Old Republic Home Protection Appears in 18.5% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Answer Capsule

In November 2026, Old Republic Home Protection appeared in 120 of 649 AI answers included in the Home Warranties benchmark (18.49%). It received 115 recommendations (17.72%), with 51 Top 3 placements and 17 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 Old Republic Home Protection mentions, recommendations and placements compare with its Home Warranties peers?

Old Republic Home Protection recorded 120 mentions (18.49%) and 115 recommendations (17.72%) across 649 answers included in the benchmark. Top 3 placements numbered 51; first-place recommendations numbered 17. Framing among its mentions was 116 positive, 4 neutral and 0 negative.

Old Republic Home Protection sits in the lower half of the tracked set, well behind the leaders on both mentions and recommendations. Its positive framing is strong, so the gap is reach rather than tone: answers that do discuss the company tend to speak well of it.

Placement is the sharper constraint. The company appears in shortlists far more often than it takes the top spot, which suggests answers treat it as a credible option rather than a leading pick. Proposed work should test whether approved facts about coverage and pricing can support stronger positioning in comparison-style answers.

Because a recommendation requires affirmative endorsement, the recommendation figure is the one to manage. We would build a scorecard that tracks mentions, recommendations and placement separately so the client can see which measure moves.

What changed since last month

Questions This Section Answers

• How did Old Republic Home Protection 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, Old Republic Home Protection's mention count fell from 144 to 120, while its recommendation count fell from 122 to 115. The recommendation rate was 17.58% and 17.72% respectively.

The November sample recorded fewer mentions and slightly fewer recommendations than October, while the recommendation rate held roughly steady. Top-three placements were unchanged in count and first-place placements rose by a small margin. These are separate selected samples, so the movement should be read as a record of what was observed, not as a trend with a known cause.

The comparability limit matters here: the answer samples differ between months, and the report does not establish why counts or rates changed. We would treat November as the working baseline and avoid drawing conclusions from a single month-to-month step.

Proposed work is to keep the monthly scorecard running and flag any movement that persists across several samples before the client reacts to it.

Step 1. Measure

Questions This Section Answers

• What should the agency measure and verify first for Old Republic Home Protection?

AI answers contained 4 conflicting claims about Old Republic Home Protection: 0 critical, 0 high, 4 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.

Four conflicting claims about the company appeared in captured answers, all rated medium priority. None were rated critical or high, so the fact-checking list is manageable rather than urgent. The ratings order the work; they do not establish that the company or any publisher made an error.

A visibility comparison alongside that claim list would let the client see where the company stands relative to peers and which disputed topics are worth resolving first. We would propose a scoped fact-review register that records each claim, its source and an owner, with resolution decided only after checking current primary sources.

That combination gives the client a priority order grounded in evidence rather than in the loudest claim.

Step 2. Make the website consistent

Questions This Section Answers

• Which recorded claim differences about Old Republic Home Protection 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 topics cluster around customer rating, monthly price and HVAC coverage limits on lower plans. Each pair of recorded claims is a conflict between AI answers, not a verified statement about the company. Some apparent conflicts may reflect different dates or plan tiers, so entity and date need resolving before any correction is considered.

We would propose verification against current primary sources for each topic, then conditional page briefs only where the company's own approved facts support a clearer statement. Where the evidence is ambiguous, the topic stays out of the correction queue.

This keeps the website work tied to facts the client can stand behind.

Step 3. Align the external narrative

Questions This Section Answers

• Which cited third-party pages are relevant to fact review for Old Republic Home Protection?

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 include large comparison and review sites plus a company-specific comparison page. Several carry conflicting claims linked to them, but a page linked to a claim is not necessarily its cause, and the same answer can touch more than one page. Current contents still need checking before any request is made.

We would prioritize the pages that appear most often in answers mentioning the company, then prepare evidence-backed requests describing the specific claim and the approved fact. Publisher review is proposed work, not an assumption of control or error.

Requests should be framed as corrections only where verification supports them; otherwise they become no-change decisions recorded for the client.

Step 4. Optimize priority company pages

Questions This Section Answers

• Which observed Old Republic Home Protection website pages should receive review briefs?

The company's website was cited 8 times across 3 distinct page addresses; the table shows 3 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.

The company's own site was cited a handful of times across a few page addresses, with the homepage accounting for most of them. That is a thin footprint relative to the external pages, and a cited page is not automatically one that accompanied a recommendation.

We would propose page briefs for the homepage and the state brochure pages, built from approved facts and the buyer questions observed in the research. Each brief would state the audience question, the approved answer and the evidence behind it, and would check existing coverage before proposing new content.

This work is about making the company's own material easier for answers to use, not about promising a citation outcome.

Step 5. Publish around buyer questions

Questions This Section Answers

• Which observed buyer questions support content briefs for Old Republic Home Protection?

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

The observed questions are mostly state-specific best-company questions plus general best-reviews and highest-rated questions. The company was mentioned and recommended in several of these answers, which suggests the topics are relevant to its audience even though the observations are not search volume or proof of missing content.

We would propose buyer-question content briefs for the states where the company already appears, checking existing pages first. Each brief would answer the question directly with approved facts and link to the relevant coverage detail.

Where the company does not appear in an observed answer, that is a prompt to review coverage, not a finding that a page is missing.

Our 90-day action plan

Questions This Section Answers

• How should the agency sequence the proposed Old Republic Home Protection work and judge completion?

The first month produces the baseline scorecard, a scoped fact-review register and a shortlist of pages and sources, each with an owner and review status. The second month turns verified facts 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. Work completed is recorded apart from measured answer outcomes, and comparability limits stay visible beside any month-to-month reading.

Reviewers are the client's own subject experts for factual approval, with our team preparing briefs and requests. Delivered work is not a guarantee of visibility gains.

Methodology

Questions This Section Answers

• How are Old Republic Home Protection 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 649 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 4875 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.

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

The report covers the reporting period, and the exact dates the original answers were collected have not been verified. Rates use answers that met the benchmark's inclusion rules. A recommendation requires both endorsement and positive wording, and top-three and first-place counts sit inside recommendations rather than adding to them.

Answers can mention several companies, so company counts cannot be summed into distinct answers. Sentiment describes answer wording, not customer satisfaction. Citation appearances across all captured answers differ from benchmark answers citing a page, and cited page contents and disputed claims still need independent verification. Monthly samples differ, so comparisons show what changed, not why.

Our first three priorities

First, verify the four medium-priority claims against current primary sources and resolve entity and date before deciding whether any correction is warranted. Ambiguous matches stay outside the queue.

Second, prepare page briefs for the homepage and state brochure pages using approved facts and the observed buyer questions, checking existing coverage first. This addresses the thin owned footprint without assuming new pages are needed.

Third, review the most-cited external pages and prepare evidence-backed requests only where verification supports them, recording responses and no-change decisions. A fresh scorecard then shows what was delivered, kept separate from measured answer outcomes.