DataHawk provides four keyword datasets to help you optimise your product visibility, improve your SEO strategy, and discover new opportunities.

What's available

Keyword Suggestions

AI-generated keyword ideas for your tracked products, refreshed daily. DataHawk analyses your competitors, extracts the keywords they rank for, filters out irrelevant terms (brand names, sizes, colours), and scores what remains by relevance and opportunity.

Each suggestion includes:

• Competitivity Score (–100 to 100) — how your product compares to the top 3 ranked products for that keyword, based on reviews, ratings, and price. A positive score means you are well-positioned to compete.
• Monthly Reach Potential — combines search volume with the competitivity score to indicate how much traffic you could realistically capture.

Keyword Lookup

A weekly view of every keyword where your products ranked organically in the past 7 days, as detected by DataHawk's tracking system. Useful for understanding your current organic footprint.

Keyword Placement (data paused as of August 2023)

Previously showed where specific keywords appeared within your listings — title, description, bullet points, backend keywords. Amazon stopped sharing this data in August 2023. Historical data remains available.

Keyword-Seeded Suggestions (available on request)

If you don't have a product to start from, you can enter a seed keyword and DataHawk will surface related and adjacent keywords from its database. It works by cross-matching DataHawk's keyword library against the title of your seed keyword to find terms with meaningful overlap. This replaces the need for external tools like SEMRush for keyword discovery. Reach out to your DataHawk contact to enable this.

Coverage and availability

• Works for approximately 90% of tracked products
• Currently available for English-speaking marketplaces only: US, GB, CA, AU, SG, IN, AE
• Track products before noon UTC to see updated results the following day (6am UTC)

What to do if keyword suggestions are missing

DataHawk needs two types of context about your product to generate suggestions: its browse node category (so it knows which market to look in) and keyword ranking data (so it knows which search terms your product already appears for). If either is thin, suggestions will be sparse or absent.