Introducing Product Scan: Product-Level Buyer Intelligence for E-Commerce

The Gap Product Scan Fills

A Category Scan tells you what your market cares about. It reads conversations across a whole product category and ranks the concerns buyers raise before they buy. That is the right starting point. It is not the whole picture.

Category intelligence stops at the category line. It cannot tell you what buyers say about your product. It does not know your earbuds have sensitive touch controls. It does not know a reviewer ran them through a washing machine.

To learn that, sellers used to mine reviews by hand. Read a hundred Amazon reviews, sort the complaints, cross-check Reddit, watch a few YouTube teardowns. The work took hours and the results were hard to trust. One faked review could tilt the read.

Product Scan automates that work. It reads buyer conversations about one specific product across networks and returns a structured Voice Profile. Product-level buyer intelligence becomes a scan, not a weekend.

How Product Scan Works

You enter a product name and a brand. That is the whole input. DecodeIQ discovers the ASIN from those two fields, then begins the scan.

The scan reads Amazon reviews segmented by star rating, so a one-star complaint and a five-star endorsement carry different weight. It reads Reddit threads where buyers compare options in the open. It reads YouTube comment sections under review videos. It reads forum posts where owners talk after the purchase.

From those sources it extracts five signal types. Product weaknesses are the complaints buyers repeat. Competitive advantages are the strengths buyers validate against rivals. Unmet needs are the things buyers wish the product did. Sentiment drivers are what moves a buyer toward love or regret. Reviewer consensus is where many voices agree on one point.

Each signal carries its own source citation. You can see the review, thread, or comment behind every claim. That matters when you write copy. A claim you can trace is a claim you can defend.

The output is a Voice Profile. It is product-specific truth, not category generalization. It knows which objections to answer first and which strengths buyers back up. It surfaces the features buyers ask for, which become selling points once the product delivers them.

A Product Scan costs 8 credits. It runs across the same networks as a Category Scan, but it points all of that discovery at one product instead of a market.

Voice Profile vs Voice Map

These two outputs answer different questions. Mixing them up leads to flat copy.

A Voice Map is category-level. It comes from a Category Scan and uses nine entity types, including buying criteria, objections, comparison anchors, and use cases. It describes how the whole category thinks. It is the map of the territory.

A Voice Profile is product-level. It comes from a Product Scan and uses five signal types. It describes what buyers say about one product. It is the ground truth for a single listing.

The Voice Map sets the frame. It tells you what buyers in your category weigh and what language they use. The Voice Profile fills the frame with specifics. It tells you whether your product wins or loses on each of those concerns.

Use them together. The Voice Map tells you what to talk about. The Voice Profile tells you what to say. One without the other leaves a gap.

The Listing Attack Plan

The Listing Attack Plan is the sixth generation type in DecodeIQ. The first five generate copy from category intelligence. This one goes further.

It takes three inputs: a Voice Map, a Voice Profile, and a Product Profile. The Voice Map brings category concerns. The Voice Profile brings product truth. The Product Profile brings your own specs and positioning. The plan combines all three into one competitive brief.

The output is annotated listing copy. Every line traces back to a buyer signal. The annotations show competitive callouts, where your product beats a named rival on a concern buyers raised. They show objection handling, where the copy answers a complaint before the buyer reaches it.

This is the layer that lets a listing read like it was written by someone who studied the reviews. It leads with the concern buyers raise first. It answers the objection that loses the most sales. It claims the advantage buyers already confirm in public.

A standard listing tells buyers what the product is. A Listing Attack Plan tells buyers why their specific worry is handled. The first is a spec sheet. The second is a sale.

A Listing Attack Plan costs 2 credits to generate, once you have the two scans behind it.

A Real Example: TOZO T6

We ran the full stack on the TOZO T6 wireless earbuds. The case study is live at the TOZO T6 three-layer listing comparison.

The Product Scan built a Voice Profile of 129 buyer signals from 32 sources across 6 networks, including 90 Amazon reviews. Those 129 signals broke into five types: product weaknesses, sentiment drivers, reviewer consensus, unmet needs, and competitive advantages. Each one carried its own source citation.

We then generated three listings for the same product, each with one more layer of intelligence. The first layer used the Voice Map and the Product Profile. It produced clean copy aligned to category concerns, but it spoke in general terms.

The second layer added the Voice Profile. The copy sharpened. It started answering the objections buyers raise about the T6 itself, not the earbud category in the abstract. It named strengths reviewers had already confirmed.

The third layer was the Listing Attack Plan. It combined all three data layers into a competitive brief. The copy gained sourced competitive positioning. It called out where the T6 wins against named rivals and handled the top objection up front. It even turned an unmet need buyers voiced into a forward-looking selling point.

The lesson is plain. The copy sharpened at every layer. Category intelligence gives you a good listing. Product intelligence gives you a true one. The full case study walks through each line, so read the TOZO T6 teardown to see the copy change layer by layer.

Get Started

The path is three steps. Run a Category Scan to build your Voice Map. Run a Product Scan to build your Voice Profile. Generate a Listing Attack Plan from both.

The credit costs are clear. A Category Scan is 5 credits. A Product Scan is 8 credits. A Listing Attack Plan is 2 credits. That gives you a listing where every line traces to a real buyer signal.

FAQ

Q: What is a Product Scan?

A Product Scan reads buyer conversations about one specific product. You enter a product name and brand, and DecodeIQ finds the ASIN, then scans Amazon reviews, Reddit threads, YouTube comments, and forums. It extracts five signal types and returns a Voice Profile with a source citation behind every claim.

Q: How is a Voice Profile different from a Voice Map?

A Voice Map covers a whole category and uses nine entity types. A Voice Profile covers one product and uses five signal types. The Voice Map tells you what the market cares about. The Voice Profile tells you what buyers say about your product. You use them together.

Q: What is a Listing Attack Plan?

A Listing Attack Plan is the sixth generation type in DecodeIQ. It needs a Voice Map, a Voice Profile, and a Product Profile as inputs. It produces annotated listing copy with competitive callouts and objection handling, so every line traces back to a real buyer signal.