N-Gram Analysis: How Supplement Brands Find Profitable Keywords Hidden in Plain Sight

The search term report is the most valuable asset in an Amazon PPC account — and the most underused. Most advertisers glance at it, sort by spend, and negative out a few obvious losers. N-gram analysis goes deeper: it systematically breaks every search term into individual word combinations and aggregates performance at the pattern level. For supplement brands, where shoppers search in highly specific long-tail phrases, this reveals profitable keyword patterns that standard keyword reviews completely miss.

What N-Grams Are

An N-gram is simply a contiguous sequence of N words from a search term. Breaking down the search term 'magnesium glycinate sleep support 400mg' produces:

• Unigrams (1 word): magnesium, glycinate, sleep, support, 400mg
• Bigrams (2 words): magnesium glycinate, glycinate sleep, sleep support, support 400mg
• Trigrams (3 words): magnesium glycinate sleep, glycinate sleep support, sleep support 400mg

When you do this across thousands of search terms in your report, patterns emerge. A bigram like 'magnesium glycinate' might appear in 200 different search terms, generating 45 orders at a 31% conversion rate. That's a clear signal to add it as an exact match keyword in a dedicated campaign — if it isn't already.

Why This Matters More for Supplements Than Almost Any Other Category

Supplement shoppers are research-driven and specific. They search for exact ingredient forms ('ashwagandha KSM-66 vs root extract'), dosage specifics ('vitamin D3 5000 IU with K2'), certifications ('organic ashwagandha USDA certified'), and combination stacks ('magnesium zinc vitamin B6'). These long-tail terms have high purchase intent and lower competition than generic category terms — but they're invisible unless you analyze them at the pattern level.

Additionally, the mid-2025 Amazon algorithm shift made this more urgent: auto campaign impression share jumped to 40%+ of total impressions as Amazon expanded semantic matching. Your ads are being served to more search terms than before, which means your search term report is generating more data — and more noise — than ever.

The Two-Sided Value: What to Add and What to Block

Side 1: Finding Keywords to Add

Sort your n-gram frequency table by orders or revenue. Any bigram or trigram that appears across multiple search terms and generates consistent conversions but isn't targeted as a keyword is a gap. These are terms Amazon is already routing impressions to — but you have no control over them because they live inside auto or broad match campaigns. Adding them as exact match targets gives you bid control and dedicated budget.

Side 2: Building Systematic Negatives

This is where the biggest efficiency gains come from. When you see a unigram or bigram that appears across hundreds of search terms with near-zero conversion rate, negating that phrase blocks an entire class of irrelevant traffic with one negative keyword entry. For supplement brands, common high-volume, low-conversion patterns include:

• Generic food terms bleeding into supplement searches (e.g., 'protein bar recipe', 'powder for smoothie')
• Pet supplement searches matching human supplement products
• Competitor brand names where you're unlikely to convert their loyal customers
• Condition-adjacent terms that drive clicks but not purchases due to search-listing mismatch
• Free-sample seekers and review hunters ('free sample', 'trial pack')

One documented case study reported a 35% reduction in PPC ad waste after systematic n-gram analysis led to a comprehensive negative keyword implementation. At supplement CPCs of $2.50–$7.00, eliminating 35% of wasted spend is material.

The Step-by-Step Process

1. 1Pull your Search Term Report from Amazon Ads Console. Use at least 30–60 days of data; 90 days is better for statistical significance.
2. 2Export to Excel or Google Sheets. Each row is a search term that triggered an impression.
3. 3For each search term, split the string by spaces to get individual words (unigrams). Use Excel's TEXTSPLIT or a simple script.
4. 4Create a second column combining adjacent word pairs (bigrams) and a third for trigrams.
5. 5Use SUMIF or a pivot table to aggregate clicks, spend, orders, and ACoS by each unique n-gram.
6. 6Sort by spend descending. High-spend n-grams with zero orders are your first negative keyword targets.
7. 7Sort by orders descending. High-order n-grams not yet in your keyword list are your harvest targets.
8. 8Repeat monthly. Run extra cycles during high-spend periods: product launches, Q4, Prime Day.

The Compliance Overlay for Supplements

There's an additional n-gram filter supplement brands must apply: compliance screening. Some of your highest-converting n-grams may contain disease names or treatment language that violates Amazon's ad policy. A term like 'anxiety relief supplement' may convert extremely well, but bidding on it exposes you to enforcement risk.

After running your n-gram analysis for performance, run a second pass specifically looking for flagged language in your highest-performing patterns. High-converting terms with prohibited language need to be evaluated — and in some cases, the right decision is to stop bidding on them proactively rather than wait for Amazon's enforcement team.