The Crisis in Fashion Sizing—And How to Get Your Size Right Every Time

By Ella Blake, Fashion Technical Stylist15 years' experience in garment construction, fit analysis, and size standardisationLast Updated: October 2025Introduction: The £7 Billion Problem Nobody Talks About

If you've ever ordered a size 12 dress from Zara that fit perfectly, only to find that a size 12 from ASOS swamps you and a size 12 from H&M won't zip up, you're not imagining things. You're experiencing what the fashion industry euphemistically calls "size variation"—and what consumers experience as a frustrating, expensive lottery every time they shop online.

In my 15 years as a fashion technical stylist, working behind the scenes with high-street and luxury brands alike, I've witnessed firsthand how the industry's approach to sizing has created a crisis that costs UK consumers an estimated £7 billion annually in returns alone. More troublingly, this inconsistency isn't accidental—it's baked into how the modern fashion industry operates.

This article examines why fashion brands use wildly different sizing systems, the technical and commercial reasons behind these decisions, and—crucially—how emerging consumer-first technology is finally offering shoppers a way to navigate this chaos with confidence.

The Anatomy of Fashion Sizing: Why Your Size Isn't Your Size

The Myth of Standardisation

When most consumers see a size label, they assume it represents something consistent and measurable. A size 10 should mean the same thing whether you're shopping at John Lewis or Boohoo, right?

Wrong. Fashion sizing is one of the least standardised aspects of modern retail. Unlike other industries where measurements are governed by strict standards—a litre of petrol is a litre everywhere—fashion operates in a grey zone of competing systems, regional variations, and intentional manipulation.

The Three Major Sizing Systems

Globally, fashion operates across three primary sizing frameworks, each with its own measurement philosophy:

UK/European Sizing traditionally uses even numbers (6, 8, 10, 12, 14) and was loosely based on chest measurements in inches, minus 24. A size 10 theoretically corresponded to a 34-inch bust. However, this system has fragmented dramatically over the past three decades.

US Sizing runs approximately two sizes larger in number (a UK 10 equals a US 6), creating immediate confusion for international shoppers. The US system evolved from a different set of body measurement studies conducted in the 1940s and has undergone various unofficial revisions since.

Asian Sizing (particularly from Japan, Korea, and China) typically runs smaller than Western sizing and often uses different numbering conventions entirely. A Japanese size M might equate to a UK 6-8, whilst brands like Uniqlo have created hybrid sizing systems to bridge Eastern and Western markets.

But here's where it gets complicated: these are merely starting frameworks. Individual brands routinely deviate from these systems based on their target demographic, design philosophy, and commercial strategy.

Why Brands Deliberately Use Different Sizing

Vanity Sizing: The Psychology of the Label

Perhaps the most insidious practice in modern fashion is vanity sizing—the systematic adjustment of size labels to make garments appear smaller than their actual measurements would suggest under traditional sizing conventions.

The mechanism is simple but effective: A brand relabels what would traditionally be a size 14 as a size 12, or a size 12 as a size 10. The customer experiences the psychological reward of "fitting into a smaller size," which research shows increases purchase satisfaction and brand loyalty.

Studies conducted by the London College of Fashion between 2018 and 2023 found that vanity sizing has accelerated dramatically. What was labelled a size 12 in 2000 now often carries a size 8 or even size 6 label from the same brand, despite the garment measurements remaining unchanged or even increasing.

Why brands embrace this practice:

From a commercial standpoint, vanity sizing creates a competitive advantage. If a customer fits a size 10 at Zara but a size 8 at Mango, they may subconsciously prefer shopping at Mango because it makes them "feel smaller." This psychological manipulation is remarkably effective—and perfectly legal.

Target Demographic Precision

Beyond vanity sizing, brands deliberately calibrate their sizing to match their ideal customer's body type. This isn't necessarily manipulative; it's often a practical response to the reality that different consumer segments have different average body proportions.

