Inriver modernizes Product Information Management at Sunbelt Rentals UK & Ireland

As part of its digital transformation program, Sunbelt Rentals UK & Ireland has worked with Inriver to create a governed product data foundation, connecting product information across its rental portal, ERP, service platforms and website.

at a glance:

• Construction & Industrial equipment rental
• B2B
• Enterprise
• Risley, United Kingdom

100+

Systems consoildated into one governed product data flow

1,000s

Products and items governed in Inriver, complete with images, documentation, and spec sheets

100+

Attributes a single item can carry, now structured in one data model

Summary

Sunbelt Rentals UK & Ireland, the UK’s largest rental company, operated across more than 100 systems, each supporting different parts of the business. As its digital transformation accelerated, Sunbelt Rentals recognized the opportunity to bring product information together within a single governed data foundation. With an elastic data model built to absorb Sunbelt Rentals’ scale and complexity, Inriver’s PIM system governs product information for thousands of items across multiple business units, feeding it out to Sunbelt Rentals’ upcoming new rental, ERP, and service systems, its website, and its marketing campaigns. The result is a team that can spend less time managing data across multiple systems and more time enhancing data quality through consistent governance, while providing a strong foundation for AI-enabled innovation.

Outcomes: 

• Consolidated product data from multiple legacy systems into one governed flow 
• Introduced structured, validated product data at scale
• Enabled a single data model to feed rental, ERP, service and maintenance, website and marketing channels 
• Enhanced the product data model around machinery type and capability, improving data quality for customers and staff 
• Deployed AI-generated product descriptions within a governed structure of validation rules and an expression engine 

The Challenge

The company was running over 100 different systems. Product information was maintained across multiple systems to support different business processes, creating opportunities to improve consistency, governance and reuse as the organization moved toward a more connected digital ecosystem. 

Meanwhile, customer expectations kept climbing. Renters wanted accurate specifications for the right equipment and better documentation. Expectations that would benefit from a modern, centralized product information platform capable of supporting future digital services and AI.

Compounding the challenge, Sunbelt Rentals product catalog doesn’t behave like a typical retail catalog. Equipment can carry hundreds of attributes and heavy documentation requirements, and the same product can be rented differently depending on the business unit. Sunbelt Rentals needed a platform that could be shaped around that reality, rather than forcing the business to fit into a rigid, predefined structure. 

The Solution

Sunbelt Rentals worked with Inriver PIM as one of their first systems in place for its digital transformation. That equencing was deliberate, ensuring a governed product data foundation was established early, allowing new business systems to integrate with trusted product information as they were introduced.  

At the core of the build is an elastic data model.

“We didn’t want to lock ourselves into something too rigid too early,”

Clare O’Brien

Data Quality Manager

With multiple business units, thousands of products, and a huge number of attributes to manage, designing a fixed model upfront wasn’t realistic. The elastic model let Sunbelt Rentals extend the structure as requirements emerged, linking items, attributes, and content in new ways, and letting a single product exist across multiple business units, without breaking the model or the integrations built on top of it.

Sunbelt Rentals data model is now driven first by machinery type and then by capability, improving findability for customers and for Sunbelt Rentals hire desk staff searching the catalog internally.  

Working closely with Inriver, the team refined the data model to better reflect Sunbelt Rentals’ operational requirements, creating a flexible structure that balanced governance with long-term scalability. 

With that foundation in place, Sunbelt Rentals began layering in governed AI. Product descriptions are now generated at scale rather than written manually, with validation rules and an expression engine built into Inriver ensuring the output is accurate and usable rather than left unchecked. The same foundation is now being used to help identify gaps and patterns in the data that would previously have taken a manual review to catch.

The Results 

The clearest achievement, according to Clare O’Brien, wasn’t the system’s implementation itself, it was the shift in how the business works with data. “We’ve strengthened the governance around our product data and created clear ownership, giving teams greater confidence in the information they use every day.” She said. Validation rules and controlled attributes now catch missing data, inconsistent formats, and duplication.

That shift shows up in numbers. Sunbelt Rentals now manages thousands of products and items in Inriver, supported by content including images, documentation, and spec sheets. More importantly, teams across the business now have greater confidence in a single source of governed product information, supporting everything from customer experiences to reporting, bids and tenders. 

Governed AI is already delivering results on top of that foundation. AI-generated product descriptions have improved both efficiency and consistency.

“It’s really important that anything that comes out of that gets referred back to a human to double-check before anybody places an order.” 

Glyn Matthews

Digital Transformation Manager

Looking ahead, Sunbelt Rentals plans to extend this same governed foundation to kitting, linked items, sales products, hundreds of thousands of spare parts, and asset mapping across its rental fleet — alongside plans for AI-assisted classification of new products, improved search and discovery through answer engine optimization, and predictive data quality that extends beyond PIM into downstream channels. “Take smaller bites, and re-evaluate after each one,” Glyn Matthews, Digital Transformation Manager, advised other teams starting a similar journey. 

“Get your foundation set first, and don’t try to over-engineer the solution at the start.” 

Clare O’Brien

Data Quality Manager

Inriver’s platform is built to absorb complexity at scale, coordinating product data across every system and channel it touches, so growth doesn’t multiply rework.