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Market/Categories/General Assistant/Wardrobe

Independent product intelligence · Worldwide · 2026-05-01 → 2026-07-31

Wardrobewardrobe-ai.com

No product description has been published for this domain yet. Everything below is measured directly.

General Assistantwardrobe-ai.comTracked since 2026-08-193 discovery sources
1.5KBacklinks
417Referring domains
21Domain authority
+15.5%Referring domains · 90 days

Authority & distribution

How strong is Wardrobe’s web footprint?

Backlinks measure accumulated distribution; referring domains show how broadly that authority is spread. Both are observable on the open web, so both are published for every product here.

Backlinks

1.5KCurrent snapshot

Referring domains

417Current snapshot

Authority

21Domain authority · category median 22

90-day move

+15.5%Referring domains, last 90 days
At 21, Wardrobe sits below the 22 median for its category.

Trajectory · Pro

The counts above are the latest of 370 daily observations. The curve through them is on the full profile.

See the trajectoryOpen the full profile

AI referral visibility

Which AI assistants are already sending Wardrobe traffic?

Measured · Pro

Measured for this product: AI referral traffic.

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Product profile

What Wardrobe is selling.

Traffic makes more sense when you can connect it to the actual product promise.

“Wardrobe”

No usable description reached this profile from any discovery source, so none is shown. The measured signals below are unaffected.

General AssistantSeen 2026-08-19 → 2026-08-21Coverage tier C

What we have measured

4 of 8 signal groups are available for this product: identity, authority and backlinks, AI referrals, search demand.

Not measured for this domain: traffic and engagement, audience demographics, country distribution, acquisition mix. Those sections are left out of the page rather than filled with estimates.

Canonical website: https://wardrobe-ai.com/

Observed across 3 discovery sources.

Research questions

What the evidence answers about Wardrobe.

Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.

What problem does Wardrobe AI solve?

Wardrobe AI solves the problem of selecting the right AI tools for fashion needs by providing personalized wardrobe advice. It uses AI to generate personalized clothing recommendations based on user photos and preferences, acting as a direct-use AI fashion advisor tool.

Who is the target audience for Wardrobe AI?

The product is designed for individuals seeking personalized fashion guidance and wardrobe planning. It is categorized as a general assistant tool, positioning it for a broad audience rather than a specialist workflow.

What features does Wardrobe AI include?

Wardrobe AI includes features for photo upload (advising variety for best results), preference configuration for color palette and style, and weekly delivery of AI-generated fashion styles to the user's inbox. It also allows users to delete generated images and attempts to find similar clothes for purchase.

What is Wardrobe AI used for and in what situations?

Wardrobe AI is used for receiving personalized fashion and wardrobe recommendations. A user uploads photos of themselves, configures their style preferences like color palette, and then receives new AI-generated fashion styles on a weekly basis via email.

What is Wardrobe AI?

Wardrobe AI is a general assistant tool that uses artificial intelligence to provide personalized wardrobe advice and fashion recommendations. Users upload their photos and preferences to receive weekly style suggestions.

5 of 6 research questions are answered for this product. The rest need source evidence we have not collected yet, so they are left unanswered rather than guessed.

Behind the lock

Unlock full Wardrobe intelligence.

  • Backlink trajectoryThe figures above are the latest observation. The daily curve behind them holds 370.
  • AI referral detailHow much traffic assistants send.
  • Search structure and ranking depthOrganic against paid, brand against non-brand, and how many keywords rank in the top three against the long tail — which is what decides whether the demand is portable or tied to the name.
  • The rest of the marketPage through every leaderboard 100 rows at a time, put any five products side by side, and query the whole dataset over API / MCP.

Worldwide estimates · Data period 2026-05-01 → 2026-07-31. Figures are measured estimates intended for market research. Signals we have not measured for this domain are omitted, never estimated; a measured zero is still reported as zero. How this was measured