New Energy Vehicle Brand Perception Structure Audit: AI Perception Analysis of Tesla, BYD, NIO, Li Auto, and XPeng via ChatGPT

Report Number: AAU-Nh4kRp82

Audit Subject: Brand Perception Structure of New Energy Vehicles

Audit Model: ChatGPT

Auditor: Striver S.

Network Environment Type: Static Residential IP

Audit Node: United States

Data Source: Structured dialogue, comprising 8 sets of Q&A, covering eight dimensions: hierarchical structure, horizontal clustering, perception mapping, value proposition positioning, narrative labeling, usage scenario association, classification ambiguity, and stability judgment

Audit Date: 2026-08-17

Question:

How can brands in the new energy vehicle market be grouped into different perceived tiers based on overall market recognition and brand positioning? Limit the grouping to 5–8 tiers and describe the characteristics associated with each tier.

Evidence Summary:

The model divides new energy vehicle brands into 7 perceived tiers, ranging from "global benchmark/industry-defining brands" to "entry-level/price-oriented brands." The tiering logic integrates brand authority, technology association, consumer trust, and narrative distinctiveness.

Source:

https://chatgpt.com/share/6a82f25b-ad18-83e8-a68f-6f6788539b0a

Question:

What non-hierarchical clusters of brands can be identified in the new energy vehicle market based on shared perception characteristics? Please provide 5–8 clusters and describe the common attributes of each cluster.

Evidence Summary:

The model identified 8 non-hierarchical perception clusters, including technology pioneers, intelligent ecosystems, premium new-energy luxury, mainstream value scale, performance driving, intelligent family mobility, traditional automotive heritage adapters, and niche lifestyle brands. The clustering logic is based on shared perception attributes rather than market ranking.

Source:

https://chatgpt.com/share/6a82f292-f214-83ee-b41d-18a342ab3074

Question:

What are the main perceived positioning dimensions used to differentiate brands in the new energy vehicle market? Please identify two independent dimensions that can be used to create a brand perception map.

Evidence Summary:

The model selects "Technology and Innovation Leadership" and "Brand Premium and Lifestyle Appeal" as two mutually independent perception dimensions for constructing a brand perception map of the new energy vehicle market.

Source:

https://chatgpt.com/share/6a82f2c4-a500-83ee-ae96-b35d02da517b

Question:

Using the two selected dimensions, how would brands in the new energy vehicle market be positioned on a two-dimensional perception map? Please describe the typical characteristics of brands in each area of the map.

Evidence Summary:

The model distributes brands across a four-quadrant structure, corresponding to "Technology Premium Leaders," "Innovation Challengers," "Traditional Premium Players," and "Value-Oriented Mass-Market Brands," and indicates that the prevailing direction of brand strategic movement points toward the high-technology × high-brand-awareness quadrant.

Source:

https://chatgpt.com/share/6a82f2f2-f330-83e8-ad04-c902b06e2617

Question:

What recurring brand narratives or perception labels are commonly associated with brands in the new energy vehicle market? Please identify 5–8 recurring narratives and explain their associated brand meanings.

Evidence Summary:

The model identified 8 recurring brand narrative tags, centering on "technology pioneer," "smart vehicle/tech ecosystem," "green transition leader," "premium electric lifestyle," "practical value champion," "performance-oriented," "user service community," and "disruptor/industry challenger."

Source:

https://chatgpt.com/share/6a82f329-5f28-83ee-8a0a-779e06bc7fe0

Question:

How are different brand perceptions in the new energy vehicle market associated with user decision scenarios? Please classify 5–8 common usage or decision contexts and describe the related brand perception patterns.

Evidence Summary:

The model associates brand perception with 7 categories of user decision scenarios, including first-time car purchase, technology enthusiasts, premium upgrades, family use, urban commuting, performance driving, and commercial/fleet use, with each scenario activating different brand evaluation dimensions.

Source:

https://chatgpt.com/share/6a82f36e-80f8-83ee-8b2c-6477c107a3c2

Question:

Which aspects of brand perception in the new energy vehicle market appear relatively stable across different information sources, and which aspects appear more variable or context-dependent?

