Harvest vs Toggl

• Consistently making updates to better serve their wide variety of users
• Allows for a decent amount of customization - you can put in different tasks for different departments, you can put in project costs on a one-time or recurring basis to compare time to money, etc.
• It's pretty easy to pull customizable reports to fit what data you want to look at.

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• Lightweight interface. It is very simple to start and stop tracking.
• Categorization, tags, projects, and clients. Make it easy to categorize time tracking and pull accurate reports
• Reporting: their reporting system makes it simple to slice and dice our tracked data to get precisely the intel we need.

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• We would love to see Harvest build a feature for more detailed proposals that could be signed by the client and then automatically be turned into a billable invoice. The estimate falls short of this for larger projects.
• Sending an invoice directly to the client from the Harvest dashboard can sometimes fail. Because it's coming from a spoofed email- some clients never get the invoice because it get's trapped in their spam folder.

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• When I generate a report based on a long date range (as opposed to a single day or week), Toggl provides logged time entries per project, user, or client, according to my search. Each time entry in the report is itemized and includes a description. However, the date and time per entry is not generated with this data. When I create invoices, I have to manually find what day the work was done.

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• Quick onboarding for new staff. Less time training means that the staff member can ramp up more quickly
• Low impact on productivity in daily use. Less time tracking your time, means more time on projects
• Easy to pull data, and use it for data driven decisions/estimates for future projects

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• We replaced our in-house time tracking tool easily
• We could incorporate the previous few months of tracking via CSV/Spreadsheet import
• We still don't have the full discipline to track everything for everybody. It's only as good as the data you put in.

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