AI customer journey audit

ExampleReal report generated on October 1, 2026 for Nike, with no human editing.

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Where Nike's buyers ask AI

Watch now: ChatGPT, Google AI Overviews, Google AI Mode, and Gemini. Biggest opportunity: Alexa for Shopping.

Market: United States18 AI engines and model families evaluatedGenerated on October 1, 2026

The buyer's question

“What are the best running shoes for marathon training and everyday runs?”

4/8

Nike is cited by 4 of 8 engines on a buyer's question

  • ChatGPT: Cites Nike
  • Google AI Overviews: No AI answer shown for this question
  • Google AI Mode: No Nike
  • Gemini: Cites Nike
  • Alexa for Shopping: No Nike
  • Microsoft Copilot: No answer in time
  • Perplexity: Cites Nike
  • Claude: Cites Nike
  • Grok: No answer in time
  • Naver: No Nike
  • Wenxin: No Nike

Watch now

  • ChatGPT

    Most of your buyers

  • Google AI Overviews

    Most of your buyers

  • Google AI Mode

    Most of your buyers

  • Gemini

    A significant share of your buyers

Opportunities

  • Alexa for Shopping

    A significant share of your buyers

  • Meta AI

    A significant share of your buyers

What a single engine does not show you

6 competitors appear on one engine only:

  • Google AI Mode
    REI
    JD Sports
    Fleet Feet
    Backcountry.com
  • NaverOn
  • Wenxin
    Xtep

Engine priorities

The AI engines to watch for your buyers

The estimated share of your buyers who use each AI engine while choosing what you sell, from 0 to 3.

Watch now

A large share of your buyers use it, with a strong signal.

ChatGPT

OpenAI

Widely used for product discovery, advice, and comparisons.

Tracked by Qwairy in this market

Most of your buyers3.0/3
Strong signal

Reaches mainstream Google searchers during high-intent research.

Tracked by Qwairy in this market

Most of your buyers3.0/3
Strong signal

Direct U.S. shopping integration for product discovery and checkout.

Tracked by Qwairy in this market

Most of your buyers2.5/3
Strong signal

Gemini

Google

Broad Google ecosystem reach and direct commerce integration.

Tracked by Qwairy in this market

A significant share of your buyers2.3/3
Close to the threshold

Opportunities

A significant share of your buyers, at some moments or in some markets.

Major Amazon shopping audience with dedicated product research and comparison.

Tracked by Qwairy in this market

A significant share of your buyers1.8/3
Mixed signal

Social discovery audiences can seek outfit and product advice.

Tracked by Qwairy in this market

A significant share of your buyers1.8/3
Strong signal

Significant U.S. reach through Microsoft products and Bing.

Tracked by Qwairy in this market

A significant share of your buyers1.8/3
Strong signal

What the engines answer

Same question, different answers

We asked one of your buyers' questions to 11 AI engines, as buyers use them in this market. Each one recommends its own set of brands.

The buyer's question

“What are the best running shoes for marathon training and everyday runs?”

Nike is cited by 4 of 8 engines. Together they named 13 different brands. 6 brands appear on one engine only: buyers on the other engines never see them.

The brands each engine names firstThe number is the brand's rank in the answer.
BrandChatGPTGoogle AI ModeGeminiAlexa for ShoppingPerplexityClaudeNaverWenxinNamed by
Nike
Cites NikeNo NikeCites NikeNo NikeCites NikeCites NikeNo NikeNo Nike4/8
ASICS
11314127/8
Brooks
42123217/8
Saucony
32413337/8
Hoka
43544/8
New Balance
25454/8
Adidas
2623/8
On1Only here1/8
REI
3Only here1/8
Altra
41/8
JD Sports
4Only here1/8
  • Google AI OverviewsNo AI answer shown for this question
  • Microsoft CopilotNo answer in time
  • GrokNo answer in time
See each engine's answer
  • ChatGPTWatch nowCites Nike

    First alternatives named

    1. 1.
      ASICS
    2. 2.
      New Balance
    3. 3.
      Saucony
    4. 4.
      Brooks

