How AI Search Is Recommending Online Estate Planning and Wills: Monthly Trends

Executive Summary

Trust & Will remains the category leader for AI-driven recommendation in online estate planning, holding 76.9% valid recommendation coverage in August 2026, but its lead narrowed as several of the category's largest brands moved down together. The gap to the second-place brand narrowed to 7.5 points after Trust & Will dropped 8.3 points from July's 85.2% coverage, a significant decline.

The most consequential movement this month came not from a single gain but from a broad decline across the category. Six tracked brands recorded significant declines from July to August, led by Rocket Lawyer, which fell 24.3 points to 42.4% coverage, and Quicken WillMaker & Trust, which dropped 20.7 points to 55.7%. Six of the ten tracked brands moved down together this month, a pattern the benchmark records as a shift in the measured output distribution across the category rather than the result of one or two brands' individual performance.

The sole significant riser was Tomorrow, which moved from 0.0% to 2.3% coverage, a small but measurable entry into the recommendation landscape. Fabric, Wealth.com, and Willing remained stable, with Willing appearing in recommendations for the first time after having zero coverage in July.

Trust & Will and LegalZoom still lead the category, though their combined dominance narrowed relative to July. The benchmark records six significant declines concentrated among the largest brands; the data does not establish why AI systems produced this distribution this month.

Each monthly run begins with 800 prompt-surface observations (666 unique questions in July, 687 in August) across the benchmark's defined AI/search surface universe. Of those, all 800 mentioned a tracked brand or competitor in both months; 371 were relevant and 429 irrelevant in July, versus 396 relevant and 404 irrelevant in August. The public metrics use the 297 qualified observations in July and 307 in August that survive both qualification stages.

Key Findings

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

Benchmark-Level Metrics

The recommendation-shaped answer share rose in August even as the valid recommendation shortlist share fell, meaning AI systems produced more recommendation-oriented output while a smaller proportion of that output qualified as a valid shortlist. The category leader's decline was significant, but the leader position itself did not change hands.

AI Recommendation Trend

Category leadership held, but the field tightened as six of ten brands posted significant declines

August's category-level change came from the combination of several significant declines rather than a single dominant movement. Six brands moved beyond normal month-to-month variation, all in the same direction, producing a broad redistribution of measured recommendation credit across the category.

What Changed This Month

Trust & Will: Leader retained, lead narrowed

Trust & Will's valid recommendation coverage fell from 85.2% in July to 76.9% in August, a significant 8.3-point decline. The brand's top-three rate dropped 14.0 points to 67.1%, yet its rank-one rate rose slightly from 29.3% to 30.6%, suggesting that when Trust & Will is recommended, it is still frequently the first choice.

The brand's raw mention presence remained high at 93.8%, down only 2.8 points from July's 96.6%. This distinction matters: Trust & Will is still nearly always named, but the depth of that recommendation has weakened.

Highest-priority diagnostic: Which specific prompts shifted from a Trust & Will top-three recommendation to a lower placement or no recommendation, and which brand captured those slots?

LegalZoom: Broad erosion across presence and placement

LegalZoom fell from 80.8% to 69.4% coverage, an 11.4-point significant decline. The erosion was consistent across metrics: raw presence dropped 5.0 points to 87.6%, top-three rate fell 13.2 points to 53.8%, and rank-one rate dropped 10.3 points to 15.6%.

LegalZoom still holds second place, but its average recommended rank slipped slightly.

Highest-priority diagnostic: Which evidence sources or prompt types drove the 10.3-point drop in rank-one recommendations, and where did those first-place slots go?

Quicken WillMaker & Trust: Sharpest drop among the middle tier

Quicken WillMaker & Trust fell 20.7 points from 76.4% to 55.7% coverage, a significant decline. Raw mention presence dropped 19.5 points to 60.6%, meaning the brand simply stopped appearing in a large share of responses altogether.

The top-three rate fell 8.5 points to 41.0%, while rank-one rate eased 3.2 points to 5.9%. The pattern suggests the brand is being excluded from more answers entirely rather than being displaced to lower positions.