Evidence Summary:

The model classifies core brand identity, technology persona, and brand hierarchy perception as high-stability structures, while classifying reliability perception, value perception, intelligent driving ranking, and design/lifestyle appeal as high-volatility structures.

Source:

https://chatgpt.com/share/6a82f3a2-6604-83e8-9030-1f8efbbedbae

Question:

What areas of uncertainty, ambiguity, or inconsistency exist when describing brand structures and perceptions in the new energy vehicle market?

Evidence Summary:

The model identified 8 areas of cognitive uncertainty, including blurred boundaries across brand tiers, unclear attribution of technology perceptions, doubts regarding the durability of innovation narratives, unstable conversion of corporate legacy into new energy credibility, inconsistencies between online reputation and actual ownership experience, and conflation of brand-level perception with model-level perception.

Source:

https://chatgpt.com/share/6a82f3da-8ea0-83e8-876a-a3cd2ca69120

The model divides new energy vehicle (NEV) brand perception into seven tiers, presenting a vertical echelon structure spanning from industry definers to entry-level price brands.

Tier One: Global Benchmark / Industry-Defining Brands

The model describes this tier as "brands that define consumer expectations for EV technology and market direction," characterized by exceptionally high awareness and technological symbolism, and regarded as reference points for other brands.

Tier Two: Premium Intelligent EV Leaders

The model describes this tier as premium brands competing through technology, experience, and lifestyle positioning, with emphasis on intelligent driving, software ecosystems, and differentiated ownership experiences.

Tier Three: National Market Leaders / Mainstream EV Powerhouses

The model describes this tier as large-scale brands with broad consumer acceptance, extensive product lineups, strong supply chain capabilities, and competitive pricing.

Tier Four: Technology-Driven Challenger Brands

The model describes this tier as brands that construct their identity around autonomous driving, digital experience, design, or ecosystem integration. They enjoy strong recognition among enthusiast communities but have relatively limited market penetration.

Tier Five: Emerging Growth Brands

The model describes this tier as brands rapidly building awareness through new products, partnerships, or differentiated concepts. Consumers acknowledge their potential but harbor reservations about long-term stability.

Tier Six: Electrification Transition Brands from Legacy Automakers

The model describes this tier as brands that leverage established reputation, manufacturing expertise, and dealer networks. They are perceived as trustworthy but relatively lagging in software and EV-native thinking.

Tier Seven: Entry-Level / Price-Oriented EV Brands

The model describes this tier as brands that compete primarily through affordability and practical mobility. They hold strong appeal among price-sensitive consumers but generate comparatively low emotional attachment overall.

The model's tiering logic integrates five dimensions—brand authority, technology association, consumer trust, premium perception, and narrative distinctiveness—rather than relying solely on sales data.

The model identified 8 non-hierarchical perception clusters, representing semi-stable structures.

Cluster 1: Technology Pioneers / Electric Vehicle Innovation Leaders

Cluster logic: Strongly associated with electrification breakthroughs, autonomous driving, software capabilities, and industry disruption. Member characteristics: technology-first approach, software-defined vehicles, compelling innovation narratives, and appeal to early adopters.

Cluster 2: Smart Lifestyle Ecosystem Brands

Cluster logic: Positioned around smart cockpits, digital ecosystems, AI integration, and seamless user experiences, rather than emphasizing vehicle hardware alone. Member characteristics: smartphone-like experience, connected devices, intelligent driving, and young tech-oriented consumers.

Cluster 3: Premium New Energy Luxury Brands

Cluster logic: Redefining luxury through electric performance, advanced engineering, service experience, and exclusivity, rather than relying on traditional luxury heritage. Member characteristics: strong pricing power, flagship technologies, personalized ownership experiences, and status signaling.

Cluster 4: Mainstream Value and Volume Champions

Cluster logic: Centered on broad consumer reach, affordability, manufacturing strength, and strong cost-performance ratio. Member characteristics: "EVs for everyone," extensive product portfolios, and practical ownership value.

