Fast Part ID, Frictionless Reorders, and Strategic Upsells Drove 28% AOV Lift and 53% Conversion Increase
Fast Part ID, Frictionless Reorders, and Strategic Upsells Drove 28% AOV Lift and 53% Conversion Increase
A spare parts and services supplier serving B2B buyers faced a common but costly problem: buyers knew what vehicle they had but struggled to find the right part quickly. Compounding this, there was no structured upsell at the service stage and no trust scaffolding to support large repeat orders. I governed the digital experience end-to-end, from search architecture to number plate tooling, turning a transactional catalogue into a revenue-optimised buying system.
A spare parts and services supplier serving B2B buyers faced a common but costly problem: buyers knew what vehicle they had but struggled to find the right part quickly. Compounding this, there was no structured upsell at the service stage and no trust scaffolding to support large repeat orders. I governed the digital experience end-to-end, from search architecture to number plate tooling, turning a transactional catalogue into a revenue-optimised buying system.
Automotive
B2B-B2C
Spare Parts & Services
Challenges
B2B buyers couldn't identify the correct part by vehicle model, high search drop-off
Product pages lacked trust signals needed for high-value repeat orders
No upsell structure around related services at point of purchase
Number plate customisation had low conversion despite strong demand
No experimentation loop to learn and iterate on buyer behaviour
B2B buyers in spare parts operate differently to retail shoppers. They arrive with a car make, model, and year - and they expect the catalogue to do the heavy lifting. When search returned ambiguous results or required the buyer to know a part number upfront, they left. The friction wasn't intent, it was identification.
On the product page, the purchasing environment felt thin. Large orders require confidence. Buyers needed to see compatibility confirmation, stock assurance, and supplier credibility, none of which were being surfaced at the right moments.
The service upsell gap was a revenue leak in plain sight. When a buyer ordered brake pads, there was no contextual prompt around brake fluid, fitting kits, or a booked service slot, the kind of add-on logic that drives AOV without feeling pushy.
And in the number plate customisation flow, conversion was low not because demand was absent, but because the design experience was generic and uninspiring, a missed opportunity in a high-margin product category.
B2B buyers in spare parts operate differently to retail shoppers. They arrive with a car make, model, and year - and they expect the catalogue to do the heavy lifting. When search returned ambiguous results or required the buyer to know a part number upfront, they left. The friction wasn't intent, it was identification.
On the product page, the purchasing environment felt thin. Large orders require confidence. Buyers needed to see compatibility confirmation, stock assurance, and supplier credibility, none of which were being surfaced at the right moments.
The service upsell gap was a revenue leak in plain sight. When a buyer ordered brake pads, there was no contextual prompt around brake fluid, fitting kits, or a booked service slot, the kind of add-on logic that drives AOV without feeling pushy.
And in the number plate customisation flow, conversion was low not because demand was absent, but because the design experience was generic and uninspiring, a missed opportunity in a high-margin product category.
Solutions
Built car model search - make, model and year filtering directly to compatible parts
Introduced contextual trust signals: fitment guarantee, reorder badge, stock urgency
Launched strategic service upsells at the product and cart stage
Designed a custom number plate builder, interactive, high-converting
Established a lean CRO pipeline for continuous experimentation
Search by Vehicle Model
The first intervention was structural. We rebuilt the search and filtering layer to allow buyers to enter make, model, and year and receive only compatible parts. This didn't just reduce friction, it eliminated the most common reason for drop-off. A buyer looking for front discs for a 2019 Ford Transit now arrived directly at a filtered, relevant catalogue. We worked closely with the development team to ensure the part compatibility logic was accurate and edge cases were handled cleanly.
Trust Signals for B2B Reorder Confidence
B2B buyers reorder repeatedly, but only from suppliers they trust. We layered in fitment confirmation badges, reorder history prompts, and real-time stock indicators at the critical decision points, not buried in product specs, but visible at the moment the buyer is evaluating. For returning accounts, we surfaced a 'you've ordered this before' prompt to reduce cognitive load and speed the reorder cycle.
