Logan McCaul

1.3% of my Slack messages include the word "sorry"

One day a coworker asked for advice on how to tell a more junior engineer that they don't need to say sorry for asking questions. After sharing some guidance a different question emerged: can we quantify how often we use "sorry" on Slack?

There are a few different ways you could analyze your Slack messages. There's a Slack analytics dashboard that can give you high level insights into organizational communication. You could also export all Slack messages (or a specific user's Slack messages) from your workspace and then analyze it using some form of text mining. You could create a Slack bot that listens for message events and keeps a count for specific words. In my case my company has restricted access to the analytics dashboard and I didn't want to make a business case on why I needed an export of all Slack messages. So instead, I used the simplest tool available, Slack's search.

You can make a simple Slack search for all of your messages to get a total count. Screenshot of a slack search for 'from: @Logan McCaul'

In my case, Slack found roughly 31,000 total messages. It's important to note this count will depend on your workspace's retention policy. At my company direct messages persist indefinitely and channel conversations are deleted after 1 year, so I've technically sent more than 31,000 messages, but we're looking for directional data anyway.

Adding a keyword then gives you a subset of those messages. For example a query for from:@Logan McCaul sorry returns only messages that contain the word "sorry". For smaller words you may need to use "" for specificity. Screenshot of a slack search for 'from: @Logan McCaul sorry'

Slack search returned 413 messages that included sorry. Meaning about 1.3% of my Slack messages include the word "sorry". Among coworkers this became known as your sorry ratio. 1.3% ended up being on the higher end with most folks hovering between 0.3% - 0.7%.

So, what does a 1.3% sorry ratio say about my communication style? I don't know. That's probably something for me to reflect on by looking at the actual context of the messages. That's a good topic for a future article. Instead, I looked up other common words to discover quirks in my communication style.

For example, I found that I use a variety of affirmative words such as "yes" (1.4%), "yup" (0.8%), and "yeah" (2.6%) in my messages. I use "no" (5.6%) slightly more in my messages, "no" isn't always negative though, "no worries" (0.7%) seems to be a go to of mine. I don't use a lot of other negative words besides "no", both "nah" and "nope" are less than 0.1%.

I tend to spell out "I don't know" (2.4%) instead of "idk" (0.1%).

I ask "what" (6.0%) twice as often as the other five w's: "where" (1.9%), "why" (2.7%), "when" (2.8%), and "who" (1.3%).

3.9% of my messages include either "thanks" or "thank you". I captured both in a single search for "thank" (3.9%).

I use "engineer" (6.1%) more often than "design" (4.5%) or "product" (3.4%) and I've bought into my company's specific terminology by using "customer" (2.8%) more often than "user" (1.6%).

I use "lol" (1.4%) and "haha" (1.0%) almost equally. 2.4% of my messages include laughter, which seems low, but I also enjoy the unaccounted for 😂 as a reaction.

I refer to myself in 45.2% of my messages with "I" (38.7%) and "me" (6.5%) and only include "you" (24.3%) in almost half as few messages.

At least 24.5% of my messages don't include closing punctuation, such as "." (29.7%), "?" (25.2%), "!" (20.6%). There could be overlap in the messages that use ".", "?", or "!" so the number of messages where I don't use any closing punctuation could actually be higher.

There's maybe some lessons mixed in here, or maybe it's just fun to put some stats to one of my most common actions at work. Either way, here's a full list of keywords I tested.

Word Messages Ratio
I 12,000 38.7%
. 9,229 29.7%
? 7,893 25.2%
you 7,535 24.3%
! 6,386 20.6%
me 2,005 6.5%
engineer 1,907 6.1%
what 1,863 6.0%
no 1,749 5.6%
😄 1,726 5.6%
good 1,660 5.3%
hey 1,630 5.3%
design 1,399 4.5%
thank 1,214 3.9%
product 1,044 3.4%
when 888 2.8%
customer 862 2.8%
why 827 2.7%
yeah 807 2.6%
oh 809 2.6%
don't know 744 2.4%
🙂 744 2.4%
😅 693 2.2%
where 600 1.9%
user 491 1.6%
yes 443 1.4%
lol 420 1.4%
sorry 413 1.3%
who 401 1.3%
data 342 1.1%
hi 324 1.0%
analytics 323 1.0%
haha 310 1.0%
yup 245 0.8%
no worries 221 0.7%
🎉 191 0.6%
sounds good 128 0.4%
👋 82 0.3%
hello 53 0.2%
idk 44 0.1%
howdy 22 0.1%