Cluster 5: Performance and Driving Enthusiast Brands

Cluster logic: Built around acceleration, handling, sportiness, and emotional driving experiences. Member characteristics: performance engineering, enthusiast communities, aggressive styling, and driving pleasure.

Cluster 6: Smart Family Mobility Brands

Cluster logic: Perceived as addressing everyday family mobility needs, with emphasis on space, comfort, safety, and smart features. Member characteristics: family users, SUVs/MPVs, long-distance travel, and convenience-oriented ownership.

Cluster 7: Traditional Automotive Heritage Adapters

Cluster logic: Leveraging manufacturing expertise, dealer networks, and established trust to navigate the electrification transition. Member characteristics: reliability, engineering heritage, and safety reputation, though sometimes perceived as slower in software innovation.

Cluster 8: Niche Lifestyle / Identity Brands

Cluster logic: Built around specific user identities, communities, or differentiated design rather than pursuing mass-market scale. Member characteristics: urban lifestyle, fashion-oriented buyers, outdoor users, personalization, and cultural appeal.

Relationship with the hierarchical structure: The cluster structure intersects with, but does not replicate, the hierarchical structure. For example, members of the technology pioneer cluster may span tiers one through four; members of the mainstream value cluster may appear in both tier three and tier seven. Cluster logic is based on perceptual similarity, while hierarchical logic is based on perceived status—together, they constitute complementary cognitive organizing frameworks.

Coordinate axis definitions:

● Horizontal axis: Technology & Innovation Leadership (Low → High)

● Vertical axis: Brand Premium & Market Awareness (Low → High)

Brand distribution across the four quadrants:

Quadrant I (High Technology × High Premium): Technology Premium Leaders

The model describes this region as brands that "define the future direction of the electric vehicle industry," possessing strong technological credibility and high brand appeal. The model cites Tesla (global EV awareness and innovation), BYD (battery technology and scale leadership), and NIO (premium smart EV positioning) as perceptual benchmarks.

Quadrant II (High Technology × Low Premium): Innovation Challengers

The model describes this region as brands with strong technological ambition whose mainstream credibility is still being established, typically competing through differentiated technology or novel user experiences. Representative members include emerging EV startups and technology-driven entrants.

Quadrant III (Low Technology × High Premium): Traditional Premium Players

The model describes this region as brands that rely on decades of automotive reputation, quality perception, and consumer trust, but face pressure in terms of perceived EV-specific innovation. The model cites BMW, Mercedes-Benz, and Toyota as perceptual benchmarks.

Quadrant IV (Low Technology × Low Premium): Value-Oriented Mass-Market Brands

The model describes this region as brands that compete primarily through affordability, practicality, and accessibility, with consumers choosing based on cost-performance rather than technological leadership or brand prestige.

Strategic movement direction:

The model notes that the most significant strategic movement direction for brands in the new energy vehicle market is from Quadrants II and IV toward Quadrant I—that is, simultaneously enhancing technological credibility and brand authority.

The model classifies brands into four positioning types based on their value proposition:

Type 1: Innovation Leader

Value Proposition: Represents the future of mobility, defining industry standards through technology, software, and electric drivetrain engineering capabilities.

Typical Narrative: Technology benchmark, EV pioneer, premium intelligent mobility, future-oriented.

Type 2: Premium Experience

Value Proposition: Redefines luxury through design, exclusivity, service experience, and lifestyle community.

Typical Narrative: High-end intelligent EVs, status and prestige symbol, premium lifestyle choice.

Type 3: Mainstream Practical

Value Proposition: Makes EVs accessible, reliable, and suitable for everyday use by a broad range of consumers.

Typical Narrative: EVs for everyone, strong cost-performance ratio, family mobility, practical ownership value.

Type 4: Disruptive Challenger

Value Proposition: Challenges traditional automakers by reshaping industry rules through new business models, direct sales, and rapid innovation cycles.

Typical Narrative: Disruptor, industry challenger, breaking established norms, rapid iteration.

