Conga Appears in 27.5% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Answer Capsule

In November 2026, Conga appeared in 103 of 375 AI answers included in the Contract Management Software benchmark (27.47%). It received 36 recommendations (9.60%), with 15 Top 3 placements and 2 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

• How do Conga mentions, recommendations and placements compare with its Contract Management Software peers?

Conga recorded 103 mentions (27.47%) and 36 recommendations (9.60%) across 375 answers included in the benchmark. Top 3 placements numbered 15; first-place recommendations numbered 2. Framing among its mentions was 37 positive, 60 neutral and 6 negative.

Conga appears in roughly a quarter of the answers reviewed, which gives it real reach, but the gap between being mentioned and being recommended is wide. Many answers bring Conga into the discussion without endorsing it, so the practical task is to turn recognition into affirmative recommendation rather than to chase more mentions.

Placement is a separate matter again. Conga rarely lands at the top of a shortlist, and first-place finishes are scarce. Buyers who see Conga named alongside stronger-positioned rivals may treat it as a fallback. The agency would build a scorecard that tracks reach, recommendation and position as distinct measures so progress in one is not mistaken for progress in another.

What changed since last month

Questions This Section Answers

• How did Conga counts and coverage differ across the available monthly snapshots?

Only months with verified results are shown. Monthly sample coverage is listed in Methodology.

From October 2026 to November 2026, Conga's mention count fell from 129 to 103, while its recommendation count fell from 88 to 36. The recommendation rate was 18.30% and 9.60% respectively.

The monthly record shows Conga's mention count easing in the latest sample while its recommendation count dropped more sharply. The recommendation rate moved down alongside it. These are observed movements in separate samples, and the comparability limit matters: the answer sets differ between months, so the change in counts should not be read as a cause-and-effect story.

What the record does support is a caution against treating the earlier recommendation level as settled. The agency would keep the monthly scorecard in place and watch whether the recommendation pattern holds across further samples before drawing conclusions or adjusting strategy.

Step 1. Measure

Questions This Section Answers

• What should the agency measure and verify first for Conga?

AI answers contained 0 conflicting claims about Conga: 0 critical, 0 high, 0 medium, 0 low. Of these, 0 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

No conflicting claims about Conga surfaced in the captured answers, so there is no immediate fact-check backlog to clear. That is a clean starting position, but it also means the measurement work should focus on comparison rather than repair: where Conga sits against named rivals, and which claims in answers deserve verification before they are repeated in client content.

The agency would produce a visibility comparison and a short list of claims worth checking against primary sources. That gives the client a defensible basis for deciding where to invest, without treating an AI answer as proof of anything.

Step 2. Make the website consistent

Questions This Section Answers

• Which recorded claim differences about Conga should be verified before proposed page edits?

No results are available for this part of the analysis.

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

This part of the analysis returned no results, so there are no disputed topics to work through for Conga at present. The absence of findings is not evidence that the website is accurate; it means nothing was flagged in this pass.

The agency would still verify company facts against current primary sources before any page work begins. Where an apparent conflict does emerge later, the entity, date and source need resolving first, since different dates can explain an apparent discrepancy. Page briefs would be drafted only after that verification, and only for topics the evidence actually supports.

Step 3. Align the external narrative

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• Which cited third-party pages are relevant to fact review for Conga?

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

The cited pages selected for review cluster around competitor-comparison and alternatives content, which is where buyers often form a shortlist. None of these pages is linked to a conflicting claim about Conga, and a citation does not show that a page influenced an answer. Their current contents still need checking before any request is considered.

The agency would review each page against primary sources and prepare evidence-backed requests only where a genuine inaccuracy is confirmed. Publishers control their own pages, so the work is a justified approach, not an assumption of error or of editorial control.

Step 4. Optimize priority company pages

Questions This Section Answers

• Which observed Conga website pages should receive review briefs?

The company's website was cited 73 times across 23 distinct page addresses; the table shows 8 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

Conga's own site is cited widely, and one blog page accounts for most of that activity. That concentration is useful: it shows which page the answers lean on and where a brief would have the most leverage. The other selected pages, including product and comparison pages, are cited far less and should be assessed on their own merits.

The agency would prepare page briefs using approved facts and the questions buyers actually ask, starting with the most-cited page. A cited page is not automatically one that accompanied a recommendation, so briefs would be prioritized by relevance rather than citation volume alone.

Step 5. Publish around buyer questions

Questions This Section Answers

• Which observed buyer questions support content briefs for Conga?

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

The recorded questions are broad category questions about the best contract management and contract lifecycle management software, plus document automation. Conga is mentioned and recommended in several of these, which suggests the category conversation is where its visibility is won or lost.

The agency would check existing coverage before proposing anything new, then draft buyer-question content that answers these questions directly with approved facts. These are recorded answer observations, not search volume or proof of a content gap, so briefs would be framed as opportunities to test rather than certain wins.

Our 90-day action plan

Questions This Section Answers

• How should the agency sequence the proposed Conga work and judge completion?

The first month establishes the baseline: a scorecard, a scoped fact-review register and a shortlist of pages and sources, each with an owner and a clear evidence requirement. Nothing is corrected or requested until that groundwork is reviewed.

The second month turns verified findings into approved page briefs and justified publisher requests, with confirmed edits, no-change decisions and responses recorded separately. The third month adds buyer-content briefs and a fresh scorecard. Completed work is reported apart from measured answer outcomes, since delivered deliverables do not guarantee a visibility change.

Methodology

Questions This Section Answers

• How are Conga answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 375 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 5498 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

Monthly sample coverage:

Reliable results for August 2026 are unavailable. This is a gap in the history, not a result of zero.

The answer samples differ between months. These comparisons show how the recorded results changed; they do not establish why they changed.

The answer samples differ between months, so month-to-month comparisons describe what was recorded, not why it changed. A company counts as recommended only when an answer endorses it with positive wording, and top-three and first-place results sit inside those recommendations rather than adding to them.

Answers can mention several companies, so counts cannot be summed into distinct answers. The current contents of cited pages and any disputed claims still need independent verification before action.

Our first three priorities

First, verify before acting. The agency would confirm company facts and the current contents of the most-cited pages against primary sources, so any later brief or publisher request rests on checked evidence rather than an AI answer.

Second, concentrate page work where the answers already lean. A brief for the most-cited blog page, built on approved facts and buyer questions, offers the clearest place to improve how Conga is presented when it is discussed.

Third, treat recommendation as the measure to move, not mentions. Buyer-question content aimed at the category questions where Conga already appears gives the best chance of turning recognition into endorsement, with the scorecard tracking reach, recommendation and position separately.