ReviewSummary

Description

Summary of publicly available customer reviews for this entity.

Time Structure

The review summary is a time series.

**Rank = 0**: The most recent review summary has rank 0
**Higher ranks (1, 2, etc.)**: Represent review summaries from earlier periods in time.

Healthy businesses will have a steadily increasing number of reviews overtime. You can calculate the "review velocity" by measuring the difference in review_count between time periods. The review velocity may be a useful indicator of business health.

Data Sources

The status data is derived from:

Actual customer reviews about business locations that are publicly available

Methodology

Sourced from publicly available customer reviews of locations. This data is updated at least every months for each location. For simplicity, individual reviews are aggregated to provide an overview of a location. It's possible for reviews to be removed or edited after some time, so it's possible you may see the number of reviews *decrease* for a location at one point in time.

type ReviewSummary implements MathFunctions {
  id: UUID!
  firstObservedDate: String
  lastObservedDate: String
  reviewCount: String
  reviewScoreAvg: String
  firstReviewDate: Date
  lastReviewDate: Date
  internalId: String
  internalReviewSummaryId: String
  operatingLocations(
    first: Int = 100
    last: Int
    after: String
    before: String
    conditions: ConnectionConditions
  ): ReviewSummaryOperatingLocationConnection
  count(
    field: String!
    conditions: Conditions
  ): Int
  sum(
    field: String!
    conditions: Conditions
  ): Int
  min(
    field: String!
    conditions: Conditions
  ): Int
  max(
    field: String!
    conditions: Conditions
  ): Int
  avg(
    field: String!
    conditions: Conditions
  ): Float
  collect(
    field: String!
    separator: String
    conditions: Conditions
  ): String
  minDateTime(
    field: String!
    conditions: Conditions
  ): DateTime
  maxDateTime(
    field: String!
    conditions: Conditions
  ): DateTime
}

Fields

`ReviewSummary.id` ● `UUID!` non-null scalar

`ReviewSummary.firstObservedDate` ● `String` scalar

`ReviewSummary.lastObservedDate` ● `String` scalar

`ReviewSummary.reviewCount` ● `String` scalar

The number of reviews submitted for a location.

`ReviewSummary.reviewScoreAvg` ● `String` scalar

The average rating of the reviews for a location. The average rating is the weighted average of reviews submitted by customers during the life of the location

`ReviewSummary.firstReviewDate` ● `Date` scalar

The date of the earliest available review (from a sample of one hundred reviews).

`ReviewSummary.lastReviewDate` ● `Date` scalar

The date of the latest available review. Because up to three months may elapse before we refresh the reviews, more reviews may be submitted after this date that aren't reflected in our data. So a lag may develop which is removed at least every three months.