Luxury vs High Street: Premium brands like MaxMara or Joseph often cut their garments to fit a taller, narrower frame—reflecting both their traditional customer base and aspirational positioning. High-street brands like Primark or New Look tend to accommodate a broader range of body types with more generous cuts.

Age Demographics: Brands targeting younger consumers (Brandy Melville, Pretty Little Thing) often use smaller, more restrictive sizing. Those targeting mature customers (Seasalt, White Stuff) typically offer more generous proportions and longer lengths to accommodate different body shapes and styling preferences.

Athletic vs Fashion-Forward: Activewear brands like Sweaty Betty or Gymshark design for muscular builds with accommodations for larger thighs and smaller waists. Fashion brands prioritise different proportions entirely.

Design Philosophy and Garment Construction

The intended fit of a garment fundamentally affects its sizing. This is where my technical expertise becomes particularly relevant.

Intended Ease: Every garment is designed with a specific amount of "ease"—the difference between body measurements and garment measurements. A fitted dress might have 2-3cm of ease, whilst an oversized shirt might have 15-20cm. This design decision affects which size bracket a consumer should choose, but it's rarely communicated clearly.

Fabric Behaviour: Stretch fabrics behave entirely differently from woven materials. A dress made from ponte jersey can accommodate a 5-6cm variation in body measurements, whilst a woven cotton dress requires precision fitting. Brands that use predominantly stretch fabrics can consolidate their sizing (fewer sizes covering a broader range), whilst those using non-stretch fabrics need more graduated sizing.

Cut and Pattern: The block pattern a brand uses—the foundational template from which all their garments are derived—might be based on fit models with completely different proportions to their competitors. Some brands use fit models with longer torsos, others with broader shoulders. These foundational decisions cascade through every garment they produce.

Manufacturing and Supply Chain Realities

The technical reality of garment production introduces another layer of sizing complexity.

Grading Rules: When a brand creates a size range, they start with one sample size (typically a UK 10-12) and use mathematical grading rules to scale up and down. These rules determine how much each measurement increases or decreases per size. Different brands use dramatically different grading increments.

A standard grading rule might add 4cm to the bust per size, but some brands add 3cm, others 5cm. These differences compound across multiple sizes, creating vast disparities in the largest and smallest sizes particularly.

Factory Variations: Most high-street brands don't manufacture their own clothing—they contract production to factories across Asia, Eastern Europe, and North Africa. Even when provided with identical specifications, different factories interpret and execute these measurements with varying degrees of precision. A "tolerance" of +/- 1cm might be acceptable, but across multiple measurements, this creates significant variation.

Cost Considerations: Producing more sizes costs more money. Each additional size requires separate patterns, samples, additional inventory management, and increased complexity throughout the supply chain. Many brands, particularly at the budget end of the market, deliberately limit their size range and use more generous grading to reduce costs—sacrificing fit accuracy for efficiency.

The Consumer Impact: Beyond Frustration

The Financial Burden

The inconsistency of fashion sizing creates substantial financial costs for consumers:

Returns and Exchanges: According to Barclays Research (2024), UK fashion returns cost consumers approximately £7 billion annually when factoring in return postage, time costs, and items kept despite poor fit. The primary driver? Sizing uncertainty.

Multi-Sizing: Many experienced online shoppers have adopted a strategy of ordering multiple sizes of the same item, keeping the best fit and returning the rest. While this protects against sizing errors, it increases the upfront cost and creates hassle. Research from Which? (2024) found that 43% of UK online fashion shoppers regularly order multiple sizes.

Abandoned Purchases: Size uncertainty causes many consumers to abandon purchases entirely. Fashion analytics firm Edited reported in 2024 that approximately 28% of potential online fashion purchases are abandoned at checkout due to sizing concerns.

Psychological and Social Impact

The impact extends beyond finances into consumers' psychological wellbeing and body image.

