Grasshopper Appears in 33.0% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Answer Capsule

In November 2026, Grasshopper appeared in 150 of 455 AI answers included in the Business Phone Systems benchmark (32.97%). It received 85 recommendations (18.68%), with 15 Top 3 placements and 3 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 Grasshopper mentions, recommendations and placements compare with its Business Phone Systems peers?

Grasshopper recorded 150 mentions (32.97%) and 85 recommendations (18.68%) across 455 answers included in the benchmark. Top 3 placements numbered 15; first-place recommendations numbered 3. Framing among its mentions was 87 positive, 63 neutral and 0 negative.

Grasshopper appears in roughly a third of the answers and is recommended in about one in five, so its reach is real but its endorsement share is thinner than its mention share. That gap is the practical story: buyers hear the name, yet the answer does not always put it forward as a choice.

Placement is a separate and much narrower measure. Being named near the top of an answer is uncommon, and being named first is rarer still. Reach, endorsement and position should be read as three different signals rather than one score.

Wording around Grasshopper is largely positive or neutral, with no negative framing recorded. That is a helpful base, but positive wording alone does not amount to a recommendation. The agency would treat the endorsement gap, not the tone, as the priority to investigate.

What changed since last month

Questions This Section Answers

• How did Grasshopper 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 rather than as evidence of movement in either direction.

That matters for how the client reads the report. Nothing here shows improvement or decline, and nothing should be presented as a trend. The value of this month is that it fixes a starting point the next verified month can be measured against.

The agency would use this baseline to set expectations: future comparisons should be made only between months measured on the same basis, and any change should be described as an observed shift rather than explained away.

Step 1. Measure

Questions This Section Answers

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

AI answers contained 0 conflicting claims about Grasshopper: 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.

With no conflicting claims recorded about Grasshopper, the fact-checking workload is light, but the measurement step still earns its place. A visibility comparison shows where Grasshopper sits against the named competitors on mentions, endorsements and placement, which helps the client decide where effort is worth spending.

A short list of claims to verify keeps that comparison honest. Even where nothing is disputed, confirming the basic company facts that answers rely on protects against future drift.

The agency would build a simple scorecard pairing the visibility comparison with a claim-review list, each item carrying an owner and a status, so priorities rest on evidence rather than impression.

Step 2. Make the website consistent

Questions This Section Answers

• Which recorded claim differences about Grasshopper 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.

No disputed topics were supplied for this part of the analysis, so there is nothing to adjudicate and no page changes to recommend on that basis. The honest position is that the consistency question is open rather than settled.

The agency would not treat an AI answer as a statement of company fact. Before any page brief is written, the entity being described, the date of the claim and the underlying source would need to be confirmed, since differing dates can make two statements look like a conflict when they are not.

Where verification confirms a genuine inconsistency, a conditional page brief would follow; where it does not, the item closes with no change.

Step 3. Align the external narrative

Questions This Section Answers

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

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 are mostly third-party comparisons and competitor sites, alongside a video and a blog roundup. None carries a conflicting claim about Grasshopper, so this is a review list, not a correction list.

The agency would check each page's current contents before making any request, and would treat a citation as evidence that a page was referenced, not that it shaped the answer. Publisher control cannot be assumed, and a polite evidence-backed enquiry may reasonably end in no change.

Priority would go to the pages most often cited alongside Grasshopper, with requests framed around accuracy and usefulness to buyers rather than around placement.

Step 4. Optimize priority company pages

Questions This Section Answers

• Which observed Grasshopper website pages should receive review briefs?

The company's website was cited 21 times across 10 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.

Grasshopper's own site was cited across a small set of pages, and only a few of those citations sit inside answers that recommend the company. The homepage and one blog page account for the recommending citations; the rest were cited without an accompanying endorsement.

The agency would prepare page briefs for the listed pages using approved company facts and the questions buyers actually ask, checking existing coverage before proposing anything new. Pages cited without a recommendation are worth reviewing for whether they answer the buyer's decision question clearly.

A cited page is not automatically a page that drove a recommendation, so briefs would be judged on clarity and accuracy, not on an assumed effect.

Step 5. Publish around buyer questions

Questions This Section Answers

• Which observed buyer questions support content briefs for Grasshopper?

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

The recorded questions cluster tightly around choosing a small-business phone system or VoIP provider, with a smaller group about business phone numbers. Grasshopper is mentioned in most of these answers and recommended in several, which suggests the question space is familiar territory rather than unexplored ground.

These are answer observations, not search volume or proof of missing content. The agency would check what Grasshopper already publishes for each question before drafting anything, then write briefs that answer the buyer's decision directly and cite approved facts.

Where coverage already exists, the work becomes refinement rather than a new page.

Our 90-day action plan

Questions This Section Answers

• How should the agency sequence the proposed Grasshopper 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, an evidence requirement and a review status. Nothing is changed in this period.

The second month turns verified findings into approved page briefs and, where justified, publisher requests, with confirmed edits, no-change decisions, requests and responses recorded separately so the client can see what was actually done.

The third month adds buyer-question content briefs and a fresh scorecard. Completed work would be reported separately from measured answer outcomes, with the comparability limits stated plainly; no visibility gain is promised.

Methodology

Questions This Section Answers

• How are Grasshopper 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 455 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 5445 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 collection dates of the original answers are unverified. Rates rest on the answers that met the benchmark's inclusion rules, and a company counts as recommended only when an answer endorses it with positive wording; top-three and first-place counts sit inside those recommendations rather than adding to them.

Answers can name several companies, so company counts cannot be summed into a count of distinct answers. Sentiment describes answer wording, not customer satisfaction. Cited pages and any disputed claims still need independent checking, and the monthly samples differ, so comparisons show what was recorded, not why.

Our first three priorities

The first priority is to close the endorsement gap in understanding: establish why Grasshopper is mentioned far more often than it is recommended, using the scorecard and a review of the answers where it appears without endorsement. This is an investigation, not a conclusion.

The second is to verify before acting. The cited third-party pages and the company's own listed pages would be checked against current primary sources, with page briefs written only where approved facts support them and ambiguous matches left out of any correction queue.

The third is buyer-question content. Briefs would target the recorded small-business phone system and VoIP questions, checking existing coverage first, and would be judged on clarity and accuracy rather than on any promised change in AI answers.