Case Study: Ranking Gains Across 10 State Markets
Aligning content to real search intent and implementing structured data and FAQ markup improved average search position across ten independent Taylor Morrison state markets over the comparison period. Nine markets improved by 55.5% to 65.8%, while seven also recorded meaningful click-through rate gains ranging from 18% to 104%.
Average search position improved in every state reviewed. Nine of the ten markets moved into a tight 55.5% to 65.8% improvement range, while Oregon improved by 46.1%. Click-through rate also increased in seven markets, remained flat in two, and declined in one.
State | Avg. Position — Prior | Avg. Position — Now | Position Change | CTR — Prior | CTR — Now | CTR Change |
Florida | 31.6 | 10.8 | -65.8% | 4.1% | 5.6% | +37% |
Georgia | 35.5 | 12.2 | -65.6% | 3.2% | 4.0% | +25% |
Nevada | 36.4 | 13.2 | -63.7% | 2.4% | 4.9% | +104% |
Indiana | 32.4 | 12.1 | -62.7% | 1.9% | 3.8% | +100% |
Colorado | 35.7 | 14.0 | -60.8% | 2.1% | 2.8% | +33% |
North Carolina | 34.6 | 13.7 | -60.4% | 3.4% | 3.4% | Flat |
Texas | 35.1 | 14.9 | -57.5% | 2.8% | 3.3% | +18% |
Arizona | 28.9 | 12.6 | -56.4% | 4.2% | 4.3% | Flat |
Washington | 37.1 | 16.5 | -55.5% | 1.9% | 2.7% | +42% |
Oregon | 41.2 | 22.2 | -46.1% | 2.2% | 1.9% | -14% |
The data comes from Google Search Console’s Performance dashboard using the same comparison for every market: the most recent three months versus the same three months one year earlier, with Search type set to Web.
Why this matters more than a single number
A large percentage from one market can be influenced by unusual local conditions, a temporary demand shift, or a reporting anomaly. A similar ranking pattern across multiple independent markets is harder to dismiss that way.
Nine states independently landed inside a relatively narrow 55.5% to 65.8% position-improvement range.
The value of this case study is therefore not one unusually large number. It is the consistency of the pattern across different markets, competitive conditions, inventory mixes, and local buyer behavior.
What actually drove the improvement
The ranking gains followed a separate initiative focused on aligning pages more closely with real search intent and making important information easier for search engines to interpret. The work included content restructuring, structured data implementation, and FAQ markup across relevant page types.
This initiative was distinct from the cannibalization work documented in another case study.
Content aligned to actual search intent
Pages were evaluated against the searches they were expected to satisfy rather than optimized around isolated keywords.
That meant asking questions such as:
- What is the buyer actually trying to find?
- Is the current landing page the right page for that search?
- Does the page answer the buyer’s main questions quickly?
- Is the content specific enough to the market, community, or product?
- Are informational and commercial intents being handled by the correct page types?
The objective was to reduce the gap between what users searched for and what the ranking page actually delivered.
Content was then rebuilt around the intent behind the query instead of simply increasing keyword frequency.
Structured data implementation
Structured data was added or improved where it could describe visible page content and relationships more clearly.
The purpose was not to add markup for its own sake.
The implementation focused on making important entities and page information easier for search systems to interpret consistently.
That work supported the broader content strategy by creating a clearer machine-readable representation of information already available to users.
FAQ markup
Frequently asked questions were added where they reflected genuine buyer concerns and strengthened the usefulness of the page.
The FAQ sections were designed to answer common questions directly and make individual passages understandable on their own.
That structure also made important answers easier for traditional search systems and AI-driven retrieval systems to extract.
FAQ markup supported the content, but the underlying value came from answering useful questions clearly rather than from markup alone.
Three markets with mixed click-through results, and why
Oregon, Arizona, and North Carolina still recorded strong average-position gains, but their click-through rate improvement was weaker than in the other markets.
Those markets are included intentionally rather than removed from the case study.
The ranking pattern remained positive. The difference appeared primarily in what happened after the listing became visible.
Why position, not just clicks, is the core proof point
Average position is the cleanest recurring signal in this analysis because it improved across all ten state markets.
Clicks and CTR remain important, but they depend on more than ranking alone.
A page can improve significantly in search position while click behavior is influenced by advertising, maps, AI answers, local demand, inventory, pricing, competitor messaging, or other changes in the search results.
That is why the primary proof point in this case study is consistency of ranking improvement.
The work was associated with better average search position in every market reviewed, including the three markets where CTR gains were flat or negative.
That pattern gives a more direct read on whether the technical and content changes improved organic search competitiveness.
What this means for multi-market home builders
Multi-market SEO should not be evaluated only at the national-domain level.
A company may improve overall while individual state or metro markets behave very differently.
Market-level measurement makes those differences visible.
It allows a builder to identify:
- markets where ranking improvements are translating into stronger engagement
- markets where rankings are improving but buyer response remains weak
- markets affected by inventory constraints
- new markets that need more time to mature
- areas where local competition may require a different strategy
The result is a more useful operating model than reporting one blended national percentage.
How this applies to regional and single-market builders
The same underlying approach applies even when a builder operates in only one or two markets.
The scale changes, but the principles do not:
- align content with actual buyer intent
- assign each page a clear search role
- structure information so search systems can interpret it
- answer buyer questions directly
- measure results against a consistent baseline
A single-market builder will not have ten independent state datasets to demonstrate repeatability.
It can still use the same process to determine whether search visibility is improving in its own communities, pages, and local market.
Frequently Asked Questions About This Case Study
Why does this case study show 10 states instead of one number?
Multiple markets provide a stronger test of whether the underlying pattern is repeatable.
One large result can be influenced by unusual local conditions. Similar ranking improvement across ten independently operating markets makes a single anomaly or short-term fluctuation a less convincing explanation.
What caused the position improvement specifically?
The documented initiative focused on aligning content more closely with actual search intent, implementing structured data, and adding useful FAQ content and markup.
Those changes were separate from the earlier cannibalization initiative documented elsewhere in the case-study library.
Why did three states see smaller click-through gains?
Oregon had more limited remaining inventory, while Arizona and North Carolina were among the newer and more actively expanding markets during the period.
Those factors plausibly contributed to weaker click-through improvement, but no single cause fully explained all three markets.
CTR also depends on buyer demand, inventory, competitors, SERP conditions, and other factors outside direct SEO control.
Does this apply to a single-market or regional builder?
Yes. Search engines still need pages to match buyer intent clearly and provide structured, understandable information regardless of company size.
A smaller builder will have fewer markets to compare, but the content and technical principles are the same.
How long did it take to see these results?
This comparison reflects roughly one year of cumulative work by comparing the most recent three-month period with the same period one year earlier.
Individual improvements can appear earlier, but the time required varies by market, competition, page history, implementation speed, and the scope of changes.
Who led the work across all ten markets
Cristobal Varela led this work directly as in-house SEO manager at the national home builder documented across all ten states here. Meet the strategist behind the data.
Next step
Request a Home Builder SEO Forecast
If your SEO forecast feels unclear, inconsistent, or hard to trust, the issue may not be SEO alone.
Your data, paid media strategy, branded traffic, page structure, technical implementation, or tracking setup may be making the picture harder to understand.
Link Socially can help you build a clearer forecast and a stronger organic growth strategy.