Cross Brand UX Analysis (Based on CrazyEgg analysis)

MOCAP + Cleartec/Beckett

Overview

Analysis of 13 pages across MOCAP and Cleartec/Beckett reveals a common set of B2B user behaviors and expectations that transcend brand identity, alongside brand-specific patterns that reflect different product complexities and user journeys. These findings have profound implications for platform consolidation strategy.

Key Synthesis Points

B2B packaging buyers, regardless of brand usually exhibit identical frustration patterns when interfaces fail to support their core workflow: rapid specification lookup, variant comparison, and confident purchase decisions.

Critical Insight: The most severe usability failures are not brand-specific design choices, but systemic mismatches between user mental models and interface affordances:

Users expect data tables to behave like spreadsheets (sortable, filterable) but encounter static displays
Users expect product images to be zoomable galleries but encounter non-interactive visuals
Users expect instant feedback on all selections but encounter silent interfaces
Users expect technical specifications to be accessible tools but encounter buried, passive content

Strategic Implication: A unified platform can address 70-80% of identified friction points through shared component libraries and interaction patterns, while accommodating brand-specific needs (MOCAP’s variant complexity vs. Cleartec/Beckett’s configurator depth) through parametric customisation rather than parallel development.

1. Universal Behavioural Patterns

Across all 13 pages analysed, 5 behavioural patterns emerge with remarkable consistency. Transcending brand, product type, and page function. These patterns represent fundamental user expectations in the B2B technical product space.

1.1 Tables as a Tool Mental Model

Pattern: Users interact with specification tables as if they were interactive data tools (spreadsheets, databases), not static displays.

Brand	Evidence	Conclusion
MOCAP	RN: 54.3% of clicks on product table, engagement concentrated in first 8–20 rows. · SQ: Filter toggle received 18.6% of all clicks, including 6 rage clicks. · RVC: 46.7% of clicks on table, with sharp decline after first 20 rows.	Users click column headers expecting sorting and variant labels expecting filtering. When the table doesn’t respond, they abandon the interaction.
Cleartec / Beckett	SBT Series: 41.3% of clicks on table, 38 clicks on “Reference #” header, 11.6% dead clicks. · SQT Series: 48.5% of clicks on table, 57 clicks on “Reference #” cells, 11.9% dead clicks. · Both: 4.3–4.4% rage clicks on sorting controls.	Users treat dimension columns (Nominal Size, Fit Length) as sortable fields. They click filter icons expecting refinement and retry rapidly when nothing happens.

Interpretation: This is not a preference, it’s a cognitive expectation formed by decades of Excel, Google Sheets, and database interfaces. Engineers and procurement specialists live in spreadsheet environments. When they see tabular product data, their mental model maps it to tools they use daily. Static tables violate this expectation so fundamentally that 11-12% of all table interactions result in dead clicks and 4% in rage behaviour.

Cross-Brand Insight: The pattern is identical across brands despite different product complexities:

MOCAP’s tables focus on dimensional specifications (diameter, wall thickness, length)
Cleartec/Beckett’s tables emphasize fit relationships (To Fit Part Width, Length Max, Nominal Size)
The data structure differs, but the interaction expectation is universal

Strategic Conclusion: Interactive table functionality is not a “feature request” — it’s a baseline expectation. The platform must treat sortable columns, size-range filters, and progressive disclosure as core table components, not page-specific enhancements.

1.2 Visual Recognition Over Text Scanning

Pattern: Users rely on product imagery as primary navigation mechanism, treating images as clickable items to detail pages, not decorative elements.

