This episode explores Ngram optimization within Amazon advertising, addressing the challenge of managing numerous low-click search terms. Against the backdrop of the common problem of high non-converting spend in Amazon PPC campaigns, the hosts discuss Ngram analysis as a solution to aggregate data from low-click keywords. More significantly, the conversation details four practical optimization strategies: a visual scan for irrelevant terms, identifying zero-order keywords sorted by spend, analyzing high-ACoS keywords, and employing an "Ngram graduation" technique to discover high-performing keywords. For instance, the hosts illustrate how analyzing the frequency of the word "lid" across various search terms reveals its poor conversion rate, prompting the addition of negative keywords. In contrast, the "Ngram graduation" method, starting with a high-performing one-gram like "forks," progressively adds more specific terms (e.g., "forks bulk," "plastic forks bulk") to identify profitable long-tail keywords. What this means for Amazon sellers is a more efficient way to manage search term data, reduce wasted ad spend, and uncover hidden opportunities for improved campaign performance.
