Remote Agent Productivity Metrics
This dataset provides comprehensive, daily productivity metrics for remote real estate agents, including deal progression, client engagement, and time management indicators. It is ideal for operations managers and real estate technology startups seeking to monitor, benchmark, and optimize the performance of distributed agent teams. The dataset supports granular analysis of agent efficiency, team trends, and regional performance.
Sample rows
preview · 8 of 75 rows · all 19 columns| agent_idstring | attendance_statusstring | hours_workedfloat | team_namestring | agent_namestring | emailstring | regionstring | datedate | deals_initiatedinteger | deals_in_progressinteger | deals_closedinteger | deals_lostinteger | total_deal_valuefloat | clients_contactedinteger | client_meetingsinteger | follow_ups_madeinteger | productive_hoursfloat | tasks_completedinteger | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| A1001 | present | 8.5 | Summit Group | Jessica Lam | jessica.lam@ | Pacific Northwest | 2024-06-05 | 2 | 5 | 1 | 1 | 350000 | 7 | 2 | 4 | 7.2 | 6 | Solid client engagement, one deal closed, proactive follow-ups |
| A1002 | present | 5 | Skyline Team | Raymond Chen | raymond.chen@ | Northeast | 2024-06-05 | 0 | 2 | 0 | 1 | 0 | 4 | 1 | 2 | 4.6 | 3 | blank |
| A1003 | present | 9.2 | Urban Pioneers | Lila Patterson | lila.patterson@ | Midwest | 2024-06-05 | 1 | 4 | 2 | 0 | 515000 | 8 | 3 | 6 | 8.9 | 7 | Excellent performance, high deal closure rate |
| A1004 | present | 6 | Eco Realty | Samuel Ortiz | samuel.ortiz@ | Southeast | 2024-06-05 | 3 | 3 | 0 | 2 | 0 | 5 | 2 | 1 | 5.8 | 2 | Lost two deals, needs to improve closing tactics |
| A1005 | half_day | 2.5 | Horizon Crew | Monique Russell | monique.russell@ | Southwest | 2024-06-05 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 2.2 | 1 | Half-day attendance due to appointment |
| A1006 | present | 8 | Skyline Team | Evan Brooks | evan.brooks@ | Northeast | 2024-06-05 | 2 | 2 | 0 | 1 | 0 | 5 | 2 | 3 | 7.5 | 3 | blank |
| A1007 | present | 7.3 | Urban Pioneers | Priya Singh | priya.singh@ | Midwest | 2024-06-05 | 1 | 5 | 2 | 1 | 420000 | 6 | 2 | 3 | 6.8 | 5 | blank |
| A1008 | present | 4 | Summit Group | Leonardo Costa | leonardo.costa@ | Pacific Northwest | 2024-06-05 | 0 | 2 | 0 | 0 | 0 | 3 | 1 | 1 | 3.4 | 2 | blank |
| A1009 | present | 10 | Eco Realty | Hannah Kim | hannah.kim@ | Southeast | 2024-06-05 | 3 | 4 | 2 | 1 | 390000 | 9 | 3 | 7 | 9.1 | 8 | Strong productivity and engagement |
| A1010 | present | 7.1 | Horizon Crew | Owen Stewart | owen.stewart@ | Southwest | 2024-06-05 | 1 | 2 | 0 | 2 | 0 | 5 | 1 | 2 | 6 | 2 | blank |
| A1011 | present | 8.3 | Skyline Team | Isabel Garcia | isabel.garcia@ | Northeast | 2024-06-05 | 2 | 3 | 1 | 1 | 275000 | 4 | 2 | 4 | 7.9 | 4 | blank |
| A1012 | present | 5 | Urban Pioneers | Marcus Lee | marcus.lee@ | Midwest | 2024-06-05 | 1 | 2 | 0 | 0 | 0 | 3 | 1 | 2 | 4.1 | 2 | blank |
| A1013 | half_day | 2.2 | Eco Realty | Sara Fields | sara.fields@ | Southeast | 2024-06-05 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 1.8 | 1 | blank |
| A1014 | present | 9 | Horizon Crew | Jamal Bryant | jamal.bryant@ | Southwest | 2024-06-05 | 3 | 4 | 2 | 1 | 470000 | 7 | 3 | 6 | 8.3 | 6 | blank |
| A1015 | present | 7.7 | Summit Group | Alina Popov | alina.popov@ | Pacific Northwest | 2024-06-05 | 2 | 2 | 1 | 1 | 320000 | 6 | 2 | 3 | 7 | 5 | blank |
| A1016 | present | 7.6 | Skyline Team | David Morgan | david.morgan@ | Northeast | 2024-06-05 | 0 | 3 | 1 | 2 | 295000 | 5 | 1 | 3 | 6.8 | 3 | blank |
| A1017 | present | 6.3 | Urban Pioneers | Yasmin Ali | yasmin.ali@ | Midwest | 2024-06-05 | 1 | 2 | 0 | 1 | 0 | 4 | 2 | 2 | 5.6 | 2 | blank |
| A1018 | present | 8.9 | Eco Realty | Tyler Reed | tyler.reed@ | Southeast | 2024-06-05 | 3 | 5 | 2 | 1 | 405000 | 8 | 3 | 5 | 8.2 | 7 | Above average productivity |
