3D product configurator performance guide

Make the whole configuration journey feel immediate.

High-performance 3D product configurator software coordinates the page, product controls, rules, pricing, WebGL assets and GPU lifecycle. This guide turns Core Web Vitals, first useful product view, option response, mobile rendering and long-session stability into a measurable architecture for manufacturers, brands, retailers, dealers, installers and ecommerce teams.

Define test scope Plan performance

One customer action

InputFinish, dimension or module selected

DecideRules validate one accepted state

Present3D frame shows the completed change

PriceCommercial result reaches the same revision

SustainResources remain stable after repeated edits

Performance is a timeline

A downloaded file is not yet a usable configurator.

Customers experience a sequence: the page explains the offer, controls become operable, product rules and pricing initialize, a recognizable product appears, the first interaction responds, and repeated changes remain stable. Measure each transition separately so a fast network result cannot hide main-thread, GPU or commercial-service delays.

Useful HTML

Can the visitor understand the product and next action before 3D is ready?

Measure: Page content, layout stability, primary action and fallback state

Failure: A blank or shifting canvas blocks product meaning and conversion.

Controls operable

Can the buyer inspect choices while richer scene resources continue loading?

Measure: Control-ready event, input delay and unavailable-state explanation

Failure: Controls look ready but queue, ignore or overwrite early input.

Rules and price ready

Is the current configuration commercially meaningful?

Measure: Rule initialization, price-service response and revision identity

Failure: The scene appears complete while options or price are stale.

First useful product view

Can the customer recognize the configured product at a useful camera position?

Measure: Required model, material, camera and render completion—not only file download

Failure: A spinner disappears before the scene is intelligible or stable.

First camera interaction

Does the first orbit, pan or named-view action respond immediately?

Measure: Input, processing, presentation and frame continuity

Failure: Decode, shader or upload work collides with the buyer's first gesture.

First option response

Does a finish, dimension or module change produce one coherent update?

Measure: Option input to visual, price and validation completion

Failure: The control, scene and total update at different times or in the wrong order.

Full-quality scene

Have deferred textures, effects and optional modules completed without disrupting use?

Measure: Deferred-resource completion, visual quality and post-load interaction

Failure: Late work causes layout movement, stutter or surprising network consumption.

Long-session stability

Can users change products and options repeatedly without degradation?

Measure: Memory, GPU resources, frame time, context loss and event/listener growth

Failure: Each reconfiguration leaves resources behind until the tab slows or crashes.

Interactive performance scope planner

Start with the product, device and delivery context.

Select the environment to expose the minimum evidence boundary. A public mobile configurator, a dealer desktop tool and an all-day showroom experience do not fail in the same ways, even when they use the same catalogue and renderer.

Delivery channel

Public product pageAcquisition, content, consent and the 3D journey share one page-performance budget.Dealer or sales portalRepeat sessions, saved projects, customer records and pricing calls shape the workload.Embedded configuratorThe host page, iframe or component and cross-boundary events must be measured together.

Primary device

Mid-range mobileVariable networks, shared memory, touch input, high-density displays and thermal limits.Everyday desktopReal customer and dealer hardware—not only a developer workstation with a discrete GPU.Showroom sessionLarge displays, repeated products and long sessions make memory cleanup and stability visible.

Scene under test

Representative productThe normal scene and option set most buyers are expected to use.Largest valid sceneThe heaviest permitted modules, finishes, accessories, shadows and repeated components.Made-to-measure sceneGenerated geometry, repeated parts and rule-driven updates after dimensions change.

Performance evidence boundary

Measure the actual sales environment.

This planner defines the minimum diagnostic scope. It does not invent universal byte, polygon or frame-rate limits; set those from measured target products and devices.

Record LCP, INP and CLS at the 75th percentile, then add first useful product view, option response and frame-time evidence.
Include acquisition content, consent, analytics, fonts and the public product page in the same loading and interaction budget.
Use physical mid-range phones and test variable networks, touch, high-density rendering, memory pressure and sustained thermal load.
Establish the representative product baseline before comparing the heaviest valid scene and optional features.
Capture exact code, asset, product-data and pricing revisions so every regression or improvement can be reproduced.

Runtime work decomposition

Find the stage that is actually slow.

Network size, JavaScript execution, decoding, scene creation and rendering are different work. Record them as separate stages with exact build and asset revisions; otherwise an apparent improvement can simply move cost from transfer to CPU, GPU or the buyer's first interaction.

