Real Estate
17 columns
200 rows
8 formats

Property Listing Engagement Metrics

This dataset provides granular engagement metrics for property listings on PropTech platforms, including user interactions, session details, conversion indicators, and geographic context. It enables platforms to analyze user behavior, optimize listings, and improve conversion rates through actionable insights. The comprehensive structure supports segmentation, trend analysis, and targeted marketing strategies.

last updated 20 Aug 2025
by GoMask

The brief that made it

Optimizing property listing engagement and conversion rates

Sample rows

preview · 8 of 200 rows · all 17 columns

engagement_idstring	engagement_typestring	session_duration_secondsinteger	conversion_flagboolean	user_location_citystring	listing_idstring	user_idstring	user_typestring	engagement_datetimedatetime	device_typestring	user_location_statestring	user_location_countrystring	referral_sourcestring	listing_pricefloat	listing_citystring	listing_statestring	listing_countrystring
ENGA_1A7B9Q	view	94	false	New York	LST10023	USR70139	buyer	2024-05-01T13:15:22Z	mobile	NY	US	organic	829000	New York	NY	US
ENGC_2B8K0P	favorite	151	false	New York	LST10023	USR70140	buyer	2024-05-01T14:22:11Z	desktop	NY	US	organic	829000	New York	NY	US
ENGQ_3D9S6T	view	67	false	Chicago	LST10031	USR70026	renter	2024-04-15T09:41:37Z	mobile	IL	US	social	2200	Chicago	IL	US
ENGJ_4E0N7U	share	78	false	London	LST10015	USR30182	agent	2024-03-29T16:45:10Z	desktop	blank	GB	other	655000	London	blank	GB
ENGH_5F1M8V	inquiry	110	true	Berlin	LST10019	USR30182	agent	2024-04-03T11:38:55Z	tablet	blank	DE	direct	740000	Berlin	blank	DE
ENGK_6G2P9W	contact	212	true	Los Angeles	LST10042	USR82211	buyer	2024-05-06T10:20:31Z	mobile	CA	US	paid	995000	Los Angeles	CA	US
ENGW_7H3R0X	view	83	false	Los Angeles	LST10042	USR82212	buyer	2024-05-07T13:04:12Z	mobile	CA	US	organic	995000	Los Angeles	CA	US
ENGA_8J4S1Y	favorite	115	false	Vancouver	LST10051	USR90021	renter	2024-05-02T16:44:02Z	mobile	BC	CA	social	3100	Vancouver	BC	CA
ENGM_9K5T2Z	inquiry	121	true	Toronto	LST10061	USR22031	renter	2024-05-05T17:39:29Z	desktop	ON	CA	paid	3350	Toronto	ON	CA
ENGV_0L6U3A	view	59	false	Toronto	LST10072	USR22032	renter	2024-05-09T13:57:17Z	mobile	ON	CA	organic	2950	Toronto	ON	CA
ENGZ_1M7V4B	share	62	false	Madrid	LST10081	USR33089	agent	2024-05-10T10:15:10Z	tablet	blank	ES	other	540000	Madrid	blank	ES
ENGT_2N8W5C	view	97	false	Paris	LST10091	USR33090	agent	2024-05-13T09:41:46Z	desktop	blank	FR	social	825000	Paris	blank	FR
ENGP_3O9X6D	view	18	false	blank	LST10101	USR54012	guest	2024-05-15T17:05:02Z	mobile	blank	blank	organic	0	Tokyo	blank	JP
ENGU_4P0Y7E	favorite	25	false	blank	LST10101	USR54013	guest	2024-05-15T18:11:15Z	desktop	blank	blank	other	0	Tokyo	blank	JP
ENGB_5Q1Z8F	view	110	false	Miami	LST10113	USR65678	buyer	2024-05-19T11:55:34Z	mobile	FL	US	direct	580000	Miami	FL	US
ENGN_6R2A9G	contact	198	true	Miami	LST10121	USR65679	buyer	2024-05-20T13:28:40Z	desktop	FL	US	paid	600000	Miami	FL	US
ENGF_7S3B0H	view	46	false	Dallas	LST10134	USR91023	renter	2024-05-23T15:09:51Z	mobile	TX	US	organic	1920	Dallas	TX	US
ENGD_8T4C1I	inquiry	95	true	Dallas	LST10134	USR91024	renter	2024-05-23T15:44:30Z	desktop	TX	US	paid	1920	Dallas	TX	US
ENGB_9U5D2J	share	157	false	Denver	LST10149	USR71009	buyer	2024-05-26T10:21:17Z	desktop	CO	US	social	462000	Denver	CO	US
ENGC_0V6E3K	view	72	false	Denver	LST10162	USR71010	buyer	2024-05-29T09:03:25Z	mobile	CO	US	organic	462000	Denver	CO	US

