Work/LoveCrafts

PIM & DataRetail & homeCW-082-PD-RH

LoveCrafts: creating a more reliable product data foundation.

A 5-week pim & data for product information and catalogue operations, shaped around product information quality, enrichment workflows, catalogue structure and data movement between systems and channels.

LoveCrafts's operating scale meant product information, catalogue governance, enrichment, data ownership and channel readiness had to work for every team and system using the data.

Week project

Kickoff to go-live

Platforms

Commerce Tools and Akeneo PIM

System integration

Microsoft Dynamics 365 Business Central +1 more

Commerce models

B2C and D2C

Read onWhat was actually wrong, what we did, and what could have gone wrong.

The problem

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.

LoveCrafts needed governed product information that could be modelled once and syndicated to every retailer, marketplace and channel where the Retail & home range is sold.

Product data ownership, attribute structure and channel-specific feed rules were likely sources of operational friction, with brand, editorial and trading teams reconciling the same product record for each retailer.

Shoppers meeting the brand on retailer sites, marketplaces and syndicated channels needed consistent, complete product information so the range is represented accurately wherever it appears.

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.

The risk

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.

When product information drifts across retailer sites, marketplaces and syndicated channels, shoppers stop trusting listings and the brand absorbs the returns, complaints and lost baskets.

Most relevant to Retail & home teams running B2C and D2C operations and 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.

The work

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.

01
Audited the product data shape before changing workflows
Mapped the existing product information, catalogue structure and maintenance work so the team could see where inconsistency and repeated effort entered the process.
02
Defined ownership around product information and enrichment
Set clearer responsibility for creating, enriching, checking and maintaining product information across the teams involved.
03
Structured attributes, categories and content rules
Organised product models, attributes and category rules so the catalogue could stay consistent as the range and channel requirements changed.
04
Connected product data to the systems and channels that needed it
Defined how product information moved through ERP, including which system owned each part of the product record.
05
Put governance in place so the data could keep improving
Established maintainable rules for enrichment, content consistency and ongoing data quality instead of treating catalogue preparation as a one-off task.

Systems

Systems, one operational truth.

The systems view follows product data from its source through enrichment and into each channel. The important questions are what each system owns, how changes move and who maintains the result.

Microsoft Dynamics 365 Business Central

Operational data system

Provided source product data and operational context for enrichment and channel preparation. Product information needed clear ownership between the ERP and the product data workflow. It mattered because unclear ownership or an incomplete data flow could create inconsistent product information across channels.

Akeneo PIM / PXM

Product information platform

Provided the product information platform used to structure, enrich and prepare catalogue data for connected channels. Product data work depended on clear boundaries between this platform, upstream data and each receiving channel. It mattered because unclear ownership or an incomplete data flow could create inconsistent product information across channels.

Commerce Tools

Project platform

Supported the Commerce Tools connection within the commerce operation.

Retail Syndication

Product data dependency

Supported the Retail Syndication connection within the commerce operation.

Risk control

Where this could have gone wrong.

PIM risk sits in ownership, structure and daily maintenance. These controls keep product information usable after the initial data work is complete.

Data ownership

When ownership is unclear, the same product field can be changed in more than one place and no team is accountable for the final value. How we held it: Assign an owner to each part of the product record and document where changes begin, who approves them and which system publishes them.

Attribute structure

Inconsistent attributes make products harder to enrich, compare and reuse across channels, especially as the catalogue grows. How we held it: Define shared attribute rules, required values and validation so product information follows one maintainable structure.

Category governance

Category structures can drift when teams organise the same products differently for separate channels or local needs. How we held it: Set category rules, ownership and review points so changes remain deliberate and reusable.

Product enrichment

Weak enrichment workflows create incomplete records, repeated content work and slow product onboarding. How we held it: Make enrichment stages, responsibilities and readiness checks visible before product information moves to a channel.

Asset/content consistency

Images, documents, descriptions and technical data can fall out of step with the product record they are meant to support. How we held it: Link assets and content to governed product records, with clear rules for updates and approval.

Channel readiness

Channels can receive product information before required attributes, content or assets are complete. How we held it: Define channel-specific readiness rules and prevent incomplete records from being treated as finished.

Workflow adoption

A technically sound data model still fails if teams continue to maintain product information outside the agreed workflow. How we held it: Align roles, training and daily maintenance work with the new ownership model.

Data maintenance

Without an ongoing maintenance process, quality falls after the initial catalogue work is complete. How we held it: Keep data quality checks, exception handling and ownership reviews active as products and channels change.

Outcome

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.

Week project

Kickoff to go-live

+245%

Streamlined catalog enrichment

Improvement recorded after launch

System integrations

Microsoft Dynamics 365 Business Central and Retail Syndication

Times adaptable and flexible to support change

Improvement recorded after launch

Platforms

Commerce Tools and Akeneo PIM

Commerce models

B2C and D2C

In their words

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.

Some live in the moment. Here at LoveCrafts, we make in the moment. Product quality and governance are key in our customer experience, iWeb have been a fantastic partner in helping us deliver that experience.”

Chloe Kumaran, Operations Manager, LoveCrafts

After launch

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

Surfaces from the live project.

Screenshots show how governed product information, content and assets are prepared for the channels and teams that use them.

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