Brand	Evidence	Conclusion
MOCAP	Homepage (Desktop): 32.9% of clicks on product category images (Caps: 13, Plugs: 12). · RN: 76+ clicks on non-clickable thumbnails or titles. · RVC: 21.2% of clicks on images, 61+ clicks on main image (mostly dead), 8 rage clicks.	Users navigate visually through the product grid, clicking images expecting to zoom or reach product detail pages. Text labels are secondary — used mainly to confirm the visual choice.
Cleartec / Beckett	Homepage: 48.2% of clicks on images (Cleartec Items: 92, Beckett Items: 81). · Beckett Products: 44.6% of clicks on images vs. 15% on links. · Cleartec Products: 52.3% of clicks on images (Thin Wall: 21 clicks). · SBT Product: 41.8% of clicks on images (180 thumbnail clicks), 22 rage clicks.	Visual-first navigation dominates. Users identify product families by shape or appearance before reading categories, treating images as the most reliable and intuitive path to detail pages.

Interpretation: In technical B2B contexts, visual pattern recognition is faster and more reliable than text parsing. Users mentally categorize products by:

Shape/form factor (round vs. square tubes, caps vs. plugs, flat vs. angled)
Application context (what they protect, where they fit)
Material/finish (clear vs. colored, rigid vs. flexible)

Text categories like “Protective Closures” or “Telescopic Packaging” require translation from business taxonomy to user need. Images provide immediate pattern matching — users recognize the product family before reading its name.

Cross-Brand Insight: This pattern is stronger in Cleartec/Beckett (44-52% image clicks) than MOCAP (22-33% image clicks), likely because:

Cleartec/Beckett homepage uses larger, more prominent brand imagery
MOCAP’s category structure is more established (users may have learned text navigation over time)
But even on MOCAP, when images are present (RN, RVC product pages), they dominate interaction

Strategic Conclusion: Privilege visual navigation:

Product category tiles should be image-first, with large, high-quality photos
Every product image should be clickable (entire card/tile as hit target)
Hover states should provide instant feedback (scale, highlight, cursor change)
Text labels should support but not replace visual recognition

1.3 Interaction Feedback Gap

Pattern: Users repeatedly click elements (rage clicks, retry behaviour) when interfaces fail to provide confirmation that their actions registered.

Brand	Evidence	Conclusion
MOCAP	RVC: Imperial/Metric toggle received 67 clicks with a high error rate and no visible feedback. · SQ: Filter toggle clicked 92 times (18.6% of all interactions) but produced little to no result. · Across all pages: CTAs underperform despite clear intent — sample/cart icons are small, unlabelled, and provide no confirmation.	Users interact with dropdowns, toggles, filters, and buttons but receive no visual or functional feedback. This uncertainty causes repeated clicks, hesitation, and eventual abandonment.
Cleartec / Beckett	Request Samples: Submit button clicked multiple times per user; opt-in section generated 19 rage clicks. · Product SQT: Configurator dropdowns show 10–20 second delay before first selection. · Collections: Add/Sample icons clicked 25–42 times but are small, unlabeled, and unresponsive.	Users complete forms and click Submit without any loading or success state. Dropdown selections show no acknowledgment, and “Add to Cart” actions lack confirmation cues, leading to confusion, mistrust, and drop-off.

Interpretation: In B2B technical buying, precision and verification matter. Users are specifying parts that must fit exactly, ordering samples for testing, or configuring products with multiple dependencies. Unlike consumer e-commerce where impulse overrides caution, B2B users need confidence at every step:

“Did my filter apply?” (show filter chips/tags)
“Is this the right configuration?” (show selection summary)
“Did the sample request submit?” (show confirmation message)
“What’s in my cart?” (show item count, immediate feedback)

The absence of feedback creates decision paralysis — users hesitate, retry, or abandon rather than risk ordering the wrong item.

