Which Schema Types Still Earn Something
Rich result support has narrowed. Here is where markup still pays for itself.
Read: Which Schema Types Still Earn SomethingTechnical problems rarely announce themselves. They show up as content that should have worked and did not, and as a graph that flattened without anyone changing anything.
It removes the reasons a search engine cannot reach, render, understand or trust a page: pages that are not crawled, pages that are crawled but render empty, duplicate addresses competing for the same intent, and templates that load slowly enough to be measured as broken. None of it adds demand. All of it decides whether the rest of your work is visible.
Rich result support has narrowed. Here is where markup still pays for itself.
Read: Which Schema Types Still Earn SomethingMost migration losses are preventable with one spreadsheet made early enough.
Read: Build the Redirect Map Before the Design Is Signed OffWhy a perfect score in a testing tool can sit alongside a terrible experience for real users.
Read: Lab Scores Lie. Read Field Data InsteadSlow accumulation of small template decisions is what makes sites stop performing.
Read: Technical Debt Is an SEO Problem Long Before It Is a Developer ProblemPost-migration collapses are predictable and preventable. Almost all of them trace back to a redirect map nobody checked.
Read: How to Replatform Without Losing the Traffic You Paid ForThousands of weak URLs do not sit harmlessly in the background. They lower the ceiling for every strong page on the domain.
Read: Index Bloat Is a Quiet Tax on Everything You PublishThe useful discipline here is to separate removing a cap from adding a capability. Removing a cap is fast and provable: a template that was not rendering now renders, and the pages that were invisible appear within a crawl cycle. Adding a capability is slow and compounding, and it is the wrong thing to start with when a cap is still in place. Most technical audits fail because they list forty items without saying which two are actually holding the site down.
Field data settles most arguments. Lab scores describe a simulated device on a simulated connection; field data describes the devices your buyers actually hold. When the two disagree, the field data is the one that matches revenue. The pieces here lean on that distinction repeatedly, because the alternative is optimising a number nobody experiences.
Where this subject turns into something we are paid to do.
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