The Scale and Specificity of the Request
Building a keyword dataset at the 100,000-entry mark isn't a matter of running a single Ahrefs report. It requires a structured approach to seed expansion, categorical organization, and layered filtering — especially when every keyword must meet precise performance thresholds.
The client's requirements were clear: focus on Amazon product review-style queries, keep monthly search volume above 10, and hold keyword difficulty below 20. That combination rules out a large portion of what any keyword tool surfaces by default, which means the extraction process had to be both systematic and selective.
How We Built the Dataset
Helion360 began by identifying the structural patterns that define Amazon product review keywords — primarily comparative and superlative constructions across consumer product niches. From there, we built out seed lists by category and ran targeted Ahrefs exports with the defined filters applied at each stage.
Rather than pulling everything at once and filtering after the fact, we worked in category-based batches. This kept the data clean from the start and made it easier to track coverage across niches. Each batch went through a quality check before being added to the master file, ensuring no entries slipped through that didn't meet the original criteria.
Once all batches were consolidated, we ran a full deduplication pass and formatted the output into a clean, structured spreadsheet — sortable by volume, KD, and category for immediate use.
What Was Delivered
The final deliverable was a 100,000-keyword dataset, fully verified against the client's criteria. Every entry carried a search volume above 10 and a KD score under 20, with keyword intent aligned to Amazon product review content. The file required no additional cleanup — it was ready to plug directly into a product introduction deck or keyword mapping workflow.
For projects like this, the value isn't just in the volume — it's in the accuracy and usability of the data. A raw dump of 100,000 unfiltered keywords would have been far easier to produce. What took precision was making sure every single entry was genuinely useful.
Working With Helion360
If you're working on a large-scale keyword research project with strict filtering requirements, Helion360 has the process and the tools to get it done accurately and at volume. We've handled datasets of this size before and know how to deliver clean, structured outputs that are ready to use from day one.