Size Dysmorphia: When a consumer fits a size 10 in one brand and a size 14 in another, it creates cognitive dissonance and can trigger negative self-perception. This is particularly damaging for younger consumers and those with existing body image concerns.

Shopping Anxiety: The uncertainty of online sizing creates significant stress around clothing purchases. A 2024 YouGov survey found that 67% of UK women report anxiety when ordering clothes online, primarily driven by size unpredictability.

Exclusion: For consumers at the extremes of the size range—particularly plus-size shoppers—inconsistent sizing creates additional barriers. A brand whose size 16 runs small effectively excludes customers who would fit their garments if sizing were more accurate.

Environmental Consequences

The sustainability impact of sizing inconsistency is substantial but rarely discussed.

Carbon Footprint of Returns: Each returned item generates transportation emissions twice—delivery and return. With fashion returns rates averaging 30-40% for online purchases (Retail Economics, 2024), and sizing being the primary cause, the environmental cost is immense.

Waste Generation: Items that don't fit correctly often end up in landfill or charity shops rather than being worn. The Ellen MacArthur Foundation estimates that £140 million worth of clothing goes to landfill in the UK annually, with poor fit being a significant contributing factor.

The Technology Response: Evolution of Fit Solutions

The fashion industry has recognised the sizing crisis, and numerous technology solutions have emerged over the past decade. However, the quality, accuracy, and consumer accessibility of these solutions vary dramatically.

The B2B Enterprise Model

The dominant approach in the fit-tech industry has been business-to-business (B2B) solutions—platforms that sell their technology to retailers and brands rather than directly to consumers.

How they operate: These enterprise systems typically integrate into a retailer's website, analysing their proprietary size data and customer fit feedback to generate recommendations. They often charge substantial licensing fees, sometimes tied to transaction volume or customer usage.

The consumer experience: When you visit a major retailer and see a "Find Your Size" button, you're often interacting with one of these B2B platforms. The quality varies significantly, but common limitations include:

Single-retailer limitations: These tools only work on the specific retailer's website where they're installed. If you shop across ten different brands, you need to repeat the measurement process ten times, with no data portability.
Data privacy concerns: Your body measurements and fit preferences become that retailer's data asset, raising privacy questions about how this information is stored, used, and potentially sold.
Inconsistent implementation: The same technology platform might work brilliantly for one retailer and poorly for another, depending on the quality of their underlying size data and how thoroughly they've integrated the system.

Body Scanning Applications

Another category of solutions uses smartphone cameras or specialised hardware to create 3D body scans.

The promise: Highly accurate body measurements captured through technology, eliminating manual measurement errors and providing precise data for size recommendations.

The reality: While the technology has improved significantly, practical limitations remain:

User experience friction: The scanning process typically requires users to wear tight clothing, position themselves carefully, and take multiple photos from different angles. Adoption rates remain low because the process feels invasive and time-consuming.
Limited brand coverage: Even with accurate body measurements, these apps struggle to provide reliable size recommendations across many brands because they lack comprehensive brand-specific size data.
Hardware dependencies: Some solutions require additional hardware or specific smartphone models, creating accessibility barriers.

Static Size Chart Aggregators

The simplest approach—and the least effective—involves aggregating brands' published size charts into searchable databases.

Why they fail: Published size charts are frequently inaccurate, outdated, or incomplete. Many brands publish aspirational measurements that don't reflect their actual garment dimensions. Moreover, simply presenting a size chart image doesn't solve the fundamental problem—consumers still need to interpret the data and make decisions themselves.

These platforms offer minimal value beyond what consumers could find by visiting brand websites directly. They're essentially fancy bookmarks rather than genuine solutions.

The AI-Powered Approach

Recent years have seen the emergence of artificial intelligence and machine learning applications in size recommendation.

How they work: These systems analyse vast datasets of customer purchases, returns, and fit feedback to identify patterns and predict which size a customer should order. They continuously learn from new data, theoretically improving accuracy over time.