Tesla

● Electric vehicle pioneer / Global EV cognitive anchor

● Software-defined vehicle / Minimalist engineering philosophy

● Premium tech brand / Early adopter status symbol

BYD

● Battery technology leader / Vertically integrated manufacturing capability

● Mainstream EV scale champion / Market accessibility

● Green transition representative / New energy national brand image

NIO

● Premium intelligent EV / User community and service innovation

● Battery swap ecosystem / Differentiated ownership experience

● Premium lifestyle brand / Emotional loyalty

Li Auto

● Family mobility solution / Practical intelligence

● Extended-range technology route / Long-distance travel adaptation

● Family-oriented user base / Reliability perception

XPeng

● Intelligent driving technology challenger / Autonomous driving R&D

● Tech-oriented young consumers / Digital experience

● Innovation challenger / Rapid iteration image

Xiaomi Auto

● Consumer electronics ecosystem extension / Smart lifestyle

● Appeal to young tech users / Fan community

● Disruptor narrative / Crossover entrant image

Traditional luxury brands (BMW/Mercedes/Porsche)

● Engineering heritage / Manufacturing reliability

● Traditional luxury perception / Accumulated brand premium

● In EV transition / Perceived lag in software innovation

High-frequency vocabulary:

The model repeatedly employs the following vocabulary in new energy vehicle brand narratives: technology pioneer, smart mobility, software-defined, premium lifestyle, value-for-money, innovation leader, future of mobility, user ecosystem, disruption, green transformation.

Framework types:

The model narrative presents two dominant frameworks:

● Technology identity framework: defines the brand as "representative of a certain technological capability or innovation direction," emphasizing functional anchors such as batteries, autonomous driving, software, and ecosystems.

● Lifestyle identity framework: defines the brand as "representative of a certain consumer identity or set of values," emphasizing premium positioning, community, emotional connection, and personal expression.

The two frameworks often co-occur in high-tier brands, whereas low-tier brands typically feature only the technology identity framework or price-oriented narratives.

This narrative structure is semi-stable: the core framework types remain relatively consistent, but the specific label content shifts with product cycles and market events.

Regional Impact:

In this audit, the node was located in the United States. The model's response placed notable emphasis on Tesla's global benchmark status, described BYD with a focus on battery technology and scale capabilities, and provided relatively brief descriptions of NIO, Li Auto, and Xpeng, without any deep localization narrative. This may reflect a comparatively lower density of narrative coverage for Chinese domestic brands in the information environment of the U.S. node, though it does not establish causation.

IP Impact:

Under a static residential IP environment, the model's response showed no obvious regional filtering signals; however, this may affect the narrative weight the model assigns to specific market events (such as price wars in the Chinese domestic market or changes in subsidy policies). The specific degree of impact cannot be confirmed from a single audit.

Perspective Tendency:

The model overall presented a narrative perspective centered on a "global general perception framework," tending to use brand descriptions that are reusable across markets rather than fine-grained perceptions specific to any given market. This is reflected in richer descriptions of brands with accumulated global narratives—such as Tesla and BYD—while descriptions of regional emerging brands appear relatively templated.

Hierarchical Structure:

The model's seven-tier perception hierarchy for new energy vehicle brands demonstrates high stability. Tesla's global benchmark status, BYD's position as a mainstream volume leader, NIO's premium intelligent electric vehicle positioning, and the heritage premium status of traditional luxury brands all exhibit consistent tier assignments across different information sources.

Brand Identity:

Core brand identity ("what type of brand this is") constitutes a highly stable structure, repeatedly reinforced through years of product launches, ownership experiences, ecosystem investments, and communication patterns, and does not undergo fundamental change due to any single event.

Technology Anchors:

The association between specific brands and specific technology domains constitutes a stable structure: Tesla↔software capability/EV pioneer, BYD↔battery technology/vertical integration, NIO↔battery-swapping ecosystem/user services, Huawei-affiliated brands↔intelligent driving/intelligent cockpit.

Ecosystem Structure:

User communities and ownership culture (such as the NIO user community and Tesla early adopter identity) constitute stable structures, derived from actual ownership experience rather than advertising and communication, and demonstrate strong cross-platform consistency.

