A proven cold email framework for getting executives attention in your enterprise accounts
And 3 real life examples.
Read time: 3 min
How can you make your cold emails stand out from the noise and genuinely engage C-level executives?
In a recent episode of the SDR Game podcast, I sat down with Krysten Conner, Sales Strategist at Usergems, on the SDR Game podcast, and something she shared around the 33-min mark caught my attention.
She shared a cold email framework for breaking through the noise and getting executives’ attention.
Now, why is this framework a game-changer?
It shows a deep, personalized understanding of the prospect's business, a quality often missing in the sea of generic emails executives receive daily.
I’ve personally put this framework to use at Castor, and will show you 3 ways I use it.
If you're interested in the full conversation, you can check out the episode here: Spotify, Apple Podcasts, or watch the interview on YouTube here.
Krysten's Cold Email Framework: Do the Maths
The framework follows this structure:
What you know about them
How you help
Do the maths
Call to Action
Here’s an example email following this approach:
Hey {{First name}} - saw that {{Prospect company}} has around 15,000 clients.
We help turn champion job changes into repeat business and find relevant buyers in your accounts.
Given a 20% job change rate and 4 people per buying committee, {{Prospect company}} could have ~12,000 past buyers ready to buy again.
Interested to learn more about this?
Here's an example of this framework in action:
And here’s a longer version (the one shared on the podcast) suitable for later in a cadence:
Hey {{Prospect name}} -
Noticed a number of your partners are our clients. Greenhouse stood out. Would love to show you how they are making the 'second sale' when their champions and users change jobs.
They're making investors happy because of the pipeline and revenue created.
We do 2 things: turn champion job-changes into repeat business and automatically surface all relevant buyers into your target accounts.
{{Prospect company}} would probably have ~12,000 past buyers who could buy again. Back of napkin math below.
15,000 {Prospect company} clients
x 4 Avg People on buying committee
x 20% job change rate (Bureau of Labor stat)
----------------------------------
12,000 potential leads (not counting influencers, power users, admins)
p.s. fun fact One of your partners who's 1/4 your size is seeing $4.1m in revenue in under 12mos.
Cheers!
Let me share 3 examples, showing how I've applied this approach at Castor:
Cut down time looking for data
Save money on data warehouse expenses
Onboarding
Cut down time looking for data
Subject line: data discovery time
Hello {{First Name}}, saw you've got over {{Size of the data team}}.
Our data catalog can cut down the time your team spends searching for data from 8h to 1h.
Imagine each person on your team spends about 8 hours finding data for each project, and they do 20 projects a year. If each person is making $120k a year, that's $12k spent on just finding data.
This time could be cut down from 160h to just 20h per person each year. That could mean {{Do the maths}} saved for your team.
Interested to learn more about this?
Let's use a team of 60 data people as an example.
Subject line: data discovery time
Hello Elric, saw you've got over 60 people on your data team.
Our data catalog can cut down the time your team spends searching for data from 8h to 1h.
Imagine each person on your team spends about 8h finding data for each project, and they do 20 projects a year. If each person is making $120k a year, that's $12k spent on just finding data.
This time could be cut down from 160h to just 20h per person each year. This could save your team around $630k.
Interested to learn more about this?
Save money on data warehouse expenses
Subject line: {{Name of their data warehouse}}
Hello {{FIRST NAME}} - it looks like you are using {{data warehouse}}.
Our data catalog can help you cut down your data warehouse costs by up to 17%, by identifing unsused, and duplicate assets.
Imagine you have about 50,000 tables, each 90 GB in size, and it costs you $0.24 for each GB every year. This means your yearly cost for using {{data warehouse}} is about $1.08 million USD.
You could bring that down to around $896,000. That means you could save $184,000!
Would love to get your feedback on our tool, do you have time next week?
Real example with Snowflake:
Subject line: Snowflake
Hello Elric - it looks like you are using Snowflake.
Our data catalog can help you cut down your data warehouse costs by up to 17%, by identifing unsused, and duplicate assets.
Imagine you have about 50,000 tables, each 90 GB in size, and it costs you $0.24 for each GB every year. This means your yearly cost for using Snowflake is about $1.08 million USD.
You could bring that down to around $896,000. That means you could save $184,000!
Would love to get your feedback on our tool, do you have time next week?
Onboarding
Subject line: ramping data analysts
Hello {{FIRST NAME}} - saw you are hiring {{number of team members}}.
We are helping data leaders reduce their onboarding time from 17 days to 2 days wiht our data catalog.
With an average salary of $120k per year per data employee.
This would mean going from $12k to $1.2k per employee onboarding, resulting in $194k saved for the {{number of team members}}.
Interested to learn more about this?
Here’s an example for 18 hires:
Subject line: ramping data analysts
Hello Elric - saw you are hiring 18 data analysts.
We are helping data leaders reduce their onboarding time from 17 days to 2 days wiht our data catalog.
With an average salary of $120k per year per data employee.
This would mean going from $12k to $1.2k per employee onboarding, resulting in $194k saved for those 18 data analysts.
Interested to learn more about this?
True power comes from doing.
The more you make your email about the person you're writing to, the better their reply will be.
So, go for it, 'Do the Maths' and take your cold email skills to a new level!
Have you given this method a go?
I'd really like to hear what happened and see any examples you might have.
That's all for this Sunday.
Quick Reminder: If you like my emails please do “add to address book” or reply.
See you next week.
Happy prospecting ✌️
Elric
PS: Here're the 3 last issues if you miss them:
If you want to read the previous ones, here's the link.