Indianapolis, United States

Last updated: June 29, 2025

2,848 active listings

North America

Market Overview & Investment Analysis

This deep-dive into the Indianapolis Airbnb market provides a comprehensive analysis for investors and researchers. With a total of 2,848 active listings in the past 12 months, Indianapolis presents a significant short-term rental landscape. The key financial indicators are promising, with an average nightly rate of $188 and a robust occupancy rate of 41.4%. These figures contribute to an estimated average annual revenue of $22,323 per listing, highlighting the investment potential within the United States region.

Total Listings

2,848

Average Price

$188

Occupancy Rate

41.4%

Annual Revenue

$22323

Available Datasets

Listings Data

Comprehensive property listings with detailed information including property attributes, ratings across multiple categories and various trailing twelve months performance metrics

CSVJSONParquet

Schema

Field	Type	Description
listing_id	long	Unique identifier for the listing
listing_name	string	Title of the listing
listing_type	string	Type of property (e.g., apartment, house, villa)
room_type	string	Type of room (e.g., entire home, private room)
cover_photo_url	string	URL of the main listing photo
photos_count	integer	Number of photos available for the listing
host_id	long	Unique identifier for the host
host_name	string	Name of the host
cohosts	string	Names of co-hosts associated with the listing
superhost	boolean	Whether the host is a superhost
country	string	Country where the listing is located
state	string	State or province where the listing is located
city	string	City where the listing is located
latitude	decimal(10,4)	Geographical latitude coordinate
longitude	decimal(10,4)	Geographical longitude coordinate
guests	integer	Maximum number of guests allowed
bedrooms	integer	Number of bedrooms available
beds	integer	Number of beds available
baths	decimal(4,1)	Number of bathrooms available
registration	boolean	Indicates if the listing has a registration number
amenities	string	List of amenities offered
instant_book	boolean	Whether the listing can be booked instantly
min_nights	integer	Minimum number of nights required to book
cancellation_policy	string	Type of cancellation policy offered
currency	string	Currency used for pricing
cleaning_fee	integer	The cleaning fee for the listing
extra_guest_fee	integer	Fee for each extra guest
num_reviews	integer	Total number of reviews received
rating_overall	double	Overall rating score
rating_accuracy	double	Rating score for listing accuracy
rating_checkin	double	Rating score for check-in experience
rating_cleanliness	double	Rating score for cleanliness
rating_communication	double	Rating score for host communication
rating_location	double	Rating score for location
rating_value	double	Rating score for value
ttm_revenue	double	Total revenue in trailing twelve months
ttm_revenue_native	double	Total revenue in native currency in trailing twelve months
ttm_avg_rate	double	Average daily rate in trailing twelve months
ttm_avg_rate_native	double	Average daily rate in native currency in trailing twelve months
ttm_occupancy	double	Occupancy rate in trailing twelve months
ttm_adjusted_occupancy	double	Adjusted occupancy rate in trailing twelve months, excluding owner-blocked days
ttm_revpar	double	Revenue per available room (RevPAR) in trailing twelve months
ttm_revpar_native	double	Revenue per available room (RevPAR) in native currency in trailing twelve months
ttm_adjusted_revpar	double	Adjusted RevPAR in trailing twelve months
ttm_adjusted_revpar_native	double	Adjusted RevPAR in native currency in trailing twelve months
ttm_reserved_days	long	Number of booked/reserved days in trailing twelve months
ttm_blocked_days	long	Number of host-blocked days in trailing twelve months
ttm_available_days	long	Number of available days in trailing twelve months
ttm_total_days	long	Total number of days in trailing twelve months (reserved + available)
l90d_revenue	double	Revenue in the last 90 days
l90d_revenue_native	double	Revenue in native currency in the last 90 days
l90d_avg_rate	double	Average daily rate in the last 90 days
l90d_avg_rate_native	double	Average daily rate in native currency in the last 90 days
l90d_occupancy	double	Occupancy rate in the last 90 days
l90d_adjusted_occupancy	double	Adjusted occupancy rate in the last 90 days
l90d_revpar	double	RevPAR in the last 90 days
l90d_revpar_native	double	RevPAR in native currency in the last 90 days
l90d_adjusted_revpar	double	Adjusted RevPAR in the last 90 days
l90d_adjusted_revpar_native	double	Adjusted RevPAR in native currency in the last 90 days
l90d_reserved_days	long	Number of reserved days in the last 90 days
l90d_blocked_days	long	Number of blocked days in the last 90 days
l90d_available_days	long	Number of available days in the last 90 days
l90d_total_days	long	Total number of days considered in the last 90 days period

Past Calendar Rates

Past 12 months of calendar rates data with occupancy rates, revenue metrics, average daily rates, booking lead times, and minimum night requirements

CSVJSONParquet

Schema

Field	Type	Description
listing_id	long	Unique identifier for the listing
date	date	First day of the month for aggregated monthly data
vacant_days	integer	Number of days the property was vacant
reserved_days	integer	Number of days the property was reserved
occupancy	double	Occupancy rate
revenue	double	Total revenue generated during the month
rate_avg	double	Average daily rate
booked_rate_avg	double	Average rate when booked
booking_lead_time_avg	integer	Average booking lead time in days
length_of_stay_avg	integer	Average length of stay in days
min_nights_avg	integer	Average minimum nights requirement
native_booked_rate_avg	double	Average rate when booked in native currency
native_rate_avg	double	Average daily rate in native currency
native_revenue	double	Revenue generated in native currency

Future Calendar Rates

Future 12 months of calendar rates data with occupancy forecasts, expected revenue, pricing trends, and advanced booking information for upcoming months

CSVJSONParquet

Schema

Field	Type	Description
listing_id	long	Unique identifier for the listing
date	date	First day of the month for aggregated monthly data
vacant_days	integer	Number of days the property was vacant
reserved_days	integer	Number of days the property was reserved
occupancy	double	Occupancy rate
revenue	double	Total revenue generated during the month
rate_avg	double	Average daily rate
booked_rate_avg	double	Average rate when booked
booking_lead_time_avg	integer	Average booking lead time in days
length_of_stay_avg	integer	Average length of stay in days
min_nights_avg	integer	Average minimum nights requirement
native_booked_rate_avg	double	Average rate when booked in native currency
native_rate_avg	double	Average daily rate in native currency
native_revenue	double	Revenue generated in native currency

Reviews Data

Monthly review aggregations showing review counts and reviewer IDs associated with each listing

CSVJSONParquet

Schema

Field	Type	Description
listing_id	long	Unique identifier for the listing
date	date	First day of the month when reviews were aggregated
num_reviews	long	Number of reviews for the listing
reviewers	array<long>	List of reviewer IDs

Host Data ✨ Coming Soon

Host profile information including verification status, superhost designation, ratings, property portfolio size, languages spoken, and biographical details

CSVJSONParquet

Schema

Field	Type	Description
host_id	long	Unique identifier for the host
host_name	string	Name of the host
is_host	boolean	Whether the user is a host
is_superhost	boolean	Whether the host is a superhost
ratings	decimal	Host rating score
reviews_count	integer	Number of reviews received by the host
listing_count	integer	Number of properties managed by host
member_since	date	Date the host joined the platform
languages	array<string>	Languages spoken by the host
profile_picture	string	URL to host profile image
about	string	Host self-description and biography

Data Information

Update Frequency
Monthly
Last Updated
June 29, 2025
Data Verification
Verified and cleaned by our data science team
Usage License
Academic and personal use license included

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Indianapolis, United States

Market Overview & Investment Analysis