Know what is mapped. Know what needs work.
Explore hotel mapping reports for coverage, review queues, supplier changes and independently verified quality with clear metric definitions.
Mapping analytics measures the state and quality of relationships between supplier records and master entities. Useful reports distinguish mapping coverage, unresolved records, review workload and verified correctness. A high mapped percentage alone does not prove that the matches are accurate.
Give every record
a clearer role.
Practical controls for teams managing supplier data and mapping decisions.
Coverage with context
Track mapped, unmapped, reviewed and suspended supplier records with a clear scope and denominator.
Actionable review queues
Group outstanding decisions by reason, age, supplier and priority so a team can focus its effort.
Quality beyond a score
Measure accepted matches against independently verified labels and expose the evaluation sample and date.
Explain each change
Follow batch changes, manual corrections and rule releases back to affected source records and property IDs.
How mapping analytics fits together.
Define the population
Choose suppliers, file versions, date range and eligible record types before calculating the report.
Calculate distinct measures
Report coverage, review backlog, content completeness and verified precision as separate measures.
Inspect exceptions
Open the underlying evidence for conflicts, stale profiles, changed source codes and rejected candidates.
Track the resolution
Record ownership, a decision and its reason, then compare the next report using the same definitions.
Keep the context
with the connection.
The solution scope describes a production approach. The working website demo focuses on hotel matching; supplier APIs and other production modules require integration.
- Coverage denominator: distinct eligible supplier records in the selected scope, with exclusions disclosed.
- Precision denominator: predicted matches in an independently adjudicated evaluation set; report sample size and selection method.
- Keep browser demo metrics explicitly labelled illustrative and separate from production performance claims.
A few good questions.
Understand the data, the decisions, and the next step.
Explore all FAQsWhat is the difference between coverage and accuracy?
Coverage is the share of eligible source records with an accepted mapping. Accuracy describes correctness and needs verified reference labels. Mapping every record can increase coverage while still introducing incorrect matches.
Which mapping reports should an operations team use?
Start with supplier coverage, unmatched records, ambiguous candidates, review age, changed profiles, suspended supplier records, content conflicts and decision history. Add independently verified quality reporting when reference labels are available.
Can a confidence score be shown as an accuracy percentage?
Not without validation. A similarity or rule score describes the model's assessment for that record. Measured quality must be calculated using independently checked outcomes and reported with its evaluation scope.
How should model improvements be measured?
Evaluate a candidate version against a fixed verified test set, including difficult matches and non-matches. Compare precision, recall and review workload before approving a versioned release.
Connected solutions
A clearer identity starts here.
Explore the mapping workflow. Build a brief around your data.