Catalogue and Product Data Support
Product data, listing accuracy and catalogue administration support for eCommerce and consumer-product teams.
Page guide
On this page
Service workflow
What catalogue and product data support covers
Product data support reduces preventable customer contact. A wrong size chart, missing compatibility note or broken image creates avoidable pre-purchase and return volume.
The service is scoped as a repeatable workflow rather than a vague promise to help. Before go-live we define the task list, exclusions, escalation triggers, systems, tone, reporting and the exact point at which an agent must stop and route to the client.
Written tasks, exclusions and authority.
Agents trained to one client process.
Operational KPIs and quality sampling.
Work handled by the team
These tasks are the normal operating surface. Some clients need all of them, others start with the two or three that remove the greatest bottleneck. RHI would rather pilot a narrow process cleanly than launch a broad one that depends on guesswork.
- Create and update product records under client rules.
- Check titles, attributes, images and descriptions.
- Flag missing or inconsistent product data.
- Support marketplace listing requirements.
- Route product questions that need brand owner judgement.
Workflow and handoff
Items move from source data to draft listing, QA check, publication and exception report. Changes are tracked so errors can be reversed.
Every workflow has a visible owner at each step. If the agent can resolve it, the case closes with a reason code. If the agent cannot resolve it, the case moves with enough evidence that the next person does not have to repeat the same questions.
Channels, systems and escalation
Work happens in commerce platforms, PIM systems, spreadsheets and marketplace portals.
Merchandising or product owners receive exception lists, missing data and repeated customer-question themes.
System access is kept as close as possible to the work being done. That usually means named accounts, role-based permissions, no local storage for sensitive files and a written rule for when screenshots, documents or customer media may be requested.
Quality, reporting and boundaries
Quality review looks at accuracy first. A warm answer that gives the wrong status, misses an escalation trigger or oversteps authority is still a failed contact. The scorecard is therefore specific to this service rather than copied from a generic customer-service template.
- Listing completeness.
- Data correction cycle time.
- Customer contact caused by listing error.
- Marketplace rejection rate.
- QA pass rate.
RHI does not invent product claims, safety statements or compliance information. Source-approved data controls the listing.
Boundary breaches are treated as critical issues because they create risk for both the client and the customer. Agents are trained with examples of what to say when the customer asks for something outside scope, so routing still feels helpful.
Launch plan
Launch needs attribute rules, source-of-truth files, approval process, marketplace requirements and QA checklist.
The monitored pilot checks whether volumes, handling time, escalation rate and quality match the assumptions. When they do, the team can scale. When they do not, the fix is made while the scope is still small enough to control.
Operating model in practice
RHI sets up catalogue and product data support as a controlled production process. The service has a queue, a priority rule, a knowledge source, an action list, an escalation path and a quality scorecard. Those pieces are simple, but they prevent the common failure where an outsourced team is trained on brand tone and left to discover the actual work during live contacts.
Agent training starts with the customer intent rather than the tool. The agent learns why someone contacts, what the customer is trying to achieve, what the client needs protected, and which pieces of information decide the next step. Only then does system training become useful. A person who knows which decision they are making will use the tool more accurately than someone who only knows where to click.
Supervision is visible from the first week. Team leads review samples, listen for uncertainty, compare escalation notes with client feedback and update the knowledge base when the same question appears more than once. The aim is not to punish agents for edge cases. It is to turn edge cases into written rules so the second customer gets a cleaner answer than the first.
The commercial value is measured in removed friction. Depending on the service, that may mean fewer missed calls, faster completion, fewer returned cases, better documentation, fewer avoidable escalations or a lower repeat-contact rate. RHI reports those trends alongside volume so the client can see whether the team is improving the operation rather than simply processing more work.
Useful next pages: eCommerce and retail, consumer products and data entry.
Frequently asked questions
It includes the operational tasks listed on this page, delivered by trained agents in the client-approved systems and under a written scope.
It excludes judgement calls, regulated decisions, professional advice and commitments outside the authority agreed before go-live.
Usually yes. RHI normally works in the client help desk, CRM, commerce, finance, HR or operational tools so data does not need to be copied into a parallel system.
Calls, tickets or completed work are sampled against a scorecard that covers accuracy, completeness, tone, verification, escalation and boundary adherence.
Timing depends on complexity, access, recruitment and training. A bounded pilot launches faster than a large multi-channel deployment, and it is usually the safer first step.