Buyer Intelligence for E-Commerce

Being found got you clicks. Now AI does the choosing.

DecodeIQ mines Reddit, YouTube, Amazon reviews, and buyer forums to uncover the questions, objections, and comparisons shaping purchase decisions. It writes those insights into your content, then measures AI recommendation trends across ChatGPT, Gemini, and Perplexity.

See if AI recommends your product

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Live extract“Does it stay on during a run?”Reddit
app.decodeiq.ai/voice-maps/vm_8241
‹ Back to Voice Maps
best wireless earbuds for running
Voice Map
Scanned 1 day ago  ·  1,499 entities  ·  73 sources
Signal strength
Buyer concerns
90/100
Cross-network
33%
Objection density
92/100
Use case diversity
91/100
Language strength
68/100
Source diversity
5/6
Generate contentCopy text
Top buyer concerns
Buying Criteria0.94

“Does it stay on during a run, or am I pushing it back in every mile?”

214 mentionsRedditAmazon
Objection0.89

“Battery died after 3 hours. Half the advertised life.”

167 mentionsYouTubeReddit
Use Case0.92

“For marathon training, sweat resistance matters more than sound.”

198 mentionsQuoraForums
Live buyer conversations. Reddit, YouTube, reviews, and forums.
RedditRedditYouTubeYouTubeAmazonAmazonWalmartWalmartBest BuyBest BuyQuoraQuoraForums
The loop

One loop. Four steps. Dated results.

01Map and freeze

Run a Category Scan or Product Scan to map buyer language and freeze the questions.

02Baseline

Run the frozen questions before publication and record the recommendation evidence.

03Publish and record

Publish buyer-matched content to an accessible surface and record the change.

04Re-measure

Run the exact same questions again and compare.

Each step feeds the next. The questions never change between checks, so the comparison means something.

The mechanism

Same product. Two languages.

Seller languagesrc: catalog

“Premium noise-canceling headphones with 40mm drivers, 30-hour battery life, and Active Noise Cancellation technology.”

0 buyer signals detected
Buyer languagesrc: 1,847 conversations

“My last pair died after 3 hours.”

Objection
8 sources · 3 networks · confidence 0.91

“Comfort matters more than sound. I wear them 9 hours a day.”

Buying Criteria
11 sources · 4 networks · confidence 0.94

“I need something that blocks gym noise but I can still hear traffic outside.”

Use Case
6 sources · 2 networks · confidence 0.88
3 entities extracted

The gap between these two is what a Voice Map measures.

DecodeIQ measures recommendation evidence. Your store analytics measure conversion.

The AI shopping window

Shoppers now ask an assistant before they ask a search box.

Third parties report the scale of that shift. ChatGPT handles 50 million shopping queries daily, and one study measured its traffic converting at 15.9 percent, near 9x higher than Google Search. These are market observations about a channel, not DecodeIQ results.

Source: Seer Interactive conversion study, 2025 · OpenAI disclosed prompt volume

Alexa for Shopping
250Mshoppers

Alexa for Shopping, formerly Rufus, has reached 250 million shoppers.

Retrieval
Meaning, not keywords.

AI shopping assistants parse meaning. Buyer language is one of the main inputs they synthesize from.

The loop: Intervene

One query in. Buyer language out.

01Scan
query: "noise canceling headphones"

One category query starts a multi-stage pipeline. It reads live buyer threads on Reddit, YouTube, Amazon reviews, and buyer forums.

02Voice Map
buying_criteriaobjectionscomparison_anchorsuse_casesoutcomeslanguage_patternsproductscompaniesfeatures

Extracted language clusters into 9 entity types. Cross-network correlation validates every one.

03Generate
product_listing.mddone
faq_section.mddone
buying_guide.mdwriting…

Generate six content types from one Voice Map. Each output speaks in your buyers' own words.

Intervene: the evidence

Nine entity types. One map of how buyers decide.

Every entity is a validated pattern from real conversations. Each carries its evidence, sources, and confidence score.

Objections125 extracted

Concerns, fears, or barriers preventing purchase.

“Battery died after 3 hours.”

Found in 37 sourcesStrong signal
What your content must address

Anchor battery claims to specific run durations. “Covers a full marathon with time to spare.” Not the spec sheet number.

Buying Criteria199 extracted

The factors buyers evaluate in purchase decisions.

“Does it stay on during a run?”

What your content must answer
Use Cases85

“For marathon training,”

Which context to speak to
Comparison Anchors43

“Compared to AirPods Pro…”

How your content should position
Outcomes
113extracted

Results buyers describe experiencing.

“never slipped off”
Language Patterns
66extracted

Distinctive phrases buyers consistently use.