| A1019 | present | 7.5 | Horizon Crew | Mason Carter | mason.carter@ | Southwest | 2024-06-05 | 2 | 3 | 1 | 1 | 315000 | 6 | 2 | 4 | 6.9 | 4 | blank |
| A1020 | half_day | 2.6 | Summit Group | Kendra Jones | kendra.jones@ | Pacific Northwest | 2024-06-05 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 2.1 | 1 | blank |
What the 75 rows show
from the 75-row sampleHalf_
- 6.7median hours_
worked - 9regions
- 2median deals_
initiated - 3median deals_
in_ progress - 1median deals_
closed - 1median deals_
lost
Median 6.7, from 2.1 to 10.2.
- string 7
- integer 8
- float 3
- date 1
Columns
19 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 7 columns | |||
agent_id | string | Unique identifier for the remote real estate agentunique | A1001 |
agent_name | string | Full name of the remote real estate agent | Jessica Lam |
email | string | Agent's work email addressunique | evan.brooks@ |
team_name | string | Name of the agent's team or groupoptional | Summit Group |
region | string | Geographical region or market the agent operates in9 regions · optional | Pacific Northwest |
attendance_status | string | Attendance status of the agent for the given datepresent · absent · on_leave · half_day | present |
notes | string | Additional notes or comments about the agent's performance or activities on the given dateoptional | Closed an important deal |
| Numbers 11 columns | |||
deals_initiated | integer | Number of new deals initiated by the agent on the given date0 or more | 2 |
deals_in_progress | integer | Number of deals currently in progress for the agent on the given date0 or more | 5 |
deals_closed | integer | Number of deals closed by the agent on the given date0 or more | 1 |
deals_lost | integer | Number of deals lost or withdrawn by the agent on the given date0 or more | 1 |
total_deal_value | float | Total monetary value of deals closed by the agent on the given date0 or more · optional | 350000 |
clients_contacted | integer | Number of unique clients contacted by the agent on the given date0 or more | 7 |
client_meetings | integer | Number of meetings (virtual or in-person) with clients on the given date0 or more | 2 |
follow_ups_made | integer | Number of follow-up communications (calls, emails, messages) made with clients on the given date0 or more · optional | 4 |
hours_worked | float | Total hours worked by the agent on the given date0 to 24 | 8.5 |
productive_hours | float | Number of hours spent on productive activities (deal work, client engagement, etc.) on the given date0 to 24 · optional | 7.2 |
tasks_completed | integer | Number of tasks or to-dos completed by the agent on the given date0 or more · optional | 6 |
| Dates and times 1 column | |||
date | date | Date for which the productivity metrics are recorded | 2024-06-05 |
Use it for
A real estate dashboard
Hours_
worked by attendance_ status and a breakdown of team_ name. Excel, Power BI or Tableau. Why do the 11 half_
day rows have a mean hours_ worked of 2.8? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Agents75A10018.5presentA10025presentA10039.2present
A software demo
Believable agents with agent_
name, email and team_ name to fill a screen in front of a buyer.
This dataset75 rows19 columns
Yours10,000 rows19 columnsregion: UK only
blueprint · remote-agent-productivity-metrics
Behind this dataset
Same schema. As many rows as you need.
These 75 rows came out of a blueprint — 19 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
- Each row represents one agent’s weekly summary.
- Include deal stages, number of client interactions, and scheduled virtual tours.
- Flag weeks with below-average activity for further review.
- Capture technology usage for remote collaboration (tools adopted, hours active).
- Anonymize sensitive agent identifiers; only aggregate performance data.
Open the blueprint in Data Factory
1 credit per row. New accounts start with 25 free credits.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- remote-agent-productivity-metrics