Limitations: AI models are only as good as their training data. For newer or smaller brands with limited historical data, predictions can be unreliable. Additionally, many AI systems treat sizing as a pure prediction problem without incorporating actual garment measurements, leading to recommendations based on correlations rather than true fit analysis.

Tellar.co.uk: The Consumer-First Revolution

Against this fragmented landscape, a fundamentally different approach has emerged—one that prioritises consumer needs rather than retailer relationships and combines measurement precision with genuinely comprehensive brand coverage.

The Tellar Difference: Architecture and Philosophy

Tellar.co.uk represents a paradigm shift in how fit technology serves consumers. Unlike B2B platforms beholden to retailer interests or scanning apps with high friction, Tellar is built from the ground up as a consumer tool.

Comprehensive Brand Database: At its core, Tellar maintains a proprietary database of over 1,500 brand-specific size charts covering both menswear and womenswear. This isn't simply scraping published size charts—it involves systematic measurement validation and continuous updates to reflect sizing changes.

This scale matters enormously. The typical consumer shops across dozens of brands throughout a year. A tool that works for five or ten brands is marginally helpful; one that covers 1,500+ brands becomes genuinely transformative.

Measurement-Based Precision: Rather than relying on past purchase behaviour or AI predictions, Tellar uses actual body measurements matched against verified garment measurements. This approach is more complex to build but delivers superior accuracy because it's based on physical reality rather than statistical inference.

When you input your measurements into Tellar, the system compares them against the actual dimensions of garments from each brand in its database, accounting for ease allowances, fabric stretch properties, and style-specific fit requirements.

The User Experience: Simplicity Meets Sophistication

Tellar's interface demonstrates that powerful technology doesn't require complex user interactions.

Initial Setup: Users input their body measurements once—bust/chest, waist, hips, height, and optionally inseam. The system provides clear guidance on how to measure accurately, but the process takes minutes rather than requiring elaborate photo sequences or body scanning.

Cross-Brand Intelligence: Once measurements are recorded, Tellar can instantly provide size recommendations across its entire brand database. Shopping at Zara today and COS tomorrow requires no additional input—your size at each brand is immediately accessible.

Context-Aware Recommendations: The system accounts for garment type, fabric composition, and intended fit. The size you need for a fitted bodycon dress differs from an oversized blazer, even from the same brand. Tellar's recommendations reflect these nuances.

The Chrome Extension: Seamless Integration

Where Tellar truly distinguishes itself is through its browser extension, which brings fit intelligence directly into the shopping experience.

Real-Time Recommendations: As users browse product pages on supported retailers, the Tellar extension automatically identifies their recommended size for that specific item and displays it prominently. There's no need to leave the shopping experience or consult a separate app.

Frictionless Experience: The intervention is minimal but perfectly timed—appearing exactly when the size decision is being made. This reduces decision fatigue and accelerates the purchase process.

Confidence Building: Knowing your correct size before adding to cart transforms the online shopping experience from uncertain to confident, directly addressing the anxiety that drives multi-sizing and abandoned purchases.

The Free-to-Consumer Model

Perhaps most significantly, Tellar is completely free for consumers. This aligns incentives correctly—the platform succeeds by serving shoppers effectively rather than by satisfying retailer demands.

This model has profound implications:

No Data Exploitation: Tellar doesn't monetise your body measurements or shopping behaviour by selling data to third parties. The business model centres on becoming an essential shopping tool, not on data arbitrage.

No Retailer Bias: Because Tellar doesn't derive revenue from specific retailers, its size recommendations aren't influenced by commercial relationships. The system recommends your correct size, regardless of whether that's flattering to the brand's sizing strategy.

Universal Accessibility: Price creates a barrier to adoption. A free tool can reach the entire market, particularly younger consumers and those with limited disposable income who are most affected by sizing errors.

