Open Airbnb datasets for Heidelberg, Germany

Heidelberg, Germany

Total listings: 675

Last Updated: 2025-06-22

Download Data

Filter

How many Airbnbs are there in Heidelberg?

There are 439 entire homes listed across Airbnb in Heidelberg and the surrounding area, with 195 private bedrooms and 18 serviced apartments. The neighbourhood with the most listings is , with 82 entire homes costing an average of €144 per night. The second most populated neighbourhood for whole rental properties is with 69 listings, followed by with 51 entire homes.

Entire Homes

439

Private Rooms

195

Serviced Apartments

Shared Rooms

Bed Homes

298

Bed Homes

Basic Pricing

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

Airbnbs charging cleaning fee

55.1%

Average Airbnb cleaning fee

€45.73

Airbnbs charging taxes

3.4%

Average Airbnb taxes

€40.22

Average Price for Private Rooms

€82.97

Average Price for Serviced Apartments

€263.00

Airbnbs charging cleaning fee

55.1%

Avg. Airbnb cleaning fee

€45.73

Airbnbs charging taxes

3.4%

Avg. Airbnb taxes

€40.22

Avg. Price for Private Rooms

€82.97

Avg. Price for Serviced Apartments

€263.00

Basic pricing is taken from the date of data collection for 1 guest. This is the average price over the first 5 consecutive days the listing is available for, within the next two months. Where these conditions are not satisfied, no pricing data is recorded. Full weekly pricing and daily availability data is available on request. All prices are in EUR.

Doorstep Analytics offers comprehensive holiday rental datasets, including detailed pricing, availability, and estimated income. You can access the complete dataset directly or request a tailored analytics report to address specific questions and insights.

Reviews

Rating per Airbnb Listing

Number of Reviews on each Listing

Airbnb review scores in Heidelberg (4.78) are slightly above the average Airbnb review score across all locations (4.754) Nearly half of Airbnb listings use self-check in, with lockboxes, keypads or similar. This implies the property is in regular use as an Airbnb listing, or is run as part of a professional business. 15% of hosts have more than one listing in Heidelberg, also suggesting they are a business.

Hosts

Hosts listed as superhosts

36.9%

Hosts with more than 1 listing

15.0%

38%

of listings welcome guests with lockboxes or other self check-in methods

Hosts with Most Listings

Host Name	No. of Listings	Avg. Review Score
Carlos Daniel	19	4.89
Stay4business	17	5.0
David	17	4.53
BAAG Immobilien GmbH	14	4.7
Hans Günter Michael	13	None
Fritz	11	4.83
Dieter	8	4.95
Jessica	8	5.0
Hotel Am Schloss	7	4.65
Klaus Karl Friedrich	7	4.77
Monika & Thea	7	4.81
Giorgio	7	4.67
Jörg	6	4.84
Timo	6	4.83

38%

of listings welcome guests with lockboxes or other self check-in methods

Neighbourhoods

	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
Neuenheim	143	82	€144	56	€130	13	€167	2	€278	54	€130	4.82
Bergheim	123	69	€117	43	€101	19	€149	2	€159	26	€71	4.70
Rohrbach	84	51	€119	34	€84	7	€103	3	€217	33	€50	4.76
Leimen	54	39	€97	25	€92	9	€111	3	€90	12	€40	4.70
Schwetzingen	39	26	€103	13	€81	8	€100	4	€132	12	€98	4.79
Edingen-Neckarhausen	37	26	€87	19	€70	2	€74	2	€190	10	€41	4.81
Handschuhsheim	36	28	€106	18	€101	4	€112	4	€140	8	€55	4.83
Dossenheim	29	26	€99	16	€68	4	€102	4	€219	3	€60	4.92
Eppelheim	24	18	€89	8	€78	9	€99	0	-	6	€41	4.79
Wieblingen	23	12	€78	9	€86	1	€60	0	-	11	€64	4.74
Oftersheim	17	11	€78	8	€74	1	€70	2	€102	6	€31	4.76
Sandhausen	16	16	€74	11	€64	4	€115	0	-	0	-	4.85
Nußloch	16	15	€107	8	€75	4	€127	3	€140	1	€29	4.82

Show All ▼

Neighbourhoods are provided by user input in Airbnb. Where this data is not provided on Airbnb, a kNN machine learning model categorises listings into their most likely neighbourhood. Translated city names and names of large regions are removed where possible.