ad-angle-miner

To extract ad angles from reviews and Reddit, you ingest qualitative data sources to identify pain points, outcomes, and competitive weaknesses. The system then captures 2-5 verbatim quotes per angle and scores them based on evidence, emotion, and differentiation to build a ranked angle bank.

The best way to find high-converting ad angles from qualitative data is to aggregate reviews, support tickets, and competitor ads. This process surfaces actual buyer pain language and outcome phrases, assigning scores based on evidence and emotion to output ready-to-test ad variants.

Yes, you can use NPS tickets and competitor ads to build an angle bank. Applying the extraction process across these sources surfaces competitive weaknesses and buyer identity angles, producing a ranked bank complete with proof quotes and recommended ad formats.

You generate ad copy variants from pain points by ranking the extracted angles using evidence, emotion, and differentiation scores. The output provides suggested ad formats per angle, creating ready-to-test variants directly from the verbatim buyer language captured.

Yes, the angle extraction process explicitly assigns a score to each extracted ad angle based on three criteria: available evidence, emotional resonance, and competitive differentiation. This scoring mechanism ensures the final ranked angle bank prioritizes the most credible angles.

To surface competitive displacement ad angles, you need to aggregate customer reviews, Reddit complaints, NPS support tickets, and competitor ads. Fusing these qualitative sources allows the extraction process to identify competitor weaknesses and capture relevant verbatim quotes.