Upsell Timing for Services — 28% Increase in AOV
Strategic messaging was introduced at the product and cart stage, tied to service timing logic. When a buyer added a wear part, filters, belts, brake components. a contextual prompt appeared: not a generic 'you might also like,' but a service-aware recommendation. For example: 'Replacing your air filter? Most technicians also swap the cabin filter at this interval - add it here.' These prompts were timed to appear after the buyer had committed to the core product, reducing resistance. The result was a 28% increase in AOV and measurable improvement in lifetime value through larger basket sizes per visit.
Custom Number Plate Design — 53% Conversion Increase
The number plate customisation flow was redesigned from the ground up. The original experience was form-based and static. We replaced it with an interactive design tool that let buyers preview their plate in real time, select materials and styles, and move through the configuration with visual confidence. The design felt premium, appropriate for a product with strong margin and emotional investment. The conversion rate on the number plate category increased by 53%.
CRO Pipeline
Underpinning all of this was a structured testing cadence. Rather than one-off launches, we established a sprint-based experimentation loop: hypothesise, build, measure, iterate. Ideas stopped being filed in a backlog and started being tested against real buyer behaviour. The team moved from infrequent big launches to frequent, learning-driven increments.
Search by Vehicle Model
The first intervention was structural. We rebuilt the search and filtering layer to allow buyers to enter make, model, and year and receive only compatible parts. This didn't just reduce friction, it eliminated the most common reason for drop-off. A buyer looking for front discs for a 2019 Ford Transit now arrived directly at a filtered, relevant catalogue. We worked closely with the development team to ensure the part compatibility logic was accurate and edge cases were handled cleanly.
Trust Signals for B2B Reorder Confidence
B2B buyers reorder repeatedly, but only from suppliers they trust. We layered in fitment confirmation badges, reorder history prompts, and real-time stock indicators at the critical decision points, not buried in product specs, but visible at the moment the buyer is evaluating. For returning accounts, we surfaced a 'you've ordered this before' prompt to reduce cognitive load and speed the reorder cycle.
Upsell Timing for Services — 28% Increase in AOV
Strategic messaging was introduced at the product and cart stage, tied to service timing logic. When a buyer added a wear part, filters, belts, brake components. a contextual prompt appeared: not a generic 'you might also like,' but a service-aware recommendation. For example: 'Replacing your air filter? Most technicians also swap the cabin filter at this interval - add it here.' These prompts were timed to appear after the buyer had committed to the core product, reducing resistance. The result was a 28% increase in AOV and measurable improvement in lifetime value through larger basket sizes per visit.
Custom Number Plate Design — 53% Conversion Increase
The number plate customisation flow was redesigned from the ground up. The original experience was form-based and static. We replaced it with an interactive design tool that let buyers preview their plate in real time, select materials and styles, and move through the configuration with visual confidence. The design felt premium, appropriate for a product with strong margin and emotional investment. The conversion rate on the number plate category increased by 53%.
CRO Pipeline
Underpinning all of this was a structured testing cadence. Rather than one-off launches, we established a sprint-based experimentation loop: hypothesise, build, measure, iterate. Ideas stopped being filed in a backlog and started being tested against real buyer behaviour. The team moved from infrequent big launches to frequent, learning-driven increments.
"The car model search alone changed the business. Buyers could finally find what they needed in seconds. The upsell logic felt natural, it matched how our customers actually think about servicing. The number plate builder was a completely different product after the redesign."
— Managing Director
"The car model search alone changed the business. Buyers could finally find what they needed in seconds. The upsell logic felt natural, it matched how our customers actually think about servicing. The number plate builder was a completely different product after the redesign."
— Managing Director
Results
+28% increase in Average Order Value (AOV) — strategic service upsells introduced at product and cart stage, contextually timed to buyer intent
+53% conversion rate on number plate customisation — interactive design tool replaced a static form, lifting engagement and purchase confidence
Significant reduction in search drop-off — vehicle model search (make, model, year) resolved the primary identification friction for B2B buyers
Stronger reorder rates from returning accounts — trust signals and reorder prompts reduced friction on repeat purchase cycles
2x experimentation velocity - lean CRO pipeline replaced ad-hoc launches with structured sprint-based testing
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