“stay put / don’t budge”
Products
54extracted

Specific products referenced in discussions.

AirPods Pro 2 · Shokz OpenRun
Companies
29extracted

Companies mentioned in buyer conversations.

Apple · Shokz · Bose · Sony
Features
114extracted

Raw product specifications discussed.

bone conduction · ear hooks · IP68
All types
9 entity types.
One Voice Map.
The loop: Apply

One Voice Map. Six ways to publish it.

Product Listing1 credit
product_listing.md
Running Earbuds with Ear Hooks, IPX7 Sweat Resistant, 12-Hour Battery,
STAYS PUT AT MILE SIX: Ear hooks hold through sprints, sweat, and head turns.
HEAR THE ROAD: Open-ear design keeps traffic audible on every city run.

Marketplace-ready copy for Amazon, Shopify, Etsy.

All 9 entity types
Blog Post2 credits
blog_post.md
Bone Conduction vs In-Ear: Which Is Safer for Road Running?
Runners near traffic treat hearing cars as a safety requirement, not a preference.
The design you pick decides what you hear at mile six.

Topics drawn from the questions buyers already ask.

Buying CriteriaObjectionsUse CasesOutcomesLanguage Patterns
FAQ Section1 credit
faq_section.md
Q: Will these stay in during a run?
A: The ear hooks hold through sprints and head turns. Runners report they
stay put through mile six, even once sweat builds up.

Built from real buyer questions and objections.

ObjectionsBuying CriteriaFeatures
Buying Guide2 credits
buying_guide.md
1. Fit security. Hooks, wings, or clips that hold at mile six.
2. Sweat rating. IPX5 minimum. IPX7 for rain and heavy sweat.

Structured from actual buying criteria and comparisons.

Buying CriteriaComparison AnchorsObjectionsProducts
Social Proof1 credit
social_proof.md
“Never fell out. Survived the most brutal rain.”
validated outcome · found in 37 sources

Curated highlights from validated buyer outcomes.

OutcomesCompaniesLanguage Patterns
Listing Attack Plan2 credits

Combines category intelligence, competitor intelligence, and your product specs. It is the only DecodeIQ generation built from all three.

Voice MapVoice ProfileProduct Specs
attack_plan.md
“Ear hooks hold through a full marathon, sweat and all.”vs Beats Fit Pro
rewrite_priority: 01 · counters objection: “battery died after 3 hours”
competitor gap: no wet-condition fit claim across top 5 listings
The loop: Re-measure

The measurement step, run twice.

First as a baseline before you change anything. Then as a re-check after you publish buyer-matched content and the engines have had time to read it. The re-check runs the exact same frozen questions. Same questions, same engines, dated results. That is the difference between a measurement and a screenshot.

AI Visibility

Freeze buyer questions, see which products ChatGPT, Gemini, and Perplexity recommend, publish buyer-matched content, then run the same questions again.

See how AI Visibility works
Evidence and limits

What we will not tell you.

AI answers vary between runs, so single screenshots prove nothing.

We run every question three times per engine and require repeated appearances before calling a change real.

Re-checks wait out a cooldown because engines index slowly. Your dashboard shows the date it unlocks.

When a check comes back incomplete, you get no score instead of a flattering one.

Tools that promise instant AI rankings are selling you the variance.

Free tool

Run a free Buyer Voice Snapshot.

Enter a product category. The snapshot returns the top buying criteria, objections, and buyer phrases from live conversations. No account required.

Run a Free Snapshot
Explore all free tools →
Snapshot · Espresso Machinessample output
Top buying criterion
“Heats up fast enough for a morning routine. Nobody waits 20 minutes.”
Top objection
“Plastic parts near the boiler scare me at this price.”
Buyer phrase
“café-quality shots without the café line”

Every AI copywriter writes from your catalog. DecodeIQ writes from your buyers' conversations.

AI copywritersKeyword toolsDigital shelf suites
Who it's for

The loop runs where you sell.

Shopify stores

You control the pages engines can reach. The loop runs end to end on your own domain.

Amazon sellers

Your listing speaks specs. Buyers ask in their own words. Map that language, then measure.

Etsy sellers

Buyer language in a marketplace where nobody else maps it.

From a seller

“We used DecodeIQ to rewrite our product pages, and the messaging just clicked better with shoppers.”

Sarah Chen · Early Access Customer
Common questions

Answers before you ask.

They generate content from your keywords and product specs. DecodeIQ generates content from your buyers' actual conversations across Reddit, YouTube, and review sites, combined with your product specs. The input is different. The output reflects it.

See your category's buyer language.

One scan produces the Voice Map everything else uses.

Start with a Category Scan

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