What was actually wrong.
Product data problems are rarely confined to one system. They show up in catalogue structure, enrichment work, ownership and the effort needed to prepare information for each channel.
Ooni needed cleaner product data and a more maintainable catalogue so the Food & beverage business could trade with confidence.
Product information, catalogue structure and supplier feeds were likely sources of operational friction, with editorial and trading teams working around fragmented data.
Product information was spread across teams and systems, making catalogue management harder to control and product content harder to reuse with confidence.
Enrichment work needed a clearer workflow, with ownership defined for the people preparing, checking and maintaining product information.
Attributes, product models and category structure needed common rules so the catalogue could stay consistent as products and channels changed.
What happens if it isn't fixed.
When product information is difficult to maintain, teams compensate with manual work. The result is slower onboarding, inconsistent content and less confidence in the catalogue.
Unclear product, pricing or fulfilment information can create friction before an order is placed.
Most relevant to Food & beverage teams weighing similar platform decisions.
Poor product data makes teams work around the catalogue instead of improving it. Product onboarding slows down, enrichment becomes repeated manual effort and ownership stays unclear.
That creates catalogue drift and inconsistent product presentation. It also weakens confidence in the information each channel receives.
The longer those gaps remain, the harder it becomes to reuse product data across channels without another round of checking, correction and content rework.
Five things, in order.
Delivery is not just a list of features. The order matters, because the wrong sequence can turn technical dependencies into business risk.
- 01Audited the product data shape before changing workflowsMapped the existing product information, catalogue structure and maintenance work so the team could see where inconsistency and repeated effort entered the process.
- 02Defined ownership around product information and enrichmentSet clearer responsibility for creating, enriching, checking and maintaining product information across the teams involved.
- 03Structured attributes, categories and content rulesOrganised product models, attributes and category rules so the catalogue could stay consistent as the range and channel requirements changed.
- 04Connected product data to the systems and channels that needed itDefined how product information moved through ERP, including which system owned each part of the product record. Commerce channels were treated as governed destinations for that data, not as the lead story.
- 05Put governance in place so the data could keep improvingEstablished maintainable rules for enrichment, content consistency and ongoing data quality instead of treating catalogue preparation as a one-off task.
Systems, one operational truth.
Where this could have gone wrong.
Measurable, not adjectival.
The useful proof is the shape of the product data work, the systems and channels involved and, where available, the numbers recorded from the project.
What the client said.
A client quote should support the case study, not carry it. The project story still needs to stay grounded in the work that was delivered.
Our partnership with iWeb has been a transformative journey for our organisation, significantly enhancing our digital presence in ways we hadn't anticipated. The depth of expertise iWeb brings to the table in defining, developing, and expanding our digital footprint has been nothing short of remarkable. From the initial planning stages to the final execution, their meticulous attention to detail and innovative approach have set a new benchmark for what we consider excellence in digital strategy and implementation.”
What moved into support.
Product data work continues after the initial structure is in place. Teams still need to enrich records, maintain quality, support new products and prepare information for changing channel needs.
The product data foundation moved into ongoing maintenance and improvement.
Support kept data ownership, enrichment workflows, catalogue structure and channel readiness visible as the product range changed.
That continuity gave teams a clearer basis for resolving data issues and improving product information without claiming an unverified outcome.
Surfaces from the live project.
Screenshots show how governed product information, content and assets are prepared for the channels and teams that use them.
Projects with a similar shape.
An air services PIM project built around product data, assets and operational catalogue control.
Product data and digital assets made easier to manage across onboard, packing and sales channels.
A buying group PIM project built around product data, catalogue scale and supplier complexity.
Faster product data management across a complex wholesale buying group catalogue.
A wholesale B2B2C foodservice platform built around mobile ordering, pricing and product data.
Trade and consumer ordering supported through faster pricing updates, mobile journeys and stronger product data.