Cross-Brand Insight: Feedback gaps manifest differently:

MOCAP: Unit toggles, filter states, variant selection (users can’t tell what’s active)
Cleartec/Beckett: Form submission, configurator progression, Add to Cart success (users can’t tell if action completed)

Strategic Conclusion: Implement feedback-first interaction design:

Loading states for all asynchronous actions (search, filter, submit)
Success confirmations for all transactions (toast notifications, inline messages, checkmarks)
Active state indicators for all selections (highlighted toggles, selected rows, filled dropdowns)
Error prevention through disabled states (“Select size before proceeding”) and inline validation

1.4 The Depth-of-Scroll Ceiling: Task Focus Over Content Consumption

Pattern: Users engage intensely with above-the-fold interactive elements (tables, configurators, category grids) but abandon before reaching supporting content (product information, technical specs, related products).

Brand	Evidence (Scroll Depth)	Conclusion
MOCAP	Homepage: Average fold at 32–40%; fewer than 25% of users view content below the product grid. · RN: 40–45% average scroll depth; only 20% reach technical notes. · SQ: 35–40% average; less than 25% reach product information. · RVC: 45% average; only 18% reach informational text, and under 10% see related products.	Between 75–90% of users never reach secondary or supporting content placed below the main interaction zones. Deeper sections such as technical notes, related products, and informational copy are effectively invisible.
Cleartec / Beckett	Homepage: 40–45% average fold; steep drop-off immediately below the hero section. · Brand pages: 40–45% average; lower text sections (Beckett/Cleartec Items) receive almost no engagement. · Product pages: 35–45% average; major decline beyond configurator or Add-to-Cart area. · Collections: 35–40% average; fewer than 15–20% reach Tolerance/Information sections.	Around 80–85% of users do not scroll beyond primary interaction areas such as category grids, configurators, or product tables, leaving most informational or conversion-supporting content unseen.

Interpretation: B2B users arrive with specific intent and task focus:

Find the product family (category page)
Identify the correct specification (size chart/table)
Configure or add to cart (product page)
Request sample or checkout (conversion)

They are not browsing for entertainment or education — they’re solving a procurement problem. Once they complete (or abandon) their primary task, they leave. Additional content like:

Brand storytelling (“Cleartec is the clear choice…”)
Manufacturing processes (“Extruded from virgin resins…”)
Related product recommendations
Technical tolerance tables
Application guides

…is valuable to a small minority (engineers doing deep research, first-time buyers learning about materials) but invisible to the task-focused majority.

Cross-Brand Insight: Scroll depth is remarkably consistent (35-45% avg fold) across both brands, all page types, and device contexts (where measured). This suggests a universal threshold: users will scroll ~1.5 viewport heights to accomplish their task, but not beyond unless compelled.

Strategic Conclusion: Progressive disclosure and content placement strategy:

Critical information (specs, fit guidance, variant selection) must be above the fold or within the primary interaction area (table tooltips, configurator inline help, expandable rows)
Supporting content should be on-demand (accordions, modals, “Learn More” buttons, downloadable PDFs)
Related products should be integrated into the transaction flow (post-Add-to-Cart: “Users also ordered…”, in-cart recommendations) not relegated to page bottom
Trust signals (certifications, Made in USA, sustainability) should be near decision points (above configurator, beside Add to Cart) not in footer

1.5 Non-Interactive Elements That Look Clickable

Pattern: Users repeatedly click elements that appear interactive (styled like buttons, links, or controls) but don’t respond, generating frustration, rage clicks, and erosion of trust.

Brand	Evidence	Conclusion
MOCAP	Homepage: 114 dead clicks (1.3% of total) on “Products by Category” header, phone number, and email. · Mobile: 41 dead clicks on “Select a CAP/PLUG” text and language selector (5 rage clicks). · RN: 76+ clicks on product names and thumbnails expecting detail pages. · RVC: 67 clicks on Imperial/Metric toggle with high error rate.	Users assume that headers expand, contact info triggers calls or emails, and product visuals link to detail pages. They also expect toggles to display a visible state change — none of which occur. This mismatch erodes trust and creates confusion during product exploration.
Cleartec / Beckett	Homepage: 61 dead clicks (5.8% of total) on contact info and location/language selector (17 rage clicks). · Beckett Products: 17 dead clicks (8.8%) on Contact, RTL, and phone number elements. · Cleartec Products: 9 dead clicks (10.2%) on product blocks and header divs. · SBT Product: 64 dead clicks (7.0%) on “Configure your Item” header and section divs (22 rage clicks).	Users expect contact info to be interactive, product tiles to act as single clickable units, and section headers to lead to navigation or expanded content. The absence of feedback or response causes frustration, repeated clicks, and a perception that the interface is broken or outdated.

