top of page

Resonance and the Non-Technical Power of Formulas

For all the wants and needs of the modern day cold emailer, the heart of outbound success can still be summed up by the term resonance.


The tangible definition of resonance being:


That when someone reads your email, it strikes them in a way that holds their attention and induces action.


There are a multitude of ways in which to arrest a prospect’s gaze, from calling out a relevant trigger, to maybe even using humor. 


And sure enough, the best of us will use them all in various forms and tests (not in the same email, mind you). 


One of the strategies that can help you incite this interest is to make sure that your email feels like it was sent to them, and not to a ‘list’.


For the non-technical Founder or CEO who wants to get a gauge on why they should use Clay, (and who does not have the time to become an expert level cold email data connoisseur) this is the answer.


Formulas & Clay


Arguably the quickest way to inject resonance-builders into your email is through relevance. This means parsing out data that is relevant to either the lead or account you are reaching out to, so that when they read the email they find that actually, it is indeed meant for them and them alone.


Clay Formulas are perhaps the best way to do this.


BONUS - they are instant (no wait time) and completely free. 


What are formulas?


Formulas are statements of logic that you can use to manipulate rows of data at scale.


Here’s an example formula:


‘If COLUMN A has the word ‘design’ in it, write ‘relevant’.’


Here’s what that statement will do:


Let’s say COLUMN A contains the job titles of your prospect list. Let’s say you only want to reach out to people with ‘design’ in their title.


That statement will put a ‘relevant’ in a new column next to the job title column (COLUMN A) - so in a list of 360 or 36,000, you can now filter for ‘relevant’ in the new column, and find everyone you need in 2 clicks.


Going Deeper


That was nice. But we can do better.


Now let’s say that you are a developer with a list of open jobs and their vacancy descriptions at companies you want to help.


And now, you want to say something that connects each specific job vacancy to what you can help with.


Here’s an example Clay formula:


“If JOB DESCRIPTION COLUMN contains ‘Azure’, write ‘Azure’


If JOB DESCRIPTION COLUMN contains ‘Python’, write ‘Python’




If JOB DESCRIPTION COLUMN contains ‘Fivetran’, write ‘various tools’”


Okay, so let’s break this formula down.


Every single job description that talks about Azure will now have that specific variable in a new column (e.g. ‘Azure’) - same for ‘Python’, and ‘SQL’. With ‘Fivetran’, we wrote ‘various tools’, because in this fictional example you know that you can’t help with Fivetran so you instead want to insert something more generic but that will make sense (this of course is a strategic decision for the sake of the example, which you may decide not to do).


That means you can now call the new column something like ‘Specialism’ and write an email that starts like this:


“Hey {first name}


I saw you’re looking for a {job vacancy title}, with a specialty in {specialism}...”


Immediately, the specific data you’ve parsed out allows you to write an email that, at scale to thousands of leads, is going to be hyper-relevant to each one of them.


Like it was just meant for them.

Layering Relevance


That was also nice. Here’s a final example.


Let’s say you have a list with 4 different types of companies - banks, marketing agencies, law firms, and web designers. You want prospects at those companies to get different social proofs statements in your email, depending on which industry they’re in.


Here’s a formula you can use:


“If INDUSTRY COLUMN contains ‘bank’, write ‘We helped banks like COMPANY NAME COLUMN do blah blah blah’


If INDUSTRY COLUMN contains ‘law’, write ‘We helped law firms like COMPANY NAME COLUMN do blah blah blah’


If INDUSTRY COLUMN contains ‘marketing’, write ‘We helped marketing firms like COMPANY NAME COLUMN do blah blah blah’


If INDUSTRY COLUMN contains ‘web design’, write ‘We helped web designers like COMPANY NAME COLUMN do blah blah blah’”


Okay so here, we’ve now used the formula to do 2 things.


  1. Every single prospect will only be shown social proof that is relevant to their industry


  1. But, we’ve also added the specific company name in the formula (simply by referencing the column with the company name) that each prospect works at inside the social proof; inside the relevant industry.


So now, someone at a marketing agency will get an email that includes social proof which hyper-relevant to their industry and also references companies like their specific brand.


Double relevance, double choc chip.


As you can see, the ability to develop hyper relevant variables using simple logical statements is endless.

Tips and Language


Formulas use AI to generate outputs based on your inputs. Here are a few tips when deploying them:


  1. Make sure your statements are logical


E.g. ‘If X contains Y, write Z’ - logical.


E.g. ‘If you think X might be a related to V, write a few lines about Z’ - NOT logical


  1. Following on from 1, keep your instructions simple. The overall formula can be long, but it should be broken up into short simple sentences.


  1. Consider using formulaic language like ‘contains’, ‘equals’, ‘greater than’, ‘less than’, for it to understand the instruction easily. 


Contains means that the word you write is somewhere in the value. I.e. Banking Firms, contains ‘bank’


Equals means it must be the exact same (including grammar) as the value. I.e. John’s Taverns does NOT equal Johns Taverns or Johns taverns. It only equals John’s Taverns. It is identical, essentially.


The key to using formulas is that the possibilities are endless. Be creative but clear and logical in your instruction, and you can turn a mass of jumbled data into a stream of hyper-relevant emails that bring about the kind of resonance that leads to meetings with your ideal clients.
bottom of page