Accommodations Lookahead

See the routes travelers are planning and how long they're looking to stay.

Lookahead analysis for accommodations consists of two tabs containing similar dashboards, one that reports on user-country to destination-country data and one that uses destination data only. This article describes both tabs, highlighting the differences between them.

Introduction

The Hotel Ads Search Trends dashboards pull advance-booking window and length-of-stay data from Google Hotel Ads impressions. Hotel Ads is how people browse hotel and vacation rental properties through Google. Users can specify location, check-in date, check-out date, number of people, and so on. Please see ads.google.com/hotels/ to discover how Google Hotel Ads works.

User privacy information: 

Trend data is anonymized using Differential Privacy, a practice that ensures user information cannot be inferred. We do not display markets that lack sufficient volume to meet the required threshold for anonymization. To further guarantee user privacy, we add a small amount of noise to the data.

Data is aggregated by search week and partitioned into buckets to maximize the number of markets that remain after anonymization. Volume numbers between the Destination Trends and Lookahead Analysis dashboards may not match exactly, as a smaller portion of markets are included in Lookahead Analysis.

Dashboard data is sourced from Google Hotel Ads and google.com queries.

Google Hotel Ads searches capture the booking window and length-of-stay trends needed to analyze the distribution of these “buckets” in a particular data representation, or “slice,” for example, by user country, destination country, and other insights. 

Google.com queries supply demand volume to help analyze the relative size of markets. Using the volume from google.com queries maintains consistency with the Accommodations Destination Trends. Queries can be specific ("Excellent Inn in NYC") or generic. They don't need to specify exact destination locations. They can also include expressions such as "vacation rentals near me." Queries like this will be used to define a destination region.

Lookahead analysis supports multiple different time periods based on search week. They range from the past week to the past 12 weeks. The time periods control how many search weeks to display and adjust the range of previous period comparisons. The time range can be changed in the Search Week filter. 

There are many ways to visualize Hotel Ads data. To emphasize user intent, the dashboard applies a weighting by default. Other visualizations are available through the "Queries to Include" selector.

The Filters

Lookahead accommodation reports show the following information:

  • Lookahead window: how far in advance travelers are looking to stay
  • Trip duration: how long travelers intend to stay
  • Trends: advanced booking and length of stay by user to destination geography and by search week

Options and filters on the right hand side of the window let you tailor the results for your markets. All reports are subject to filtering  as described below.

Search Week (required)

Set the number of weeks to include in the dashboard and to use in period-over-period comparisons. Note that each week represents the week of the user's search, starting on Sunday, and not the check-in week. 

Geo Filters

The Geo Filters in the Country to Country tab include user locations and destinations.

The Geo Filters in the Destinations tab only includes destinations.

Use the geography filters to constrain results by location. Geographies are defined as follows:

  • Domestic / Int'l: Whether the demand is within a country or between countries.
  • Subcontinent: A large part of a continent, e.g., North America, East Asia, etc.
  • Country: Country, e.g., US, Indonesia, France, etc.
  • Region: ISO 3166-2 administrative area 1. Usually a large part of a country, e.g., states in the US.
  • Location: Geographic or political location of the user's search (e.g., city, national parks, lakes, etc.).

Advanced

Queries to Include

  • All Queries: All anonymized Google Hotels queries are included and no additional processing is applied.
  • User-Selected Dates: Only anonymized Google Hotels queries where users explicitly selected a check-in or check-out date are included and no additional processing is applied.
  • All Queries (Weighted): All anonymized Google Hotels queries are processed and data is weighted based on user intent. This selection upweights queries where users explicitly selected a check-in or check-out date and downweights default date queries.

Dashboard sections

The Accommodations: Country to Country dashboard contains the following charts and tables:

Summary

Highlight the distribution of Advance Booking Window and Length of Stay, compared with the previous period.

The summary panel shows two bar charts:

  • Advance Booking Window Distribution shows how far in advance travelers are looking to stay, compared with the previous time period. Lookahead ranges start from same/next day to over 31 days.
  • Length of Stay Distribution compares the current period with period-over-period demand volume for length of stay, in nights.

The accompanying table, Demand in Advance Booking Window x Length of Stay Distribution, breaks out advance booking windows across length-of-stay ranges. Demand is rounded to the nearest significant number.

Advance Booking Window

Highlight when users expect to stay by showing the number of days between search date and check-in date. Bucketing is useful to identify the type of travels users are looking for, for example during holiday periods or for major events.

This section displays a timeline showing advance booking window trends over the current period (last 12 weeks for example). The Country to Country tab includes a bar chart comparing domestic to international booking windows over the same period.

The accompanying table shows countries with demand (rounded number of queries) by booking-window bucket percentages. The Country to Country tab includes the country of origin.

Length of Stay

Highlight how long users plan to stay by showing the number of days between check-in dates and check-out dates. Bucketing is useful to help further analyze the type of travels users are looking for, for example, business trips vs long holidays.

This section consists of a timeline showing length-of-stay trends over the current period (last 12 weeks for example). The Country to Country tab includes a bar chart comparing domestic to international length of stay over the same period.

The accompanying table shows countries with demand by length of stay bucket percentages. The Country to Country tab includes the country of origin.

Trends by Geo / Destination

For the Country to Country tab:

Highlight the distribution of Advance Booking Window and Length of Stay per user country - destination country when the users search for an accommodation in Hotel Ads.

The Trends by User and Destination Subcontinents table shows the relative demand share by user subcontinent and destination subcontinent, across advance booking window and length of stay.

The Trends by User and Destination Countries table shows the same information by user and destination countries.

For the Destinations tab:

Highlight the distribution of Advance Booking Window and Length of Stay per destination where the accommodations are located.

The Trends by Destination Subcontinents table shows the relative demand share by destination subcontinent across advance booking window and length of stay.

Three similar tables show the same information by destination country, destination region, and destination location.

Trends by Search Week

Highlight the distribution of Advance Booking Window and Length of Stay per search week when the users search for an accommodation in Google Hotels.

The Trends by Search Week table shows the relative demand for advance booking window and length of stay per search week, based on accommodation-related searches on Google.com.

 

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