Interpretation: False affordances are more damaging than missing features. When a feature doesn’t exist, users adapt or find alternatives. When a feature appears to exist but doesn’t work, users experience:

Confusion — “Is it broken? Did I click wrong? Is my browser blocking it?”
Frustration — Rage clicks reveal emotional response to repeated failure
Distrust — “If this doesn’t work, what else is broken?” → abandonment

False affordances occur when visual design signals interactivity without implementing functionality:

Text styled like links (blue, underlined) but not wrapped in <a> tags
Elements with hover cursors but no click handlers
Buttons/icons that look like controls but are decorative
Headers that look like accordions but don’t expand

Cross-Brand Insight: False affordances cluster in three categories across both brands:

Contact information (phone, email): 5-9% of page clicks are dead attempts to interact
Product imagery/names: 15-25% of image clicks are dead (users expect navigation or zoom)
Navigation elements (category headers, section titles): 1-6% of clicks are users trying to expand or navigate

Strategic Conclusion: Enforce affordance consistency rules:

Principle 1: If it looks clickable, it must be clickable

All contact info: tel: and mailto: links
All product images: clickable tiles leading to detail pages or zoom modals
All category headers: links, accordions, or styled as non-interactive

Principle 2: If it’s not clickable, it must not look clickable

Remove underlines, blue text, pointer cursors from static text
Use disabled states (greyed out, cursor: not-allowed) for inactive controls
Differentiate decorative elements visually

Principle 3: Test with hover states and error states

Interactive elements must show hover feedback (color change, scale, underline)
Failed interactions must provide error messages (“Please select size first”)

Comparative Analysis Tables

Area	MOCAP	Cleartec / Beckett	Conclusions
Primary Navigation Method	Category-based structure (Caps, Plugs, Grips) using visual product cards.	Dual-brand visual gateway (Cleartec Items / Beckett Items) leading to category grids.	Both depend on visual-first navigation, but MOCAP organizes by category type while Cleartec/Beckett emphasize brand-level entry points.
Image vs. Text Balance	22–33% of clicks on images across homepage and product pages.	44–52% of clicks on images across homepage and brand pages.	Cleartec/Beckett users are more visually driven, while MOCAP users engage slightly more with text-based navigation.
Sidebar Navigation Usage	9–13% of clicks on the left sidebar.	Minimal sidebar interaction (5–8% when present).	In both cases, sidebars underperform; users prefer direct navigation via imagery or on-page elements.
Search as Fallback	6–7% of total interactions (≈65 clicks on homepage).	5–7% of total interactions (≈6–10 clicks on brand pages).	Search functions as a consistent fallback (~6% usage) when visual navigation fails to meet expectations.
Mobile Hamburger Dependency	31% of mobile clicks on the hamburger menu alone.	Not measured (Cleartec/Beckett data desktop only).	MOCAP’s mobile UX shows over-reliance on hidden navigation, posing accessibility and discoverability risks.

Insight: Visual navigation is universal but C+B leverages it more effectively through prominent brand imagery (92 and 81 clicks on Cleartec/Beckett hero images). MOCAP has opportunity to strengthen visual hierarchy on homepage.

