In our recent quality review, it came to our attention that many analysts have been doing many mistakes that we consider now to be common issues in your
market.
Please take time to review this document as it will help you improve your quality.
If anything is unclear or you need further support, please don’t hesitate to contact us on our mapping portal https://homeworker.custhelp.com and we will get back
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Relevance rating for a prominent suggestion
In the task below, the query is for “Ghirnat” with a stale viewport age. Most likely the query is for Ghirnatah which is a sub locality within Riyadh. Even though this suggestion is not the closest to the user location, it is the most prominent suggestion which should be promoted to Excellent.
Suggestions with high prominence may still be relevant even when far away from the user.
Suggestions with low prominence, on the other hand, may not be as relevant even if they are close to the user.
GL Section 4.3.3 and 4.3.4: Prominence and Distance vs. Prominence.
The prominence of a feature refers to its popularity, including the number of people visiting and media sources referencing it. Prominence can vary based on the test locale and even local knowledge. Consider the following list to get a general idea of the concept of prominence, ordered from the most prominent to the least prominent:
The feature is known internationally
The feature is known in the country
The feature is known in the suggestion region The feature is known locally
The feature may not even be known locally
Rating for Category Queries with far away suggestions
In the task below, the suggestion matches the query however when we search the real world, we did not find any suggestions within and around the viewport. Since there are other suggestions and categories that could match the query, this category suggestion should be rated as Bad.
Once you’ve decided how relevant the suggestion is based on user intent, consider the suggestion in the context of all possible suggestions in the real world.
GL Section 4.13. Query and Category Suggestions
Query and category suggestions are rated by considering the user intent and the possible suggestions within the viewport. For a query/category suggestion to be valid it needs to provide some use to the user. Simply matching the user query is not enough on its own. When both individual POI results and a query suggestion for the same chain are present, give the query suggestion the highest rating the closest existing POI result can achieve.
Fewer suggestions within the requested area
In the task below, the user asked for a specific chain business (Alharm) with a general location modifier in the form of a sub locality (Namar). The fresh viewport can be ignored since the user has a specific area in mind for results. Because there are very few stores within the specified area, results outside it are gradually demoted. The best rating for the suggestion would be Good.
GL Section 2.3.1 Explicit Location
If there are few results for the chain business inside the requested location, results outside the area may be demoted less severely depending on how close they are to the named location and how many branches of the chain exist in the real world. Ratings may range from
Good to Bad.
This is because when there are fewer locations of a chain business inside the requested area, results that are outside it can still be relevant. However, it’s also possible for results to be so far away from the location that they have no relevance at all.
Relevance Rating Based on Matching the Query String
In the task below, although the suggestion doesn’t match the beginning of the query string, users in Saudi Arabia are likely to start their search with “تﻟا” when searching for this POI.
Correct relevance: Excellent.
It’s often difficult to identify the user primary intent, so you’ll have to research the individual suggestions provided to make your rating decisions as well as doing general research in the area of location intent.
GL Section 4.1.Matching the Query String and 4.1.1. General Match
Matching to the query string is the first step in the rating process and is the minimum requirement for a suggestion to be considered relevant. Once a match is confirmed, the relevance rating is rated in terms of prominence and distance. If there is no match between the query and the suggestion, rate the suggestion Relevance as bad.