What the 200 rows show

from the 200-row sample

Inquiry (engagement type) stands out: 42 of its 45 rows have conversion_flag = true, against 14 of 155 for the rest.

28%conversion_flag = true
79.5median session_duration_seconds
3device types
4user types
5referral sources
11user location countries

Conversion flag rate by engagement_typeconversion_flag = true

session_duration_seconds200 rows, in bands of 50

Median 79.5, from 4 to 298.

user_location_city171 rows with a value · 29 left blank

Berlin13
Dallas13
Boston13
Chicago12
Vancouver11
Madrid10
San Francisco10
Toronto9
Seattle9
London7

17 columns by typefrom the column list below

string 13
integer 1
float 1
datetime 1
boolean 1

Columns

17 columns in four groups

blueprint · 17 columns
column	type	description	example
Text 13 columns
`engagement_id`	string	Unique identifier for each engagement recordunique	ENGA_1A7B9Q
`listing_id`	string	Unique identifier for the property listing	LST10023
`user_id`	string	Unique identifier for the user interacting with the listing	USR70139
`user_type`	string	Type of user (e.g., buyer, renter, agent, guest)buyer · renter · agent · guest	buyer
`engagement_type`	string	Type of engagement action performed (e.g., view, favorite, share, inquiry, contact)view · favorite · share · inquiry · contact	view
`device_type`	string	Type of device used for engagement (e.g., desktop, mobile, tablet)desktop · mobile · tablet · optional	mobile
`user_location_city`	string	City from which the user engaged with the listingoptional	New York
`user_location_state`	string	State from which the user engaged with the listingoptional	NY
`user_location_country`	string	Country from which the user engaged with the listing11 countries · optional	US
`referral_source`	string	Source from which the user arrived at the listing (e.g., organic, paid, social, direct)organic · paid · social · direct · other · optional	organic
`listing_city`	string	City where the property listing is locatedoptional	New York
`listing_state`	string	State where the property listing is locatedoptional	NY
`listing_country`	string	Country where the property listing is locatedoptional	US
Numbers 2 columns
`session_duration_seconds`	integer	Duration of the user's session on the listing in seconds0 or more · optional	94
`listing_price`	float	Current price of the property listing at the time of engagement0 or more · optional	829000
Dates and times 1 column
`engagement_datetime`	datetime	Timestamp of when the engagement occurred	2024-05-01T13:15:22Z
True or false 1 column
`conversion_flag`	boolean	Indicates if the engagement led to a conversion (e.g., inquiry, booking, contact)	false

Use it for

A real estate dashboard
The conversion_flag rate, session_duration_seconds by engagement_type and a breakdown of user_location_city. Excel, Power BI or Tableau.
Why do 56 of 200 rows have conversion_flag = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Engagements200
ENGA_1A7B9Q94view
ENGH_5F1M8V110inquiry
ENGK_6G2P9W212contact
A software demo
Believable engagements with listing_id, user_id and user_type to fill a screen in front of a buyer.

This dataset200 rows17 columns

Yours1,000 rows17 columnsuser_location_city: UK only

blueprint · property-listing-engagement-metrics

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 17 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Track property listing ID and views
Record inquiry sent and contact attempts
Flag highly engaged listings
Exclude expired listings

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: property-listing-engagement-metrics

What should your data show?

No signup. No card.

Sample rows

What the 200 rows show

Columns

Use it for

A real estate dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Real Estate

What should your data show?