Navigation should:

Default to image-first category tiles (proven successful on C/B)
Provide persistent category bar on mobile (avoid MOCAP’s 31% hamburger dependency)
Enhance search with auto-complete (currently underutilized at 5-7% but could serve power users)
De-emphasize or eliminate left sidebar navigation (consistently underperforms)

Product Discovery & Selection

Area	MOCAP	Cleartec / Beckett	Conclusions
Primary Interaction Surface	Product tables attract 46–54% of clicks on collection pages.	Configurator dropdowns capture 27–62% of clicks on product pages.	Both aim to help users narrow from a product family to a specific SKU, but MOCAP relies on tables while Cleartec/Beckett depend on configurators.
Variant / Size Selection Method	Long, scrollable tables with Imperial/Metric toggles.	Multi-step dropdowns with dependent parameters.	Tables support fast scanning and comparison, while configurators provide structured, guided selection. Each suits different user workflows.
User Mental Model	”Show me all sizes — I’ll find mine” (spreadsheet mindset).	”Guide me to the right fit” (wizard-style mindset).	MOCAP users are self-directed and analytical; Cleartec/Beckett users expect assisted navigation and validation before choosing.
Frustration Hotspot	Static tables that appear sortable or filterable (11–12% dead clicks).	Unclear configurator entry points and ambiguous dropdown labels (4–7% dead clicks, 10–20s hesitation).	Both violate user expectations of interactivity — MOCAP through static data surfaces, Cleartec/Beckett through unclear progression.
Image Role in Selection	Users click images expecting zoom or navigation (17–25% of image clicks are dead).	Users click images expecting zoom or variant previews (18–42% of image clicks, frequent rage on main image).	Across both, product images are treated as functional UI elements, not decoration — zoom and visual detail are critical to confidence and conversion.

Insight: MOCAP and C+B represent two valid approaches to technical product selection:

MOCAP’s table approach suits products with many dimensional variations (50+ tube plug sizes)
C/B’s configurator approach suits products with multi-dimensional parameters (material × color × fit dimension × length)

Neither is wrong, but both fail to meet core interaction expectations (tables should be sortable, configurators should provide guidance).

Product discovery & selection should support both patterns as configurable components:

Table component with: sortable columns, size-range filters, sticky headers, quick-add checkboxes
Configurator component with: visual stepper, inline help, dependency management, configuration summary
Selection logic in product data: flag products as “table-suitable” (many sizes, simple variants) or “configurator-suitable” (complex parameters, dependencies)

Conversion Actions (CTAs)

Area	MOCAP	Cleartec / Beckett	Conclusions
Add to Cart Visibility	Small, unlabeled icons within tables; 54–112 clicks per page.	Prominent Add to Cart button on product pages; 82 clicks (SBT & SQT).	Cleartec/Beckett’s button-based approach outperforms MOCAP’s hidden icons by providing clearer intent and affordance.
Request Sample Prominence	Present in top navigation but underperforms (10–43 clicks per page).	Dedicated form page (152 visits) but friction-heavy, averaging 4.39 clicks per visit with 19 rage clicks.	Both underperform: MOCAP suffers from visibility issues, while Cleartec/Beckett struggle with interaction friction and poor usability.
Confirmation Feedback	No visible confirmation — users can’t tell if cart updated after clicking.	No confirmation either — Submit and Add to Cart repeatedly clicked.	A universal UX failure: both lack success states or progress feedback, undermining user confidence.
CTA Performance vs. Engagement	High table engagement (46–54% of clicks) but low conversion actions (6–9% on CTAs).	High configurator engagement (27–62%) but only moderate conversion (9–17% on Add to Cart).	Both show a clear intent-to-action gap: users interact heavily but hesitate or fail to complete conversions.
Sample / Cart Icon Design	Very small, unlabeled icons embedded in table rows.	Larger button treatment but still no post-click visual response.	The icon-based CTA model consistently underperforms across brands; larger buttons help visibility but not without confirmation feedback.

