Why this matters
Once you’ve run a comparables search and identified the right results, exporting is your next step. You’ll want to get the data into a format that you can analyze, share with stakeholders or print for client presentations. This process ensures you’re leveraging your search results effectively.
What you’ll do
- Select the comparable records you want to export.
- Choose the export format that fits your use-case (raw data vs presentation).
- Download the file and integrate into your workflow (spreadsheet, CRM, print).
Select Comparable Properties
- After running your comparables search, review the list of results.
- Use the check-boxes to select the specific properties you want - or click “Select All” if you want the full set.
Choose Export Format
- Click the green Export button.
- In the export window, select among available formats:
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- Excel (.xlsx) - Ideal for raw data analysis and manipulation.
- CSV - Useful for importing into CRMs or other systems.
- PDF - Best for printable reports or client-facing materials.
- Total - (If applicable) for integration with specific appraisal software.
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- Tip: If your goal is presentation or sharing, choose PDF. If you’re doing modeling, valuation or further filtering, pick Excel or CSV.
Download & Use the File
- Confirm your format choice and initiate the download.
- Save the file in your project folder (e.g., Comps_Q4_2025_BuildingXYZ.xlsx).
- Open in the relevant application (Excel, Google Sheets, CRM) and proceed with your next steps: analysis, sharing, modeling, or printing.
Pro-Tips
- Name downloads clearly so you can retrieve them later (e.g., include property name, date, export type).
- Keep track of your export format choice: raw data exports allow deeper insights; PDF exports are cleaner for client-facing use.
- Store export files in a structured system (by campaign, property, or time period) so you build a library of comparable sets.
- If you anticipate needing updates (e.g., new sales coming in), decide if you’ll re-run search and export again rather than relying on stale data.
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