Network delivery

HTML, JavaScript, CSS, glTF/GLB, textures, decoders, fonts, product data and API calls

Evidence: Request waterfall, cache state, transferred and decoded sizes, priority and failure behavior

JavaScript startup

Download, parse, compile, evaluation, hydration, listeners and framework initialization

Evidence: Main-thread profile, long tasks, unused startup code and control-ready timing

3D parse and decode

Container parse, geometry decode, texture transcode, image decode and dependency resolution

Evidence: Per-stage duration, worker use, failure paths and representative-device traces

Scene construction

Nodes, materials, instances, rules, generated geometry, bounding data and camera framing

Evidence: Construction time for normal and largest valid configurations

GPU preparation

Texture upload, buffers, shader compilation, render targets and first-frame warm-up

Evidence: First-render trace, memory estimate, program count and visible first-interaction stutter

Continuous rendering

Draw calls, fill rate, pixel ratio, lighting, shadows, transparency, effects and animation

Evidence: Frame-time distribution during camera motion and demanding valid scenes

Configuration response

Rule evaluation, pricing, geometry changes, material changes, API work and state coordination

Evidence: Input-to-visual, input-to-price and complete-state timings with revision IDs

Cleanup and recovery

Disposed geometry, materials, textures, render targets, workers, events and WebGL context recovery

Evidence: Repeat-cycle memory profile, context-loss test and stable resumed configuration

Metric dictionary

Combine web standards with product-specific milestones.

Core Web Vitals protect loading, responsiveness and stability across the page. A 3D sales journey also needs custom events that describe when the product, commercial state and repeated interaction are genuinely ready.

Largest Contentful Paint (LCP)

Loading experience for the page's largest visible content element

Use the Core Web Vitals good threshold of 2.5 seconds or less at the 75th percentile, while verifying which element becomes LCP.

Interaction to Next Paint (INP)

Responsiveness across interactions during the page visit

Use the Core Web Vitals good threshold of 200 milliseconds or less at the 75th percentile and inspect input, processing and presentation delay.

Cumulative Layout Shift (CLS)

Visual stability while the page, viewer, controls and consent layers load

Use the Core Web Vitals good threshold of 0.1 or less at the 75th percentile and reserve viewer and control space deliberately.

First useful product view

When the customer can recognize the configured product in a useful view

Define the required model, material, camera and stable render conditions as a product-specific event.

Option-to-visual response

How quickly a choice becomes visibly complete

Measure input, rule decision, scene mutation and presented frame—not only the event handler duration.

Option-to-price response

How quickly the commercial consequence becomes current

Separate local calculation, network work, document rules and final displayed revision.

Frame time distribution

Camera and animation fluidity across ordinary and difficult states

Retain percentiles and dropped/slow-frame evidence; an average can hide severe stutter.

Memory and context stability

Whether repeated use remains reliable

Track heap trends, estimated GPU resources, context loss, recovery and resource counts over scripted cycles.

Layered performance budgets

Budget by when the resource earns its place.

Universal polygon, texture and megabyte limits are rarely credible. Set measured budgets for the target route, device, network and accepted scenes, then separate what is required now from what can arrive later or only after intent.

Initial and critical

The content, controls, rules, minimum code and product resources needed to understand the offer and reach the first useful product view.

Examples: HTML shell, critical styles, product metadata, essential runtime, base model and first-view materials

Deferred but expected

Resources that improve quality after the buyer can already use the experience and must not interrupt an active interaction.

Examples: Higher-detail textures, secondary viewpoints, optional modules, nonessential effects and export tooling

Conditional and optional

Resources loaded only after intent, visibility, feature use or a compatible product choice makes them necessary.

Examples: AR path, rare accessories, heavy document preview, alternative product families and diagnostic tools

WebGL and mobile GPU control

Design for finite graphics resources.

Browser and device limits vary. Treat textures, draw work, resolution and lifecycle as a governed runtime budget, then degrade visual cost deliberately before the page loses interaction, context or the customer's configuration.

Texture memory

Record dimensions, channels, mipmaps and runtime format. A compact JPEG or PNG transfer can occupy far more memory after decoding; KTX 2.0 and supported GPU formats can reduce both delivery and runtime pressure.

Draw and material work

Measure draw calls, material programs, transparency, lights, shadows and post-processing. Geometry count alone does not explain render cost.