Insight: CTA performance is suboptimal across both brands despite different approaches:

MOCAP: CTAs exist but are invisible (small icons lost in dense tables)
C/B: CTAs visible but lack confidence (no confirmation users did it right)

Combined lesson: CTAs need visibility + feedback + reassurance:

Visibility: labeled buttons, not icons
Feedback: immediate confirmation (”✓ Added to cart”)
Reassurance: microcopy (“Free samples,” “No credit card needed,” “Edit anytime”)

CTA system should enforce:

Labeled button standard (replace all icon-only CTAs)
Consistent feedback pattern (toast notifications or inline messages)
Context-aware microcopy (samples: “Free, ships 1-2 days”; cart: “Secure checkout”)
Multi-select support for tables (checkboxes → bulk “Add selected to cart”)

Mobile vs. Desktop Behavior (MOCAP only)

Area	Desktop	Mobile	Conclusions
Primary Navigation	Top navigation and category images dominate (41.6% + 32.9% = 74.5% combined).	Hamburger menu alone receives 31% of all clicks.	Mobile experience is over-dependent on a hidden navigation system, increasing friction for quick access.
Contact Intent	Lower priority — only 7.1% of clicks fall in footer or misc contact areas.	Second-highest interaction type — 22% of clicks (phone: 274, email: 152).	Mobile users show stronger intent to contact directly, prioritizing immediate access to phone and email links.
Scroll Depth	Average fold at 32–40%.	Around 60% average scroll depth (though smaller viewport makes this relatively similar).	Mobile users scroll slightly more but engagement still drops sharply beyond first screens — key actions must remain high on the page.
False Affordances	Users click non-interactive “Products by Category” headers, product images, and contact text.	Users tap “Select a CAP/PLUG” text, non-clickable product thumbnails, and language selector (5 rage clicks).	Same false affordance problem across devices, but mobile adds touch-target precision issues, worsening frustration.

Insight: Mobile behaviour shows different task priorities (quick contact, immediate access) and higher sensitivity to navigation friction (hamburger dependency, touch target issues).

Mobile-specific optimisations needed:

Expose top 4-6 categories in persistent bar (don’t hide behind hamburger)
Sticky floating contact button (phone/email always accessible)
Larger touch targets for all interactive elements (minimum 44×44px)
Simplified configurators (single-column layout, larger dropdowns, clearer stepper)

Content Strategy & Information Architecture

Area	MOCAP	Cleartec / Beckett	Conclusions
Supporting Content Visibility	75–90% of users never reach technical notes, product info, or related products positioned below the fold.	80–85% of users don’t scroll beyond configurator or table; “Additional Information” sections have less than 20% visibility.	Universal issue: supporting content is effectively invisible across all sites, meaning critical details and secondary CTAs go unseen.
Specs / Tolerances Location	Placed below product tables with less than 20% view rate.	Located beneath configurators with less than 15–20% visibility.	Both brands bury vital technical data, forcing engineers to hunt for essential specifications.
Related Products Positioning	Located at page bottom, seen by less than 10% of users.	Positioned at bottom or sometimes absent entirely.	Shared missed opportunity for cross-sell or exploration, as related items appear too late in the user journey.
Trust Signals (Certifications, “Made in USA”)	Displayed below the fold with minimal visibility.	Not prominently featured near CTAs or key decision areas.	Both fail to reinforce credibility at the moment of conversion, weakening user confidence.
Educational Content (Fit Guides, How-to-Measure)	Present but buried below fold; rarely seen.	Present but also placed too low; minimal engagement.	Both have valuable educational resources misplaced in low-visibility zones — good content, wrong location.

Insight: Both brands follow traditional web content model (hero → primary content → supporting details → footer) but users follow task-focused model (find product → select size → convert → leave). This mismatch means 75-85% of users never see content that might help them make better decisions.

