Spark vs Skiff

Spark has optimized for more focus, although there are still some UI elements that are cluttered, like in their compose screen there are too many buttons.

Spark's emails also stretch way across the screen causing fatigue when reading, while the other platforms format emails to be more narrow to help with readability.

Spark tries to simplify triage by auto-sorting your inbox into categories like Newsletter and Notifications but you cannot customize it further so most of your mail appears in the main inbox as one big pile to get through, which is where it loses points.

Spark was built to be used with a keyboard, you can hit CMD+K to go anywhere. With Spark you can fully navigate snooze and send later features without a mouse but it doesn't support natural language and this is where it got a bit clunky as if you want to snooze on a custom date, you need to count the exact days into the future rather than being able to type it in.

If you want to reply in line, the process is that you need to copy the entire email, format it, and then use their quoting feature and then write your reply. This is tedious.

Spark has templates, and you can access them via your keyboard using the shortcut Cmd + Shift + T, and it has placeholder functionality. You can also save any To, CC, and BCC fields to your template turning them into a bit of a workflow.

Sparks offline mode is good, it doesn't need to be enabled although it only caches recent emails and users complain its quite slow.

Spark automatically categorizes your emails just based on notifications and newsletters, but you can't set up custom auto-labels.

Spark also doesn't have AI search, but they do have pre-defined AI summaries. You can ask AI to summarize an email, or translate it...but you can't ask it any specific questions about your inbox or emails. Summaries aren't really efficient in our experience, especially when you can't go deeper and ask your own questions about the context.

In terms of AI drafts, the email started to sound a bit more like me. That's because Spark has a feature where it will scan 3 of your emails and learn a bit about the tone you typically write in. While this is better, it's still limited. That's why it doesn't score very high as an AI email assistant.

Spark supports read receipts on the paid tier only. Spark does not have any features that help with follow-up.

Spark allows for team comments and sharing drafts allowing team members to collaborate on emails in real-time. You can also assign emails to team members so they know they are responsible for responding. If you want to share an email with a non-team member, Spark allows you to generate a link to share emails and comments externally. However, external team members can't jump in and leave a comment themselves, so this is more to bring them up to speed on a conversation.

You can assign emails to team members in Spark, which is a great way to indicate that they are responsible for taking over.