Keap Appears in 10.3% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Answer Capsule

In November 2026, Keap appeared in 28 of 272 AI answers included in the CRM Software benchmark (10.29%). It received 5 recommendations (1.84%), with 0 Top 3 placements and 0 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 Keap mentions, recommendations and placements compare with its CRM Software peers?

Keap recorded 28 mentions (10.29%) and 5 recommendations (1.84%) across 272 answers included in the benchmark. Top 3 placements numbered 0; first-place recommendations numbered 0. Framing among its mentions was 11 positive, 17 neutral and 0 negative.

Keap appears in roughly one answer in ten, but it is almost never the brand an answer puts forward. Mentions are frequent enough to show the name is in the conversation; recommendations are rare, and no answer placed Keap at the top of a shortlist. Reach and endorsement are clearly separate here.

Framing is not the obstacle. Most mentions are neutral and the rest are positive, with nothing negative recorded. The gap sits between being named and being endorsed, so the useful work is understanding which questions produce a recommendation and what evidence those answers lean on.

We would build a scorecard that separates mentions, recommendations and placements, then trace the questions where Keap is recommended to see what those answers cite. That gives the client a defensible starting point rather than a single blended score.

What changed since last month

Questions This Section Answers

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

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

There are insufficient usable monthly observations for a prior-period comparison.

Only one month of verified results is available, so there is no prior period to compare against. The current figures stand as a baseline, not as evidence of movement in either direction. Any future change should be read against this starting point.

Because the monthly samples are selected separately, later comparisons will describe what was recorded without explaining why counts or rates shifted. We would keep the baseline scorecard fixed so future months are measured the same way.

The practical value of this month is that it establishes where Keap sits before any work begins, which makes later reporting honest about what changed and what did not.

Step 1. Measure

Questions This Section Answers

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

AI answers contained 1 conflicting claim about Keap: 0 critical, 0 high, 1 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.

The benchmark surfaced a single conflicting claim about Keap, rated medium priority. That is a manageable starting point: one topic to check rather than a backlog. The rating orders the fact-checking work; it does not mean anyone published an error.

We would pair the visibility scorecard with a short list of claims worth verifying, each tied to the answer that raised it. The client then sees which gaps are about being recommended and which are about being described accurately.

That separation matters because the two problems need different work. Accuracy issues call for verification against primary sources; endorsement gaps call for content and evidence that answers can draw on.

Step 2. Make the website consistent

Questions This Section Answers

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

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.

The disputed topic is entry-level monthly pricing, where recorded answers give different figures. Both are quotations from AI answers, not confirmed company facts, and different dates or plan definitions could account for the difference.

We would verify the current published price and its effective date before proposing any change. If the website already states it clearly, the brief may be about making the pricing page easier to quote accurately rather than correcting it.

Only after that check would we draft a conditional page brief, with the approved figure, its date and the plan it applies to stated plainly. No correction is proposed until the primary source confirms one.

Step 3. Align the external narrative

Questions This Section Answers

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

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.

Several third-party pages were selected for review because they relate to Keap in captured answers, including review sites, comparison posts and a business publication. Each was cited once, and each is linked to the conflicting pricing claim. That link does not establish that any page caused the conflict.

We would check the current contents of these pages before deciding whether any request is warranted. Where a page is out of date, an evidence-backed request with the verified figure is reasonable; where it is accurate, no action is the right outcome.

Publisher control is never assumed. Requests are recorded separately from responses, and a page that merely appears alongside a claim stays out of the correction queue.

Step 4. Optimize priority company pages

Questions This Section Answers

• Which observed Keap website pages should receive review briefs?

The company's website was cited 20 times across 14 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.

Keap's own site was cited across many distinct addresses, with the homepage, the CRM explainer and the pricing page drawing the most appearances. None of those citations came from answers that recommended Keap, which suggests the site is being used for description rather than endorsement.

We would prepare page briefs for the priority pages using approved facts and the questions buyers actually ask. The pricing page brief would carry the verified figure and its date; the CRM explainer would state plainly what the product does and who it suits.

Briefs describe proposed work. Whether revised pages change answer behaviour is a separate question that only later measurement can address.

Step 5. Publish around buyer questions

Questions This Section Answers

• Which observed buyer questions support content briefs for Keap?

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

The recorded questions cluster around two themes: broad top-CRM lists and specific cost questions about Keap. Keap is mentioned in several list answers and recommended in a few, while the cost questions mention it without a recommendation.

We would check existing coverage before proposing anything new. Where a cost page already exists, the brief is about making it quotable; where list-style questions dominate, the work is evidence that helps an answer justify an endorsement.

These are recorded answer observations, not search volume or proof that the website lacks content. Briefs would be written around the buyer's question, with approved facts and clear comparisons.

Our 90-day action plan

Questions This Section Answers

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

The first month establishes the baseline scorecard, a scoped fact-review register and a shortlist of pages and sources, each with an owner and a review status. Nothing is corrected in this period; the work is verification and prioritisation.

The second month produces approved page briefs and any justified publisher requests, with confirmed edits, no-change decisions, requests and responses recorded separately. The third month adds buyer-question content briefs and a fresh scorecard.

Delivered work is reported as work completed, kept apart from measured answer outcomes. No visibility gain is promised, and later comparisons will carry their comparability limits.

Methodology

Questions This Section Answers

• How are Keap 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 272 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 5143 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:

July 2026 measured a different set of companies, so it is excluded from this comparison. August 2026 measured a different set of companies, so it is excluded from this comparison. September 2026 measured a different set of companies, so it is excluded from this comparison. October 2026 measured a different set of companies, so it is excluded from this comparison.

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

The report covers a single month, and the exact dates the answers were collected are unverified. Rates use the answers that met the benchmark's inclusion rules, and a company counts as recommended only when an answer endorses it with positive wording. Placements sit inside recommendations rather than adding to them.

Answers can name several companies, so company counts do not sum to distinct answers. Citation appearances across all captured answers differ from benchmark citations. Cited pages and disputed claims still need independent verification, and monthly samples are selected separately, so comparisons show what was recorded, not why.

Our first three priorities

First, verify the entry-level pricing claim against the current primary source, including its date and plan, before any correction is considered. This is the one accuracy issue the evidence raises, and it should be settled before page or publisher work begins.

Second, prepare page briefs for the homepage, CRM explainer and pricing page, using approved facts and the buyer questions recorded in the research. The aim is to give answers clear, quotable material that supports an endorsement rather than only a description.

Third, build buyer-question content around cost and CRM selection, checking existing coverage first. Throughout, keep mentions, recommendations and placements as separate measures so progress is read honestly.