Content strategy must practice progressive disclosure and point-of-need information:

Specs in table: Use tooltips, expandable rows, or modal dialogs (ℹ icon → dimension details)
Fit guides contextual: “Need help measuring?” link beside configurator dropdowns
Trust signals at decision points: Certifications, quality badges, “Made in USA” near Add to Cart button
Related products after action: “Users who ordered this also ordered…” appears after Add to Cart (not page bottom)
Downloadable references: “Download full size chart PDF” as alternative to long scrolling tables

The B2B Technical Buyer’s Mental Model

This analysis reveals a consistent mental model that B2B packaging buyers bring to all interactions:

Users arrive treating these sites like:

Engineering reference tools (not marketing websites)

Expect data-dense, scannable interfaces
Prioritize specs over storytelling
Want spreadsheet-like manipulation (sort, filter, compare)

E-commerce platforms (not catalogs)

Expect immediate add-to-cart functionality
Want confirmation feedback on all actions
Need reassurance about samples, shipping, returns

Technical databases (not brochures)

Expect search to work like product search (SKU, dimension, material)
Want to save/export/share product selections
Need cross-session persistence (saved configurations, recent views)

When sites don’t support this model:

Static tables feel broken (violate spreadsheet expectation)
Non-interactive images feel incomplete (violate e-commerce gallery expectation)
Long scrolling content feels inefficient (violate database quick-lookup expectation)
Silent interfaces feel unreliable (violate confirmation expectation)

User Expectations Shape Platform Requirements

Combined findings reveal five non-negotiable user expectations that must shape platform architecture:

1. Data Must Be Manipulable

Users expect to sort, filter, search, and export product data
Static displays violate fundamental mental models
Platform requirement: All product data must be structured for programmatic manipulation (sortable, filterable, searchable)

2. Actions Must Confirm

Every user action must receive immediate, visible feedback
Silent interfaces erode trust and stall conversion
Platform requirement: Feedback layer must be baked into component library (not per-page implementation)

3. Images Must Function

Product images are not decorative — they’re navigation and evaluation tools
Non-interactive images generate rage clicks
Platform requirement: All product images must support zoom, gallery navigation, variant switching as baseline

4. Complexity Must Be Guided

Users can’t infer technical parameters without help
Configurators need explicit guidance, tooltips, examples
Platform requirement: Inline help, progressive disclosure, and contextual assistance must be first-class features

5. Friction Must Be Minimal

B2B users are task-focused and time-constrained
Every extra click, every unclear state, every missing confirmation increases abandonment risk
Platform requirement: Optimize for efficiency — fewest clicks, clearest paths, instant feedback

2. Brand-Specific Behavioral Signatures

While universal patterns dominate, each brand also shows unique behavioural signs, reflecting different product complexities, user journeys, and interface challenges.

2.1 MOCAP: Variant Selection Challenge

Unique Behaviour: Users struggle to differentiate between variants (metric vs. standard, flat vs. angled, round vs. square) within the same product family, leading to high engagement with labels that look like filters but aren’t.

Evidence:

RN (Round Tubes): Repeated clicks on “Metric or Standard” and “Flat Top / Angled Top” text — users expect these to filter the table or navigate to separate pages
SQ (Square Tubes): Filter toggle receives 18.6% of all clicks (92 clicks) but is broken/unintuitive, causing 6 rage clicks
RVC (Round Vinyl Caps): Users repeatedly click “Imperial / Metric” toggle (67 clicks, 9.4% of total) but unclear whether toggle worked or what changed

Interpretation: MOCAP’s product range is characterised by incremental dimensional variations within the same base product:

Round tube plugs in 50+ sizes (metric and standard)
Angled vs. flat top variants of the same tube plug
Different wall thicknesses for same outer diameter

Users arrive knowing the general product type (round tube plug) but need to narrow to specific variant (flat top, metric, 1.5” diameter). Current interface presents everything in one long table, requiring users to manually scan and interpret rather than filter and select.

