Behind the Scenes of a Teacher Building Her First Online Course with Keyword Data

Jennifer teaches AP Biology, and last summer she decided to create supplementary video lessons for her students. What started as a simple project turned into a case study in using search data to build educational content that people actually need.

She didn't start with keyword research. She started by filming ten videos on topics she thought were challenging, based on her fifteen years of teaching experience. The topics made perfect sense to her—cellular respiration, photosynthesis, protein synthesis. Standard difficult concepts from the curriculum.

Then she tried to figure out what to title these videos for YouTube. She typed "cellular respiration" into YouTube's search bar and paid attention to what autocompleted. The suggestions weren't matching her video content at all. Students weren't searching for "cellular respiration overview." They were searching for "cellular respiration steps in order," "cellular respiration equation explained," "glycolysis vs krebs cycle difference."

This bothered her enough that she postponed the launch and started investigating what students actually needed help with. She created a document and began collecting real search queries. YouTube autocomplete became her primary research tool because that's where students go for video explanations.

For each major topic in her curriculum, she'd type the basic term plus common question words. "Why does," "what is the difference between," "how to remember," "how to solve." The patterns that emerged weren't what she expected from years in the classroom.

Students struggled most with connecting concepts, not learning them in isolation. Searches like "how does glycolysis connect to krebs cycle" and "where does electron transport chain happen in the cell" showed up repeatedly. They wanted the relationships explained, the spatial understanding, the sequence of events.

Jennifer then cross-referenced these YouTube searches with Google Trends to see seasonal patterns. Sure enough, certain topics spiked in September and again in January—exam prep periods. Other topics had consistent year-round interest, suggesting these were concepts students struggled with regardless of where they were in the curriculum.

She installed Keywords Everywhere, a Chrome extension that shows search volume data. This helped her prioritize which videos to create first. A search like "how to read a phylogenetic tree" showed 1,300 monthly searches with relatively few quality video results. That went to the top of her production list.

The real methodology shift happened when she started looking at question-based searches. She used a free tool called Also Asked that extracts "People also ask" questions from Google. For "DNA replication," it pulled 30+ related questions that students were asking. Half of them were about common misconceptions—"does DNA replication happen in mitosis," "why is DNA replication semiconservative," "what happens if DNA replication goes wrong."

She restructured her entire course outline based on these questions. Instead of teaching concepts in traditional textbook order, she organized modules around the specific confusion points that search data revealed. Each video would answer one clear question that real students were actually searching for.

Before filming anything new, she created a spreadsheet matching each planned video to its target search query, monthly search volume, and current top-ranking videos. This let her spot gaps where student demand existed but quality supply didn't.

The finished course had 34 videos, each titled with the exact question students were searching for, covering content in an order determined by search frequency and conceptual dependencies rather than traditional curriculum sequence.