Email Productivity Benchmark Report (November 2020)

Welcome to the first-ever Email Productivity Benchmark Report!

This is a new monthly report that I’ll be releasing every month to analyze typical email statistics across a random sample of EmailAnalytics customers to answer questions about how people interact with email on daily basis.

You can use this data to benchmark your own team’s performance and activity. Set up your own EmailAnalytics account to see how your stats measure up. Let’s get to it!

Methodology

• This data comes from 511 EmailAnalytics customers — both paying and trial users. All data has been aggregated and anonymized.
• All @gmail.com email addresses were removed from the data, so that we are only looking at Google Workspace users (ie, professionals).
• All data is localized to the each user’s timezone.
• About 41% of the data is from US-based customers. Here’s the geographic breakdown:

Terms & Definitions

You need to be familiar with some terminology we use here at EmailAnalytics to fully understand the data.

• Average response time (actual): The actual time it takes to reply to an email.
• Average response time (work hours): The amount of elapsed time within work hours to respond to an email. Work hours are set individually by EmailAnalytics customers, and are, by default, set to 8am to 5pm.
• Average response time (received, actual): The actual time it takes to receive replies to emails. We do not measure “work hours” response time for received responses, because work hours among participants often vary across time zones.

How do we calculate email response time?

We have a few rules for how we count email response time:

• Only emails that receive a response are counted in the average. We do not count emails that do not receive a response.
• We do not count responses that occur after longer than 14 days.

How we calculate response time for a single day:

Many emails are not responded to until the next day, or several days later. So, we calculate average response time for a single day as the average amount of time it takes to respond to an email received on that day.

Example:

You received exactly one email on April 1st at 10am, and later responded to it on April 3rd at 10am. Your email response time for April 1st is 48 hours, even though that is longer than a single day. Thus, your response time for a single day can be longer than a single day.

In other words, your average email response time for April 1st the average of all your responses that you sent in response to emails you received on April 1st.

Executive Summary (Statistics Summary)

Including weekends & holidays

This set of statistics covers ALL of November 2020, including weekends and holidays.

• The average person received 93.3 emails per day, including spam
• The average person received 1.6 spam emails per day
• The average person sent 36.1 emails per day
• 4.7 (13%) of those sent emails were in response to a received email
• 7.4 (8%) of all non-spam emails received were responses
• Average response time (actual): 11h 48m 52s 
• Average response time (work hours): 4h 49m 57s
• Average time to receive a response (actual): 15h 28m 49s
• EmailAnalytics users’ email response time is 23.68% faster than non-EmailAnalytics users’ response time.
• EmailAnalytics users respond, on average, 3h 39m 56s faster than non-EmailAnalytics users.

Excluding weekends & holidays

If we exclude weekends and holidays, we get a clearer picture of what a true workday looks like. All weekends, and the following holidays have been excluded from this dataset:

Thursday, November 26 (Thanksgiving)
Friday, November 27 (Black Friday)

• The average person received 123.2 emails per day, including spam
• The average person received 2.0 spam emails per day
• The average person sent 48.7 emails per day
• 4.4 (9%) of those sent emails were in response to a received email
• 6.9 (5.69%) of all non-spam emails received were responses
• Average response time (actual): 6h 33m 28s  
• Average response time (work hours): 2h 6m 58s
• Average time to receive a response (actual): 7h 30m 46s
• EmailAnalytics users’ email response time was 12.71% faster than non-EmailAnalytics users’ response time.
• EmailAnalytics users responded, on average, 57m 18s faster than non-EmailAnalytics users.

Holiday observations

What if we look at holidays only? We are only looking at US holidays, and US users comprise about 41% of our total pool, so the observations here will likely be stunted, but they paint an interesting picture nonetheless:

November 26 (Thanksgiving): 

• The average person received 65.2 emails, not including spam
• The average person sent 24.7 emails
• Average response time (actual): 14h 55m 58s  
• Average response time (work hours): 4h 37m 08s
• Average time to receive a response (actual): 16h 38m 22s

November 27 (Black Friday): 

• The average person received 87.6 emails, not including spam
• The average person sent 32.4 emails
• Average response time (actual): 17h 11m 04s  
• Average response time (work hours): 3h 38m 48s
• Average time to receive a response (actual): 20h 12m 13s

Part I: Emails sent & received

Most email activity occurs on Mondays, with a slow drop-off of activity throughout the week. As expected, Saturdays and Sundays have a significant drop-off of activity:

	Avg. Sent	Avg. Received	Response time (wh)	Response time (actual)	Response time (received, actual)
Sunday	9.1	29.7	7:27:52	10:38:48	17:24:59
Monday	49.8	130.9	3:11:42	8:02:57	9:29:00
Tuesday	47.9	125.6	3:32:45	9:26:11	10:20:28
Wednesday	48.4	121.1	3:34:40	10:30:07	12:00:00
Thursday	43.3	107.5	3:22:36	11:10:03	12:43:21
Friday	43.2	104.7	3:11:37	15:13:42	17:52:08
Saturday	10.3	30.8	8:52:39	18:02:25	28:26:57

 

Here’s a chart that shows average email activity by day, for each day in November 2020, excluding spam:

You can see the clear drop-off in email traffic for Thanksgiving (November 26) and Black Friday (November 27) which most Americans take off as holidays.

And here’s what spam emails look like over the course of November 2020:

Part II: Email Response Time

Response time shows an interesting pattern. If we only record responses within work hours, then every day of the work week actually shows pretty similar response times. But if we look at it from an “actual” perspective (ie, the amount of actual time elapsed between receipt of an email and responding to it), then responses take longer as the week goes on.

Here’s the average email response time by day:

Again, we see the clear pattern of Mondays being the best day for response times, with a gradual increasing slowness as the week progresses.

Closing Thoughts

So, what wisdom can we draw from this data?

1. If you want a fast email response, send your email on a Monday.

Mondays have the fastest response time for both recipients and senders. As the week goes on, response times get slower.

2. …But if you want a thorough, detailed response, maybe pick a Friday.

People are dealing with the most email activity on Mondays. As such, they might be more likely to send a reply quickly so they can move on to the next email in their inbox. Fridays have the slowest email response time, but also the lowest email volume of the workday. So your recipient is more likely to have more time to respond to your email if you send it on a Friday.

3. If you want to improve your email response time (or your team’s), monitor it.

The Hawthorne effect has shown that simply knowing you’re being monitored — even if you’re the one monitoring yourself — causes your behavior to change. If you monitor your email response time, it’s likely to improve. EmailAnalytics customers respond to emails significantly faster (about 24%)  than non-EmailAnalytics customers, and that is likely at least partially due to the Hawthorne effect.

You can use this data to benchmark your own performance (or your team’s) in EmailAnalytics. Start a free trial and get instant access to your own email stats — no credit card required, and no software to install.

How do your stats measure up to these benchmarks?