Resolution and fill rate

High device-pixel ratios multiply the pixels rendered. Define when the back buffer, shadow maps or effects can use a lower resolution without harming a buying decision.

Instancing, LOD and culling

Reuse repeated components, reduce distant detail and avoid drawing work outside the useful view. Validate that optimization never changes quantities, identity or visible commercial state.

Thermal and long-session behavior

Test sustained interaction on physical phones and showroom hardware. Short desktop profiles do not reveal throttling, accumulated resources or device-specific context loss.

Cleanup and context recovery

Dispose superseded geometry, materials, textures and render targets deliberately. Test a lost WebGL context and restore the accepted configuration without duplication or stale state.

Main thread and interaction

Protect the next customer action.

Long tasks block input even when the scene is visually complete. Code splitting, scheduling, yielding and workers can help, but the right change begins with a trace of input delay, processing and presentation on the complete host page.

Reduce startup JavaScript

Load the code required for the current product journey; defer AR, export, rare tools and alternate catalogues until intent.

Break long work apart

Split independent work and yield so the browser can present feedback and respond between chunks instead of monopolizing one task.

Move suitable work off-thread

Use workers for supported decode, parse or calculation paths when transfer and coordination cost produce a measured benefit.

Measure presentation delay

A quick event handler is not enough if scene mutation, style, layout or rendering delays the next visible frame.

Loading, caching and failure

Progressive does not mean unpredictable.

Reserve stable viewer space, publish useful HTML, prioritize the minimum accepted product and make deferred work visible without interrupting the buyer. Cache immutable assets by revision, refresh changing commercial data deliberately and design a usable outcome when any dependency fails.

Critical delivery

Prioritize the page shell, essential runtime and first-view product assets. Prevent low-value requests from competing with the first useful state.

Revision-aware caching

Use immutable hashed assets and a content delivery network while keeping product rules, price and authorization freshness explicit.

Recovery contract

Name the failed stage, preserve valid choices, provide retry and retain a readable product, price or contact route when 3D is unavailable.

Performance acceptance tests

Prove speed under real configuration pressure.

A release pack should identify the exact page, host environment, product revision, runtime build, asset revision, device, browser, network, cache state and expected outcome. Repeatable scenarios turn performance from an impression into acceptance evidence.

Cold-load the representative product on a target mobile device and captured network profile.

Cold-load the largest valid configuration with every required decoder and texture path uncached.

Repeat with a warm cache and prove immutable assets are reused while changed product data refreshes.

Interact at the moment the first useful view appears and inspect input, processing and presentation delay.

Change a finish, dimension, module and incompatible option while tracing visual, price and validation completion.

Orbit and zoom the normal and largest scenes while recording frame-time distribution rather than average FPS alone.

Run repeated product-switch and reconfiguration cycles while tracking heap, GPU-resource proxies and listener counts.

Background and restore the tab, rotate a phone and resize the viewer without losing the saved configuration.

Simulate a missing model, texture, decoder and price response; verify readable fallback, retry and preserved work.

Force WebGL context loss in a controlled test and confirm recovery or a useful non-3D completion route.

Measure the configurator inside the real host page with analytics, consent, chat, fonts and marketing scripts active.

Compare field data by release, route, device tier, product family and scene size before accepting an optimization.

Common performance failures

Avoid optimizations that only move the delay.

Performance work fails when one convenient metric stands in for the customer journey. Review these patterns during architecture, procurement and every major catalogue or runtime change.

Optimizing the file, not the journey

A compressed model can still require decoder code, expensive texture upload, shader work and a blocked main thread. Accept total time to useful interaction.

One device represents every buyer

A developer laptop hides mobile CPU, memory, GPU, network and thermal constraints. Define a maintained physical-device matrix.

Average FPS becomes the verdict

A comfortable average can coexist with repeated long frames during option changes. Use a frame-time distribution and interaction traces.

The canvas owns LCP by accident

If the useful content waits for 3D or the poster is replaced poorly, the page can delay or shift its largest element. Design the HTML and viewer loading sequence together.

Every feature loads up front

AR, export, rare accessories and alternate catalogues consume startup budget before the buyer expresses intent. Split by actual journey and preserve predictable loading states.

A spinner hides missing contracts

One indefinite loading state cannot explain model, rule, price or service failure. Expose stages, timeout, retry and a useful completion route.

