57 min
Episode 59 Building an Email Calculator with Michael Einstein part 3 2Time Labs Podcast
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- Education
Ever longed for a tool that could give you feedback on the health of your email inbox? Listen in as I take on the challenge of creating one from scratch. Here in the third and final episode in this series, I continue working with Dr. Michael Einstein to create an email health calculator.
We take the lessons learned from the prior discussion and start by listing a hierarchy of concerns. They are listed here from 1-5 in rank order.
1. How many days of stored email are accumulated? (read vs unread, subscribed vs non-subscribeds)
2. How old are these message? (read vs. unread)
3. How unique are these messages? (subscribed vs non-subscribeds)
4. How fast are they entering? (incoming email)
5. How complicated are they by being threaded?
During the hiatus since the last episode, I drafted a weight for each measure and after playing with the tool we would be using, producing the following formula which we discussed in this episode.
0.25 x Left Behind Index (i.e. (Total messages in your inbox - unread messages-tagged, read messages)/incoming email each day)
0.20 x Number of Days Surprise Index (i.e. unread messages – unread subscriptions email)/incoming email each day)
0.20 x Total messages older than a day)/incoming mail each day
0.20 x (Average age of non-Subscription messages/days)
0.20 x ( .50 x Average age of Subscription messages/days)
0.10 x Incoming Email each day / messages removed per day
0.20 x Threaded messages
The final input into the calculoid app used the following weights which were simply scaled so that they would sum to 1.0:
Field 1 - 18% Left Behind Index [i.e. (Total messages in your inbox - unread messages-tagged, read messages)/incoming email each day)]
Field 2 - 14% Number of Days Surprise Index [i.e. unread messages – unread subscriptions email)/incoming email each day]
Field 3 - 14% Total messages older than a day)/incoming mail each day
Field 4 - 14% Average age of non-Subscription messages/days
Field 5 - 7% Average age of Subscription messages/days
Field 6 - 11% Max(1, incoming email/150)
Field 7 - 7% Incoming Email each day / messages removed per day
Field 8 - 14% Threaded messages x #average active participants in each thread
Want to support the work at 2Time Labs? Here's my Patreon Link. Patrons receive a number of benefits including early access and followup conversations related to work like this.
Ever longed for a tool that could give you feedback on the health of your email inbox? Listen in as I take on the challenge of creating one from scratch. Here in the third and final episode in this series, I continue working with Dr. Michael Einstein to create an email health calculator.
We take the lessons learned from the prior discussion and start by listing a hierarchy of concerns. They are listed here from 1-5 in rank order.
1. How many days of stored email are accumulated? (read vs unread, subscribed vs non-subscribeds)
2. How old are these message? (read vs. unread)
3. How unique are these messages? (subscribed vs non-subscribeds)
4. How fast are they entering? (incoming email)
5. How complicated are they by being threaded?
During the hiatus since the last episode, I drafted a weight for each measure and after playing with the tool we would be using, producing the following formula which we discussed in this episode.
0.25 x Left Behind Index (i.e. (Total messages in your inbox - unread messages-tagged, read messages)/incoming email each day)
0.20 x Number of Days Surprise Index (i.e. unread messages – unread subscriptions email)/incoming email each day)
0.20 x Total messages older than a day)/incoming mail each day
0.20 x (Average age of non-Subscription messages/days)
0.20 x ( .50 x Average age of Subscription messages/days)
0.10 x Incoming Email each day / messages removed per day
0.20 x Threaded messages
The final input into the calculoid app used the following weights which were simply scaled so that they would sum to 1.0:
Field 1 - 18% Left Behind Index [i.e. (Total messages in your inbox - unread messages-tagged, read messages)/incoming email each day)]
Field 2 - 14% Number of Days Surprise Index [i.e. unread messages – unread subscriptions email)/incoming email each day]
Field 3 - 14% Total messages older than a day)/incoming mail each day
Field 4 - 14% Average age of non-Subscription messages/days
Field 5 - 7% Average age of Subscription messages/days
Field 6 - 11% Max(1, incoming email/150)
Field 7 - 7% Incoming Email each day / messages removed per day
Field 8 - 14% Threaded messages x #average active participants in each thread
Want to support the work at 2Time Labs? Here's my Patreon Link. Patrons receive a number of benefits including early access and followup conversations related to work like this.
57 min