    What the buyer saw

    • 5 product cards
    • 1 web search

    Searched first: “best marathon training daily running shoes 2026 Novablast 5 Ride 18 Ghost 17 Pegasus 42 1080 v15”

    Most cited sources: rtings.com, prodirectsport.com, nextgait.com

  • Google AI ModeWatch nowNo Nike

    First alternatives named

    1. 1.
      ASICS
    2. 2.
      Brooks
    3. 3.
      REIOnly here
    4. 4.
      JD SportsOnly here
    5. 5.
      Fleet FeetOnly here

    What the buyer saw

    • 4 product cards
  • GeminiWatch nowCites Nike

    First alternatives named

    1. 1.
      Brooks
    2. 2.
      Saucony
    3. 3.
      Asics
    4. 4.
      Hoka
  • Alexa for ShoppingOpportunityNo Nike

    First alternatives named

    1. 1.
      ASICS
    2. 2.
      Brooks
    3. 3.
      Hoka
    4. 4.
      Saucony
    5. 5.
      New Balance

    What the buyer saw

    • 7 product cards
    • 1 community source
    • 4 suggested follow-ups

    Most cited sources: runnersworld.com, marathonhandbook.com, outdoorgearlab.com

  • PerplexityLow priorityCites Nike

    First alternatives named

    1. 1.
      Saucony
    2. 2.
      Adidas
    3. 3.
      Brooks
    4. 4.
      Asics

    What the buyer saw

    • 1 community source
    • 2 suggested follow-ups

    Most cited sources: runnersworld.com, nike.com, irunfar.com

  • ClaudeLow priorityCites Nike

    First alternatives named

    1. 1.
      ASICS
    2. 2.
      Brooks
    3. 3.
      Saucony
    4. 4.
      New Balance
    5. 5.
      HOKA

    What the buyer saw

    • 1 web search

    Searched first: “best marathon training shoes 2026”

    Most cited sources: csr.hdsupply.com, esquireindia.co.in, trainingplan.dev

  • NaverLow priorityNo Nike

    First alternatives named

    1. 1.OnOnly here
    2. 2.
      ASICS
    3. 3.
      Saucony
    4. 4.
      Altra

    What the buyer saw

    • 1 web search

    Searched first: “What are the best running shoes for marathon training and everyday runs?”

    Most cited sources: blog.naver.com, on.com, weartesters.com

  • WenxinLow priorityNo Nike

    First alternatives named

    1. 1.
      Brooks
    2. 2.
      Adidas
    3. 3.
      Saucony
    4. 4.
      HOKA
    5. 5.
      New Balance

    What the buyer saw

    • 2 web searches

    Searched first: “适合马拉松训练和日常跑步的最佳跑鞋”

    Most cited sources: baijiahao.baidu.com, zhuanlan.zhihu.com, rtings.com

Blind spots

What you miss by watching a single engine

The buyers, markets and moments other AI engines cover.

Google AI OverviewsGoogle AI Mode

Watching only ChatGPT misses Google-native discovery through AI Overviews and AI Mode.

Alexa for Shopping

Watching only Google misses Amazon-intent shoppers using Alexa for Shopping.

Meta AI

Watching only general-purpose assistants misses social-led discovery through Meta AI.

WenxinQwenKimiGLMNaver

Watching a U.S.-focused engine misses China and Korea discovery moments.

Your buyers

Who your buyers are

Your buyers' profiles and markets, as the analysis sees them.

B2C

U.S. B2C sneaker, sportswear and lifestyle shoppers

  • United States
  • Canada
  • United Kingdom
  • France
B2C

U.S. B2C runners, gym-goers, and team-sport participants

  • United States
  • Canada
  • Mexico
B2C

U.S. B2C style-led sneaker buyers and collectors

  • United States
  • Japan
  • South Korea

Features that matter

The engine features that matter for your activity

Beyond which engine, what shows up in the answer counts: products, local results, ads, sources.

  • Shopping results

    High

    Buyers need products, prices, availability and retailers during shortlist and comparison.