Resources disappear only from the scene

Removing an object from a scene graph does not necessarily release GPU buffers, textures or programs. Define and test lifecycle disposal.

Lab scores replace field evidence

A controlled run is repeatable but cannot represent every real device and network. Pair laboratory diagnostics with privacy-conscious real-user measurement.

Implementation roadmap

Turn performance into a maintained operating system.

The strongest programmes connect product milestones, target devices, asset budgets, automated regression and production evidence. They do not wait for customer complaints or a one-off score before deciding who owns the problem.

Define journeys and milestones

Product + performance owner

Name the pages, products, first useful view, first interaction, option response and completion events that matter commercially.

Evidence: Measurement dictionary and event contract

Build the representative matrix

QA + engineering

Select ordinary and largest valid scenes, devices, browsers, networks, cache states and embedded-host conditions.

Evidence: Versioned test matrix with physical device IDs

Profile before changing

Web + 3D engineering

Capture network, main-thread, decoder, scene, GPU and API work so the team fixes the actual limiting stage.

Evidence: Baseline traces and ranked bottlenecks

Set layered budgets

Architecture + product

Allocate initial, deferred and conditional budgets for code, assets, memory, interactions and long-session stability.

Evidence: Accepted budget table linked to target journeys

Optimize the critical path

Web + 3D engineering

Reduce or move startup work, prioritize useful content and deliver the minimum product representation before optional quality.

Evidence: Before-and-after stage timings and visual approval

Control runtime cost

3D runtime owner

Tune materials, textures, resolution, visibility, repeated components, generated geometry and cleanup for real devices.

Evidence: Frame, memory, context and repeat-cycle results

Automate regressions

QA + platform

Fail releases when accepted asset, code, interaction or stability budgets regress beyond the agreed tolerance.

Evidence: CI reports tied to exact build and asset revisions

Observe and improve in production

Product operations

Segment field signals by release, product, scene, device and route, then reproduce changes in the laboratory.

Evidence: Dashboards, alerts, release annotations and corrective actions

Laboratory + real-user monitoring

Explain what changed, where and for whom.

Segment field signals by route, release, device tier, product family and scene size, then reproduce the affected state in a controlled trace. Retain only the diagnostic data needed and avoid recording customer choices or personal data without a defined purpose and governance.

Laboratory evidence

Repeatable device, network, cache and scene conditions expose stage-level regressions and support before-and-after comparison.

Field evidence

Percentiles and segmented custom events reveal actual audience conditions, affected releases and products that need reproduction.

Release identity

Record code, asset, product-data and pricing revisions so a slow or incorrect session can be tied to a reproducible system state.

Privacy-conscious telemetry

Collect timings, coarse device and scene attributes, errors and revision IDs without retaining unnecessary customer or configuration content.

Procurement and vendor evidence

Ask for traces, not a fast-demo promise.

Use these questions in a product configurator RFP, technical discovery or acceptance workshop. Answers should name the working product, target environment, measurement method and retained proof.

What exact event defines first useful product view, and how is it verified?

Which Core Web Vitals and custom configurator metrics are captured in field and laboratory data?

Which physical mobile, desktop and showroom devices represent the supported audience?

What normal and largest valid product configurations form the acceptance matrix?

Which resources are initial, deferred, conditional and cached, and why?

How are glTF/GLB parse, geometry decode, texture transcode, image decode and GPU upload measured separately?

How are draw calls, materials, transparency, shadows, effects and device pixel ratio controlled?

How does the viewer remain usable while deferred resources load or fail?

How are option-to-visual, option-to-price and validation-complete timings correlated to one configuration revision?

Which work can move off the main thread, and which browser constraints remain?

How are superseded geometry, materials, textures, render targets, workers and events disposed?

What happens after WebGL context loss, memory pressure, offline transition or a failed asset request?

How is the complete host page measured when the configurator is embedded with third-party scripts?

Which automated budget checks block a release, and what evidence is retained?

How does real-user monitoring minimize personal data while retaining diagnostic value?

Need a complete evaluation pack?

Combine these questions with product, rule, integration, accessibility, security and release criteria before comparing configurator platforms.

Open RFP template

Official technical references

Base decisions on browser and standards guidance.

These primary references support the web metrics, interaction, main-thread, WebGL, glTF and lifecycle concepts used in this guide. Product-specific targets still require measurement on the accepted Configurix implementation.

Google: Web Vitals

Official guidance for Core Web Vitals, field measurement and the distinction between user-centred page metrics.