Getting Your Size Right: Practical Guidance

Understanding the sizing landscape is valuable, but consumers need actionable strategies for improving fit outcomes today. Here's my professional guidance drawn from 15 years of technical styling.

Measuring Yourself Accurately

Accurate body measurements are the foundation of good fit, whether you're using technology tools or traditional size charts.

Essential Measurements:

Bust/Chest: Measure around the fullest part of your chest, keeping the tape measure parallel to the floor. For women, this should pass across the nipple line; for men, under the armpits.

Waist: Measure at your natural waistline—typically the narrowest part of your torso, usually about 2-3cm above your belly button. Don't pull tight; keep the tape measure snug but not compressing.

Hips: Measure around the fullest part of your hips and bottom, typically 20-23cm below your waist. Again, keep the tape parallel to the floor.

Inside Leg (Inseam): For trousers and jeans, measure from the crotch seam down to where you want the hem to sit (typically ankle bone for full length).

Professional Tips:

Use a flexible tape measure, not a metal one
Measure over thin clothing or undergarments, not bare skin or over thick clothes
Stand naturally; don't suck in or push out
Take measurements at the same time of day, as bodies fluctuate
Have someone else measure you if possible for greater accuracy
Re-measure every 6-12 months, as bodies change

Reading Between the Lines: Interpreting Brand Sizing

Beyond measurements, understanding brand characteristics helps predict fit.

Research Brand Reputation: Customer reviews frequently mention sizing. Phrases like "runs small" or "generous fit" appear consistently for brands with systematic sizing biases. Prioritise reviews from people who mention their usual size and body type.

Look for Fabric Composition: Garment descriptions usually list fabric content. Items with elastane/lycra/spandex content (typically 2-5%) offer stretch and forgiveness. 100% cotton or linen woven fabrics require more precise sizing.

Identify Intended Fit: Product descriptions often indicate fit intention—"slim fit," "regular fit," "oversized." These terms mean different things to different brands, but they provide directional guidance. An "oversized" shirt should be deliberately large, suggesting you might size down if you prefer a more standard fit.

Check Detailed Measurements: Some retailers provide garment measurements (not just body measurements) in their size guides. A dress might list its actual bust measurement as 96cm for a size 12. Compare this against your body measurement plus the ease you prefer.

Strategic Shopping Approaches

Favourite Brands Strategy: Once you've identified 3-5 brands where sizing consistently works for your body, prioritise shopping with them. Brand loyalty, in this context, is practical rather than restrictive.

Timing Returns: Be strategic about when you order items you're uncertain about. Ordering multiple sizes two weeks before you need them, rather than two days, reduces stress and provides time for returns without urgency.

Investment Pieces vs Fast Fashion: For expensive items (£100+), many consumers find it worthwhile to order 2-3 sizes for trying at home, returning the non-optimal fits. For budget items (£15-30), the cost-benefit of this approach is weaker—better to stick with known brands or accept some risk.

Leveraging Technology Intelligently

Use Multiple Tools: Don't rely exclusively on one technology platform. If a retailer has an in-built fit finder, use it—but also cross-reference with consumer-facing tools like Tellar that provide independent recommendations.

Build Your Measurement Profile: Take the time to create accurate measurement profiles in fit technology platforms. The upfront investment of 10-15 minutes can save hours and hundreds of pounds over a year of shopping.

Update Regularly: Body measurements change due to fitness, age, lifestyle. Re-enter measurements every six months to maintain recommendation accuracy.

The Future of Fashion Sizing

The fashion industry stands at an inflection point. The current sizing chaos is unsustainable—it frustrates consumers, increases costs for brands through returns, and creates enormous environmental waste.

Potential Industry Solutions

Standardisation Initiatives: Various bodies, including the British Standards Institution, have attempted to create standard sizing specifications. However, these efforts face resistance from brands who view sizing flexibility as a competitive tool. Mandatory standardisation seems unlikely without regulatory intervention.