    Matters most on
    ChatGPT, Gemini, Google AI Mode, Alexa for Shopping, Perplexity, Microsoft Copilot
    Seen on the test question
    • ChatGPT5
    • Google AI Mode4
    • Alexa for Shopping7
    Qwairy tracks it on
    ChatGPT, Google AI Mode, Alexa for Shopping, Microsoft Copilot
  • Ads in answers

    High

    Paid visibility can influence discovery, but organic product relevance remains important.

    Matters most on
    Google AI Overviews, Google AI Mode, Microsoft Copilot, ChatGPT, Alexa for Shopping
    Seen on the test question
    -
    Qwairy tracks it on
    ChatGPT, Google AI Mode
  • Social and community sources

    High

    Fit, comfort, styling and durability depend heavily on peer experiences and reviews.

    Matters most on
    ChatGPT, Gemini, Perplexity, Meta AI, Claude, Grok
    Seen on the test question
    • Perplexity1
    • Alexa for Shopping1
    Qwairy tracks it on
    ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Microsoft Copilot, Perplexity, Claude, Grok, Naver, Wenxin
  • Web searches before answering

    High

    Current prices, reviews, availability and sizing require broad, fresh research.

    Matters most on
    ChatGPT, Perplexity, Google AI Mode, Gemini, Google AI Overviews, Grok
    Seen on the test question
    • ChatGPT1
    • Claude1
    • Naver1
    • Wenxin2
    Qwairy tracks it on
    ChatGPT, Perplexity, Claude, Grok, Naver, Wenxin
  • Local results

    Medium

    Store discovery matters, but most apparel research and purchasing happens online.

    Matters most on
    Google AI Mode, Google AI Overviews, Meta AI, Gemini, Microsoft Copilot
    Seen on the test question
    -
    Qwairy tracks it on
    ChatGPT
  • Follow-up questions

    Medium

    Iterative questions help narrow activity, fit, style, budget and preferences.

    Matters most on
    ChatGPT, Gemini, Google AI Mode, Perplexity, Claude
    Seen on the test question
    • Perplexity2
    • Alexa for Shopping4
    Qwairy tracks it on
    Alexa for Shopping, Perplexity, Grok, Naver

Buyer questions

What your buyers ask AI

One question per moment of the journey, in the language of your market.

  1. 01

    Discover

    “What are good athletic shoes for running, training, walking, or everyday wear?”

  2. 02

    Shortlist

    “Which athletic shoes fit my activity, foot shape, budget, and style preferences?”

  3. 03

    Compare

    “How do these athletic shoes differ in comfort, durability, fit, performance, and price?”

  4. 04

    Validate

    “Are these athletic shoes worth buying based on reviews, sizing, return policy, and current price?”

Method

How to read this report

  1. 1Qwairy reads your website to understand your offer, your buyers and your market.
  2. 2Several AI models answer the same questionnaire separately. Each one estimates, from 0 to 3, the share of your buyers who use each of the 18 engines, and sees them in its own order so that list position does not sway the ratings.
  3. 3An engine's rating of itself never counts. An engine reaches “Watch now” only when its average is high and at least two thirds of the ratings agree; when they diverge, its confidence level says so.
  4. 4Figures, market shares and rankings that a model states without a source are removed. Audience figures come only from cited public sources.
  5. 5Finally, one of your buyers' questions is asked live to every engine Qwairy tracks in your market. The brands named are recorded as they appear: this part is observed, not estimated.

This is an estimate, not a measure of actual usage: web analytics only count the visits AI answers send, not the questions buyers ask. Use it to choose the engines to watch; Qwairy's monitoring then measures your visibility on them, prompt by prompt.

Usage scale

  1. 3/3Most of your buyers
  2. 2/3A significant share of your buyers
  3. 1/3A niche group of your buyers
  4. 0/3Almost none of your buyers

Confidence level

  • Strong signalThe ratings converge on this level.
  • Close to the thresholdThe engine sits between two levels and can change from one report to the next.
  • Mixed signalThe ratings clearly diverge: read this level with care.

Watch the engines that matter for your buyers

Qwairy tracks your visibility on the AI engines of this report, prompt after prompt, week after week.

The free audit measures if ChatGPT, Gemini and Perplexity cite your brand.