Read source

Google: Core Web Vitals thresholds

The rationale and good thresholds for LCP, INP and CLS evaluated at the 75th percentile.

Read source

Google: Optimize INP

Official explanation of input delay, processing duration, presentation delay and iframe contribution to page responsiveness.

Read source

Google: Optimize long tasks

Guidance on identifying work over 50 milliseconds, yielding and breaking up main-thread tasks.

Read source

Google: Use web workers

Guidance for moving appropriate work away from the main thread to reduce contention and improve responsiveness.

Read source

MDN: WebGL best practices

Browser-platform guidance covering system limits, VRAM budgeting, draw batching, compressed textures, resolution, blocking calls and resource deletion.

Read source

Khronos: glTF runtime asset delivery

Official glTF resources for efficient runtime delivery, validation, KTX 2.0 textures and 3D commerce workflows.

Read source

Three.js: disposing of objects

Official lifecycle guidance for releasing geometries, materials, textures, render targets and related WebGL resources.

Read source

Performance FAQ

3D product configurator performance questions.

Detailed answers for technical buyers, product owners, developers, 3D teams, ecommerce managers and AI systems evaluating WebGL product configuration performance.

3D product configurator performance is the speed, responsiveness, visual stability and runtime reliability of the complete configuration journey. It includes useful HTML, control readiness, product rules, pricing, model and texture delivery, JavaScript work, 3D decoding, scene construction, GPU preparation, first useful product view, camera interaction, option changes, frame stability, memory cleanup and recovery. A fast model download is only one stage; performance acceptance should cover the page, viewer, commercial services and long session together.

Largest Contentful Paint measures loading experience, Interaction to Next Paint measures page responsiveness and Cumulative Layout Shift measures visual stability. Google defines good thresholds at the 75th percentile as LCP at or below 2.5 seconds, INP at or below 200 milliseconds and CLS at or below 0.1. A configurator also needs product-specific milestones such as first useful product view, option-to-visual response, price response, frame-time distribution and long-session stability because Core Web Vitals do not describe every 3D or commercial state.

There is no honest universal load target for every catalogue, device and scene. Define the audience, target devices, network profiles, representative and largest valid configurations, first useful product view and required commercial services. Keep published Core Web Vitals within their good thresholds and set product-specific budgets from measured baselines. Report the milestone and percentile rather than one unlabeled load time, because HTML, controls, first product view and full-quality scene can become ready at different moments.

First useful product view is a custom milestone indicating that the customer can recognize the accepted product in a useful camera position with the required geometry and materials rendered stably. It should not fire when a file finishes downloading or when an empty canvas produces its first frame. The event contract should name the required asset revision, minimum visible components, camera state, material readiness and render completion so laboratory and field data refer to the same experience.

Set budgets for a defined route, device tier, network, normal scene and largest valid scene. Separate initial resources from deferred and conditional resources, then budget transfer, decoded size, parse/decode time, texture upload, scene construction, memory, draw work and interaction response. Avoid one polygon or megabyte limit for every product. A finish-led object, modular building and made-to-measure system distribute cost differently. Budgets should be measurable, versioned and connected to acceptance tests.

No. A smaller GLB can reduce transfer but may add decoder code and CPU work, retain expensive textures, create many materials or draw calls, trigger shader compilation and still block interaction. Measure total time through download, decode, parse, construction, GPU upload, first useful frame and first interaction. Compression is valuable when the complete path improves on target devices and the visual and product contracts remain correct.

Network file size is not the same as runtime texture memory. JPEG and PNG are decoded before sampling, texture dimensions and channels determine the base cost, and mipmaps add levels. Multiple finish maps, normal maps, high device-pixel ratios and render targets increase pressure further. Inventory every runtime texture, remove duplicates, select dimensions by visible use and evaluate KTX 2.0 or supported GPU-compressed formats. Retain visual approval because finish quality is part of the buying decision.

KTX 2.0 can deliver Basis Universal supercompressed textures that transcode to GPU-supported formats, reducing transfer and runtime texture pressure on diverse devices. The runtime must support the relevant glTF extension and transcoder. Measure transcode time, decoder cost, memory, visual quality and first useful interaction for representative products. KTX 2.0 is a delivery technique, not a substitute for sensible texture dimensions, UVs, map selection and caching.