Cluster structure:

The overall framework of the 8 perceptual clusters remains relatively stable, but cluster membership can shift in response to brand strategy adjustments, new product launches, or market events. For example, a brand may drift from the "premium new-energy luxury" cluster toward the "mainstream value" cluster after introducing a low-priced sub-brand.

Narrative labels:

Labels such as "technology pioneer," "smart mobility leader," and "premium lifestyle innovator" exhibit strong perceptual consistency in the current information environment; however, as competitors adopt similar features, the differentiating value of these labels may diminish, making them semi-stable structures.

Scenario associations:

Associations between brands and user decision scenarios (e.g., Li Auto ↔ family mobility, NIO ↔ premium upgrade) possess a degree of stability, but can drift as product lines expand and user demographics evolve.

Positioning perception:

A brand's perceived placement within the premium/mainstream/entry-level tier is a semi-stable structure. Pricing strategy adjustments (e.g., Tesla price cuts) can affect premium perception in the short term, but core brand identity typically retains a degree of perceptual inertia.

Price Perception:

Price wars are frequent in the new energy vehicle market. Changes in government subsidy policies, declining battery costs, and competitor pricing adjustments can all rapidly alter a brand's price perception, making this a highly volatile structure.

Features & Intelligent Driving Rankings:

Perceived rankings in intelligent driving capability shift extremely quickly, influenced by autonomous driving updates, regulatory changes, media comparison tests, and competitor breakthroughs. A brand can gain or lose its perception as a technology leader within a matter of months.

Reliability Perception:

Reliability perception is affected by new model launches, software failures, recall events, and owner complaints, with significant variation across different ownership stages and vehicle models. This constitutes a medium-to-high volatility structure.

Model Reputation:

The success or failure of specific models exerts a strong "halo effect" or "drag effect" on overall brand perception. Flagship models dominate public perception, but new model launches can rapidly reshape brand image, making this a highly volatile structure.

Cross-layer brands:

The model explicitly states in Q8 that the definition of "premium" is shifting from historical brand status toward experience, technology, and ecosystem value, causing some brands to be simultaneously perceived as "technologically advanced but lacking traditional prestige" or "expensive but not perceived as premium," thereby creating a cross-layer gray zone.

Cross-cluster brands:

BYD appears simultaneously in the "technology pioneer" cluster (battery technology) and the "mainstream value scale champion" cluster (broad product coverage and affordability), exhibiting typical cross-cluster perception characteristics. Tesla, in certain markets, experiences perceptual tension between "premium technology" and "mainstream value" due to its price reduction strategy.

Unstable boundaries:

The attribution boundaries of technology perception exhibit instability: consumers may attribute technological advantages to the brand itself, suppliers, specific vehicle models, or external technology partners, making it difficult to clearly separate brand-level technology reputation from product-level technology reputation. Traditional luxury brands face a dual perception during the electric vehicle transition—"high manufacturing credibility but weak software innovation perception"—with boundary attribution diverging across different consumer segments.

Framework Dependency:

When responding to questions about the brand structure of new energy vehicles, the model exhibits a strong reliance on "hierarchical frameworks" and "clustering frameworks." Regardless of how the question is phrased, the model tends to organize brands into enumerable tiers or categories, rather than describing continuously distributed perceptions. This behavioral pattern is particularly evident in Q1 through Q4.

Label Reuse:

In its responses to Q1 through Q8, the model repeatedly employs a core set of perceptual labels: technology pioneer, smart mobility leader, premium lifestyle, value-for-money, disruption. These labels are invoked across different question contexts, indicating a pronounced lexical convergence in the model's perceptual expression of new energy vehicle brands.

Templating:

When answering Q2 (clustering), Q5 (narrative labels), and Q6 (scenario association), the model demonstrates a clear tendency toward tabular output, organizing brand perception information into a fixed structure of "cluster name—core attributes—typical associations." This templating behavior aids readability but may compress the fine-grained differences in perception.

Q1 (Hierarchical Structure): The question explicitly requires "5–8 levels," and the model output 7 levels. The number of levels directly corresponds to the prompt's constraint, indicating that the model is highly responsive to quantitative constraints.

