There are 113 entire homes listed across Airbnb in Agra and the surrounding area, with 451 private bedrooms
and 2 serviced apartments.
The neighbourhood with the most listings is Sikandra,
with 5 entire homes
costing an average of Rs3,149 per night.
The second most populated neighbourhood for whole rental properties is
Basai with 0 listings, followed by
Kahrai with 4 entire homes.
Entire Homes
113
Private Rooms
451
Serviced Apartments
2
Shared Rooms
5
1
Bed Homes
28
2
Bed Homes
40
3
Bed Homes
28
4
Bed Homes
6
5
Bed Homes
2
6+
Bed Homes
11
Basic Pricing
The figures below represent the average nightly price in INR over the first five consecutive available nights within the next two months.
This reflects the standard Airbnb rate shown when no specific check-in or check-out dates are selected and is based on two guests by default.
For approximately 2% of listings with no upcoming availability, these criteria are not met and no pricing data is recorded.
Complete weekly pricing and daily availability data are available upon request.
Average Price per night per Bedrooms
for entire homes and serviced apartments
Average Price per night per Bedrooms
for entire homes and serviced apartments
Average Price per night per Max. Guests
for entire homes and serviced apartments
Average Price per Review Score
Average Price for Other Property Types
Farm stay: Rs5648
Airbnbs charging taxes
97.8%
Average Airbnb taxes
Rs1110.53
Average Price for Private Rooms
Rs2978.97
Average Price for Serviced Apartments
Rs9413.11
Airbnbs charging taxes
97.8%
Avg. Airbnb taxes
Rs1110.53
Avg. Price for Private Rooms
Rs2978.97
Avg. Price for Serviced Apartments
Rs9413.11
Reviews
Airbnb review scores in Agra (4.63) are
significantly below
the average Airbnb review score across all locations (4.754).
There are 274 listings with zero reviews. While some of these will be new properties, it is
possible many are lets only offered for a very short time window, or are junk listings. These results can be filtered out using the controls
at the top of this report.
Rating per Airbnb Listing
Number of Reviews on each Listing
Hosts
Approximately a third of
Airbnb listings offer self check-in through lockboxes, keypads, or similar.
This suggests these properties are either regularly rented on Airbnb or managed professionally.
21% of hosts have more than one listing in Agra, indicating a business presence.
Additionally, 17% of hosts are superhosts; a status awarded by Airbnb for hosts with at least 10 reservations,
an average rating of 4.8 or higher, a fast response rate, and low cancellation rate. This status is assessed once every three months.
of hosts welcome guests with lockboxes, keypads, smart locks or other self check-in methods
Doorstep Analytics provides in-depth vacation rental datasets, covering pricing, availability, text descriptions and guest reviews.
Access the full dataset or submit an analytics request to answer your specific questions.
Request Analytics
Neighbourhoods
Neighbourhood information is sourced from host input on Airbnb’s platform.
When this data is unavailable, a k-nearest neighbours (kNN) machine learning model assigns each listing to its most probable neighbourhood.
Translated city names and names of large regions are filtered out where possible.
Total
All Entire Homes
1-Bed Homes
2-Bed Homes
3-Bed Homes
Private Rooms
Reviews
Count
Count
Avg. Price
Count
Avg. Price
Count
Avg. Price
Count
Avg. Price
Count
Avg. Price
Avg. Score
Sikandra
20
5
3,149
2
1,364
2
5,498
1
2,023
12
1,847
4.71
Basai
17
0
-
0
-
0
-
0
-
17
2,401
4.74
Kahrai
15
4
7,610
2
3,123
0
-
1
3,607
9
2,551
5.00
Show All ▼
Download Data
Airbnb Overview
Basic property, host and review data for all Airbnb listings
Airbnb Pricing
Pricing per weekend and weekday, for the next 50 weeks
Airbnb Availability
Daily check-in and check-out availability, per listing
Airbnb Reviews
All review text and scores
Airbnb Descriptions
Text descriptions of property space, location and host details
Airbnb Amenities
Amenities featured in each property
Data Dictionary
Verbose descriptions of all fields
Access complete datasets
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