Each draw requires state and command work, so a scene with many separately rendered parts and materials can be expensive even when its polygon count looks modest. Repeated modules may benefit from instancing; compatible parts may share materials; invisible work can be culled; distant details may use an accepted level of detail. Optimization must preserve product identity, visible quantities, selection, compatibility and outputs rather than merging commercially distinct parts blindly.

Profile the complete interaction to separate input delay, handler work and presentation delay. Reduce startup JavaScript, split optional code, break long work into smaller tasks, yield where appropriate and move suitable parsing or calculations to web workers. Avoid doing geometry generation, large state reconciliation, synchronous WebGL queries and pricing work in one blocking turn. Measure the real host page because analytics, chat, consent and an embedded iframe can contribute to responsiveness.

Workers can reduce main-thread contention for suitable work such as supported decoding, parsing, calculations or data transformation. DOM work and many WebGL integration decisions remain constrained by the browser and chosen runtime. Worker startup, transfer, serialization and error handling also have cost. Profile first, define message and revision contracts and verify that moving work actually improves input response and total completion time on target devices.

Deliver useful HTML and stable viewer space first, initialize essential controls and rules, then present the minimum accepted product representation before deferred quality and optional features. Prioritize by the buyer journey rather than by file type alone. Load rare accessories, AR, export tooling or other product families after intent where appropriate. Every stage needs readable progress, timeout, failure, retry and preserved configuration state.

Use maintained physical mid-range and constrained devices as well as emulation. Test cold and warm cache, variable networks, touch input, orientation, high-density displays, browser restore, memory pressure and sustained interaction. Run both a representative and largest valid configuration. Record Core Web Vitals, custom milestones, interaction traces, frame-time distributions, memory trends and context loss. A brief run on a flagship phone does not represent the supported audience.

A browser may lose a WebGL context because of GPU resets, memory pressure, driver behavior, resource limits or competing tabs and applications. A production configurator should handle context-loss events, stop invalid rendering work and either restore resources and the accepted configuration or provide a useful non-3D route. Test the recovery path deliberately. Resource budgets and eager cleanup reduce pressure but cannot guarantee that context loss never occurs.

Repeated changes may leave geometries, materials, textures, render targets, workers, timers, event listeners or cached scene structures alive. State subscriptions can also multiply, and generated geometry can accumulate. Script repeat cycles and compare heap, resource proxies, frame time and response after each interval. In runtimes such as Three.js, removing an object from the scene does not by itself dispose every WebGL resource; lifecycle ownership must be explicit.

Laboratory tests use controlled devices, networks, cache states and scripted products to make diagnosis and regression comparison repeatable. Field or real-user monitoring describes actual devices, routes, releases and interactions, but contains environmental variation and requires careful privacy design. Use both: field segments identify affected audiences and changes, while laboratory traces reproduce the specific stage. Annotate releases and asset revisions so results remain explainable.

Measure the complete host page and the embedded application. Record host content, consent, analytics, fonts, chat and other third-party work, plus iframe or component startup, cross-boundary messaging, model delivery and pricing. Interactions inside an iframe can contribute to page-level responsiveness even when attribution tools show separate contexts. Define shared ownership for viewer space, loading UI, focus, errors, events and release identification.

Configurix treats performance as a product-specific acceptance system. The implemented catalogue is measured across useful HTML, controls, rules, pricing, runtime assets, first useful product view, interaction response, frame stability and long-session behavior on agreed devices and scenes. Asset optimization, progressive delivery, runtime rendering and monitoring are connected to the same product and release revisions. Exact targets, supported devices, integrations and evidence are scoped and verified for the working system rather than assumed from a generic demo.

Continue the technical evaluation

Connect performance to assets, UX, accessibility and QA.

Performance evidence is strongest when it uses the same product revisions, user journeys, accessible controls and release scenarios as the rest of the implementation.

3D asset pipeline

Prepare governed geometry, materials, textures, variants and runtime delivery assets.

Read guide

Configurator UX guide

Design product choices, feedback, recovery and conversion around real buyer tasks.

Read guide

Accessibility guide

Make controls, product state, validation and completion operable beyond the canvas.

Read guide

Testing and QA guide

Verify rules, price, visuals, integrations, devices, security and release recovery.

Read guide

Define performance against your real catalogue.

Bring a representative product, the largest valid configuration, target devices and delivery channel. Configurix can map the runtime stages, budgets, tests and evidence required for a working 3D product configurator.

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