What MOCAP Does Well:

Comprehensive size charts provide all dimensional data in one place
SKU-level detail supports engineering precision
Consistent table structure across product families

What MOCAP Struggles With:

No functional filtering or variant navigation
Visual repetition (all variants look similar in thumbnail)
Metric/Standard toggle doesn’t provide obvious confirmation

Unique needs:

MOCAP requires hierarchical variant navigation: Product Family → Variant Type → Size Range → Individual SKU
Filtering must support both discrete categories (Flat/Angled) and continuous dimensions (diameter, length)
State management must handle multi-dimensional selection (material + variant + size + metric/standard)

2.2 Cleartec/Beckett: The Configurator Complexity

Unique behaviour: Users spend significant time (10-20 seconds) trying to understand multi-step product configurators, often clicking non-interactive headers and divs before discovering dropdowns, then hesitating before making selections.

Evidence:

Product SBT: Users repeatedly click “Configure your Item” header and section divs (22 rage clicks, 64 dead clicks total) before engaging with dropdowns
Product SQT: 61.8% of clicks on configurator dropdowns, but 10-20 second delay before first selection; users unsure what each parameter controls
Dropdown engagement sequence: Material/Color (196 clicks) → Part Width (184) → Part Length (157) → Add to Cart (82) — clear funnel drop-off

Interpretation: Cleartec/Beckett products require multi-dimensional configuration:

Material selection (PVC, PET, PP)
Color/clarity (clear, colored, semi-transparent)
Dimensional fit (tube must fit over customer’s part)
Length/height options
Optional accessories (hanging caps, closure styles)

This is more complex than MOCAP’s variant selection because:

Dependency chains exist: selecting Material may constrain available Colors; selecting Part Width may constrain available Lengths
Fit calculations required: user must know their part dimensions to choose tube size (not just browsing sizes)
Multi-step progression needed: can’t add to cart until all required parameters selected

Current interface presents all dropdowns simultaneously without visual hierarchy or guidance, creating cognitive overload.

What Cleartec/Beckett Does Well:

Clear Add to Cart CTA (82 clicks on both SBT and SQT — consistent conversion intent)
Product imagery prominent (though not interactive)
Size chart links available for reference

What Cleartec/Beckett Struggles With:

Configurator entry point unclear (users click headers thinking that’s how to start)
No visual stepper or progress indicator (Steps 1-3 look identical)
Dropdown labels too technical without explanatory help
No confirmation/summary of selected configuration before Add to Cart

Unique needs:

Cleartec/Beckett requires stepped configurator pattern: clear Step 1 → Step 2 → Step 3 progression
Dropdowns need contextual help (tooltips, inline examples, “Why does this matter?” links)
Must support dependency management (disable invalid combinations, show only valid next options)
Needs configuration summary (sidebar or top bar showing “You’re configuring: PVC Clear Tube, 2” × 6”, Flat Top”)

User Experience Risks

Risk 1: Over-Standardization

Description: Forcing MOCAP and C/B into identical patterns when users actually need different experiences

Mitigation:

Validate with user testing: do MOCAP users and C+B users actually have same needs?
Build flexibility into components to handle brand-specific workflows
Monitor metrics post-launch: if C/B configurator approach doesn’t work for MOCAP, adjust

Risk 2: Migration Shock

Description: Changing too much too fast confuses existing users

Mitigation:

Phased rollout: start with new pages or low-traffic pages
Provide “old vs. new” comparison links during transition
Monitor support tickets and user feedback during rollout
Keep fallback to old experience if new version causes issues

Final Reflection

The data from 13 pages across two brands tells a clear story: B2B packaging buyers have consistent expectations that current interfaces fail to meet. These failures are not unique to MOCAP or Cleartec/Beckett — they are systemic to the industry and reflect a mismatch between how these sites were built (content-first, marketing-focused) and how users actually behave (task-first, data-focused).

The opportunity is not to build 2 or 4 better sites. The opportunity is to build one excellent platform that both brands leverage, eliminating waste, accelerating innovation, and delivering the user experience that B2B buyers have been signalling through their clicks, scrolls, and rage interactions.