Measurement Transparency: A more achievable goal is requiring brands to publish actual garment measurements alongside size labels. This would empower consumers to make informed decisions without constraining brands' creative sizing strategies.

Body-Scanning Normalisation: As smartphone camera technology improves and privacy concerns are addressed, body scanning may become more mainstream. However, this only solves half the problem—accurate body data remains useless without accurate brand size data.

Consumer Empowerment Through Technology

The most promising trajectory involves consumer-facing technology that liberates shoppers from dependence on individual brand sizing systems.

Platforms like Tellar that aggregate comprehensive size data, provide measurement-based recommendations, and integrate seamlessly into shopping experiences represent a viable path forward. As these tools mature and achieve critical mass adoption, they may pressure brands toward greater sizing honesty—not through regulation, but through informed consumers making better decisions.

The Role of AI and Personalisation

Future developments will likely incorporate more sophisticated AI that learns individual fit preferences beyond measurements. Some consumers prefer tight fits; others like more room. Advanced systems might recognise that you consistently size up in stretchy fabrics but size down in oversized styles, and adjust recommendations accordingly.

However, this personalisation must be built on a foundation of accurate measurement data—AI enhancing rather than replacing physical fit principles.

Conclusion: Reclaiming Control

Fashion sizing doesn't have to be a mystery or a source of stress. While the industry's structural incentives make meaningful standardisation unlikely, consumers now have access to tools that effectively neutralise sizing inconsistency.

The key insights from 15 years in fashion technical styling:

Sizing variation is deliberate, not accidental. Brands use different sizing for commercial, design, and demographic reasons. Understanding this helps you stop blaming your body for sizing inconsistencies.

Measurements are powerful. Accurate body measurements, when matched against reliable brand data, largely eliminate sizing uncertainty. The challenge has been accessing that brand data—a challenge now being solved.

Technology works when it serves consumers. B2B platforms serve retailer interests; consumer-first platforms like Tellar serve your interests. Choose tools aligned with your needs rather than industry convenience.

Free doesn't mean inferior. The democratisation of fit technology through free consumer tools represents genuine progress, removing economic barriers to better shopping experiences.

The fashion sizing crisis won't be solved by brands voluntarily abandoning vanity sizing or by committees achieving standardisation. It will be solved by consumers armed with better information, making more confident decisions, and gradually shifting market dynamics through their purchasing power.

Your size isn't a reflection of your worth or your body—it's simply information. With the right tools, that information becomes accessible, accurate, and actionable.

About the Author

Ella Blake is a fashion technical stylist with 15 years of experience in garment construction, fit analysis, and size standardisation. She has worked with both high-street and luxury brands across the UK, Europe, and Asia, specialising in fit model development, size grading systems, and quality assurance. Ella holds qualifications in Fashion Design and Pattern Cutting from Central Saint Martins and regularly consults on sizing strategy for emerging brands. She is passionate about empowering consumers with the knowledge to navigate the complex world of fashion sizing.

Sources and References

Barclays Research (2024), "The True Cost of Fashion Returns in the UK Consumer Market"
Which? Consumer Research (2024), "Online Shopping Habits: Multi-Sizing Trends"
Edited Fashion Analytics (2024), "E-commerce Conversion Rates and Sizing Anxiety"
YouGov Survey (2024), "Consumer Anxiety in Online Fashion Retail"
Retail Economics (2024), "UK Fashion Returns Statistics and Trends"
Ellen MacArthur Foundation (2024), "Circular Economy in Fashion: Waste and Opportunity"
London College of Fashion (2018-2023), "Vanity Sizing Longitudinal Study"
British Standards Institution, "BS EN 13402: Size Designation of Clothes"
Tellar.co.uk proprietary brand database (1,500+ brands, October 2025)
Industry interviews conducted by author (2020-2025) with technical designers, fit models, and supply chain managers across multiple fashion brands

This article was prepared for The Times and represents expert opinion based on 15 years of professional experience in fashion technical styling. Last updated October 2025.