Highest-priority diagnostic: Which prompt categories now omit Quicken WillMaker & Trust entirely, and what does the competitive landscape look like in those responses?

Rocket Lawyer: Largest percentage-point decline

Rocket Lawyer's coverage fell 24.3 points from 66.7% to 42.4%, the largest single decline in the category. Raw mention presence dropped 23.7 points to 52.4%, indicating the brand vanished from nearly a quarter of the responses where it previously appeared.

The top-three rate held relatively steady at 10.1%, down only 0.7 points, meaning when Rocket Lawyer is mentioned, it still makes the top tier at a similar rate. The decline is in presence, not placement quality.

Highest-priority diagnostic: Why did AI systems stop mentioning Rocket Lawyer in roughly a quarter of responses where it previously appeared, and which brands captured that presence?

FreeWill: Significant decline despite stable sentiment

FreeWill dropped 9.0 points from 74.1% to 65.1% coverage. Raw presence eased 4.9 points to 74.6%, and top-three rate slipped 2.3 points to 37.1%. However, the rank-one rate actually rose 1.3 points to 20.2%.

FreeWill holds third place and maintains strong sentiment (0.9 net sentiment score), but its recommendation footprint narrowed. The brand remains highly valued when mentioned but is appearing in fewer responses.

Highest-priority diagnostic: Which surface family reduced FreeWill's presence, and is the decline concentrated in specific prompt types?

GoodTrust: Significant decline from a smaller base

GoodTrust fell 6.3 points from 12.8% to 6.5% coverage, a significant decline. The drop was driven by raw presence, which fell 6.3 points to 8.5%, while the top-three rate held at 1.0%. GoodTrust's absolute valid recommendation count fell from 38 to 20 observations.

Highest-priority diagnostic: Which prompts previously featured GoodTrust that now omit it, and is the decline concentrated on a particular AI surface?

Tomorrow and Willing: New entrants to the recommendation set

Tomorrow moved from 0.0% to 2.3% coverage, with 7 valid recommendations in August versus none in July. The brand's raw presence rose from 0.3% to 2.9%. Willing appeared for the first time with 1.0% coverage and 3 valid recommendations.

These are small counts, but they represent entry into a recommendation set that previously excluded both brands entirely.

Highest-priority diagnostic: For Tomorrow, which prompts produced its first recommendations, and what attributes did AI systems cite? For Willing, is this a one-off appearance or the start of a trend?

Stable brands: Fabric, Wealth.com, Willing

Fabric rose a modest 0.8 points to 6.2% coverage with 19 valid recommendations. Wealth.com held at 0.3% with 1 valid recommendation. Willing's 1.0% coverage represents 3 valid recommendations, a small but real presence.

Highest-priority diagnostic: For Fabric, which prompts produce its steady top-three appearances, and can those patterns be extended to other prompt categories?

Buyer-Intent Interpretation

All qualified observations in both July and August fell into the Brand Recommendation cluster. No observations qualified for Pricing & Value or Multi-Brand Comparison clusters. The public benchmark therefore answers which brand AI systems recommend, but it cannot yet distinguish how price sensitivity or direct comparison dynamics influence those recommendations. The commercial questions of cost, value, and head-to-head trade-offs remain outside the scope of the current public data.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Market Discovery research program.

• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• The qualified benchmark set (307 observations in August) is smaller than the raw collection universe (800 prompt-surface observations), and brand-level percentages are calculated within the qualified set.
• Small-count movements, such as Willing at 1.0% coverage (3 valid recommendations), should be interpreted with caution.
• Directional analysis identifies changes worth investigating; it does not establish cause.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

The aggregate percentages reveal which brands gained or lost recommendation credit in August, but they do not explain the mechanics behind those movements. Which high-intent prompts are being won, which competitor takes the recommendation when a brand loses, what attributes AI systems associate with each option, and which external sources shape those answers are the questions that sit beneath the category-level numbers.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It turns the benchmark's directional signals into actionable intelligence for a single brand's position in the AI recommendation landscape.

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