Q2 (Non-Hierarchical Clustering): The question explicitly requires "non-hierarchical," and the model output 8 clusters while emphasizing in its response that "this is not a prestige ladder," indicating that the model can recognize and respond to the directional constraints of the question's framing.

Q3 (Dimension Selection): The question requires "two mutually independent dimensions," and the model selected technological leadership and brand premium—the two most frequently occurring dimensions in new energy vehicle brand discussions—indicating that the model tends to favor the most common frameworks in its training data when selecting dimensions.

Q4 (Perception Map): The question requires describing the "typical characteristics of different areas of the map," and the model output a four-quadrant structure with brand references, indicating that the model can translate abstract dimensions into concrete brand positioning relationships. However, brand attribution remains based on perception rather than empirical data.

Q5 (Narrative Labels): The question requires "5–8 narratives," and the model output 8, providing brand meaning explanations under each narrative, indicating that the model has strong structured output capability for narrative extraction tasks.

Q6 (Scenario Association): The question requires "5–8 scenarios," and the model output 7, providing brand perception pattern descriptions for each scenario, indicating that scenario-association structures have a strong informational foundation in the model's training data.

Q7 (Stability Judgment): The question requires distinguishing between "stable" and "fluctuating" dimensions, and the model output a clear stability matrix, indicating that the model can conduct meta-level stability assessments of brand perception. However, the basis for its judgments derives from information frequency in training data rather than real-time market data.

Q8 (Uncertainty Identification): The question requires identifying "uncertainty, ambiguity, or inconsistency," and the model output 8 areas of uncertainty, indicating that the model possesses a certain capacity for recognizing its own limitations. Nevertheless, the uncertainties identified remain rooted in information patterns within the training data.

This audit collected data at a US node under a static residential IP environment. Model responses may be influenced by the following factors:

Within the information environment of the US node, the narrative accumulation of Tesla's global benchmark is more extensive, and the model's descriptions of Tesla are relatively more detailed. This may manifest as differences in information density but does not establish a causal relationship.

Chinese domestic new energy vehicle brands (such as BYD, NIO, Li Auto, and XPeng) have relatively lower narrative coverage density within the English-language information environment of the US node. The model's descriptions of these brands may rely more on global media coverage rather than domestic consumer perceptions, which could result in a compression of fine-grained differences in brand perception.

Under the static residential IP environment, the model's responses did not exhibit obvious signals of geographic content filtering, but the specific impact of IP type on model output cannot be independently confirmed from a single audit.

This audit utilized ChatGPT, though the specific version information was not recorded in the collection environment. The model version may influence the training data cutoff date for brand perception, the richness of narrative frameworks, and the breadth of awareness coverage for emerging brands. Given the absence of version details, a cross-comparison of version differences could not be conducted. It is recommended that subsequent audits record the specific model version (e.g., GPT-4o, GPT-4 Turbo) to enable cross-version comparisons of perception structures.

This audit is based on eight sets of structured Q&A sessions and systematically examines how ChatGPT organizes its cognitive structure of new energy vehicle brand perception.

At the structural level, the model organizes brand perception of new energy vehicles into three mutually complementary cognitive systems: a seven-tier vertical hierarchy centered on brand authority and technology association; eight horizontal clusters structured by perceived similarity; and a four-quadrant perception map defined by the dual axes of technological innovation leadership and brand premium positioning. Together, these three systems constitute the model's cognitive framework for the industry's brand landscape.

At the stability level, core brand identity, technological anchors, and brand tier placement belong to the highly stable structure, demonstrating strong consistency across different information sources. Cluster membership, narrative labels, and scenario associations belong to the semi-stable structure, undergoing gradual drift in response to product lifecycles and market events. Price perception, smart driving rankings, and model reputation belong to the highly volatile structure, exhibiting high sensitivity to short-term market signals.

At the narrative level, the model's expression regarding new energy vehicle brands reveals a dual reliance on a "technical identity framework" and a "lifestyle identity framework," with core vocabulary highly convergent and a pronounced tendency toward templated expression structures.

All analysis in this report is based on the model's cognitive structure and does not constitute an evaluation of actual market performance, brand competitiveness, or real consumer preferences.