
2. Reporting window: Data reflects the September 2026 measurement cycle, with July 2026 and August 2026 referenced for movement analysis.
3. Platforms tracked: Six canonical AI and search surface families were tracked: ChatGPT, Microsoft Copilot, Google Gemini, Google AI Mode, Google AI Overviews, and Perplexity.
4. Observation count: The benchmark began with 800 prompt-surface observations, of which 712 were relevant and 88 were filtered as irrelevant, leaving 482 qualified benchmark observations as the public denominator.
5. Competitor universe: Ten brands were tracked: Agiloft, Conga, ContractSafe, ContractWorks, DocuSign, Icertis, Ironclad, Juro, LinkSquares, and PandaDoc.
6. Public clusters used: The September 2026 qualified observations fell entirely into the Best Contract Management Software Discovery cluster. The Pricing and Value and Multi-Brand Comparison clusters recorded zero qualified observations.
7. Stage 0 role: Prompt-level observations retained the query, AI surface, answer, brand outcome, recommendation placement, sentiment, and citations where exposed. Source presence is evidence about the information environment, not proof of causation.
8. Definition of a mention: A mention is any qualified observation where the brand appears in the AI answer, regardless of whether it receives recommendation credit.
9. Definition of a valid recommendation: A valid recommendation is a qualified observation where the brand receives bona fide recommendation credit, excluding passing mentions and neutral references.
10. Limitations: This public benchmark does not measure market share, attributable sales, every possible AI response, organic-search ranking, social mention volume, or private and sponsored channels. Metric movements do not establish causality. ContractWorks holds only 26 valid recommendations, so its coverage percentages carry more uncertainty than brands with larger counts.

See How AI Is Recommending Your Brand

The public benchmark shows where Conga stands in AI-generated recommendations, but category-level percentages cannot explain why the brand is mentioned more often than it is recommended. A company-level AI visibility audit maps the specific prompts, competitor displacement patterns, and evidence sources that determine whether Conga appears on buyer shortlists or remains a secondary reference. Understanding that gap is the first step toward closing it.