High Response Rate Cold Email Campaign for Cyber SaaS Partnerships

Muzafar C. · 2025-01-30T21:53:19.469Z

Old one but a good one that I've not shared before. Probably my highest response rate campaign ever. Very small numbers - super personalised and tailored targeting MSSP partnerships for a cyber SaaS company. 24% response rate average - and 10% booking rate to meetings. This was enriched in Clay + some custom scripts and human validation in sheets then run out of Apollo with custom fields. The client had previously run cold email en-masse and had a response rate of less than 0.1%. The campaign had to get paused multiple times as a new team was built around this.

12 comments

· Sorted by Oldest

OU
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Could you share more about what went into the campaign design?
Muzafar C.
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Its pretty difficult to find MSSPs - there's no company category or SIC code. So the first step was a massive SERP scrape, then enrich. The next was to verify that they were in fact a MSSP - custom script to crawl and check the site (google apps script in sheets) Next - claygent to pull "focus area" of the MSSP - e.g. public sector, healthcare, legal etc For contacts - finding the most senior with the right persona. Enriching their city and the company HQ city. The offer had to get worked to be of value to them. In this case the client had a lot of low quality/smb enquiries that they didn't have the bandwidth for. The assumption was that the MSSP would be interested. So instead of framing it as a partnership, the framing was needing help with serving a <match enquiry location with either contact/hq location> <match focus area> SMB - and if interested maybe there could be a partnership. Extensive cleanup and validation before running. Very short, sweet and human. Sent from a c-suite contact matching the persona of the recipient so its peer-to-peer with colloquial language.
Daniel K.
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Nice! Is that the apollo sequencer?
💯1
Georgi B.
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Can you explain more about the Google apps script part? You wrote a script that crawls the website in order to just verify whether the company is MSSP, do I get that right?
Muzafar C.
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Daniel K. yep - was run in Apollo
Muzafar C.
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Georgi B. yep, it would have been insane on credits to check all the results - so used google sheets to fetch pages and match keywords - to quickly prune down the list
Joe S.
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That is awesome - interesting use case of google scripts to use the free script to save on credits. Love that as a use case, gonna have to try that
Georgi B.
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Indeed, as the MSPs have very specific keywords to detect. Smart move!
Joe S.
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are there any other use cases you’ve found that google scripts is better, or more cost saving to utilizing instead of a claygent. Of course it has it’s place and time, just curious if you have any other specific cases it’s worked well for!?
Muzafar C.
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Anytime you're doing something simple that can be determined from a homepage / have a very large dataset - much better. I typically just have chatgpt write the appscript (not a developer) and iterate till it does what I need. For this project I had 3 functions - fetch page/check if MSP/MSSP by keyword. For undeterminable, I had Groc/llama3 check. Also did a contact pull with Apollo with a batch delay due to api limitations (clay doesn't do this at the mo). Used clay to fill the gaps. Dataset was huge. Doing all of this in clay would've cost probably a couple hundred thousand credits.
Muzafar C.
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here's a quick sheets script if you want to play with ai in google sheets for small bits and bobs. Just needs a free key from https://console.groq.com/playground usage: =ai("prompt",CELL,"prompt") etc. Has its limitations but a fun little exercise.
❤️2
Muzafar C.
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the above runs into rate limits, so a neat way to learn is to feed the script to gpt + ask to add batch functionality etc

High Response Rate Cold Email Campaign for Cyber SaaS Partnerships | Clay

OU
·
·
Could you share more about what went into the campaign design?
Muzafar C.
·
·
Its pretty difficult to find MSSPs - there's no company category or SIC code. So the first step was a massive SERP scrape, then enrich. The next was to verify that they were in fact a MSSP - custom script to crawl and check the site (google apps script in sheets) Next - claygent to pull "focus area" of the MSSP - e.g. public sector, healthcare, legal etc For contacts - finding the most senior with the right persona. Enriching their city and the company HQ city. The offer had to get worked to be of value to them. In this case the client had a lot of low quality/smb enquiries that they didn't have the bandwidth for. The assumption was that the MSSP would be interested. So instead of framing it as a partnership, the framing was needing help with serving a <match enquiry location with either contact/hq location> <match focus area> SMB - and if interested maybe there could be a partnership. Extensive cleanup and validation before running. Very short, sweet and human. Sent from a c-suite contact matching the persona of the recipient so its peer-to-peer with colloquial language.
Daniel K.
·
·
Nice! Is that the apollo sequencer?
💯1
Georgi B.
·
·
Can you explain more about the Google apps script part? You wrote a script that crawls the website in order to just verify whether the company is MSSP, do I get that right?
Muzafar C.
·
·
Daniel K. yep - was run in Apollo
Muzafar C.
·
·
Georgi B. yep, it would have been insane on credits to check all the results - so used google sheets to fetch pages and match keywords - to quickly prune down the list
Joe S.
·
·
That is awesome - interesting use case of google scripts to use the free script to save on credits. Love that as a use case, gonna have to try that
Georgi B.
·
·
Indeed, as the MSPs have very specific keywords to detect. Smart move!
Joe S.
·
·
are there any other use cases you’ve found that google scripts is better, or more cost saving to utilizing instead of a claygent. Of course it has it’s place and time, just curious if you have any other specific cases it’s worked well for!?
Muzafar C.
·
·
Anytime you're doing something simple that can be determined from a homepage / have a very large dataset - much better. I typically just have chatgpt write the appscript (not a developer) and iterate till it does what I need. For this project I had 3 functions - fetch page/check if MSP/MSSP by keyword. For undeterminable, I had Groc/llama3 check. Also did a contact pull with Apollo with a batch delay due to api limitations (clay doesn't do this at the mo). Used clay to fill the gaps. Dataset was huge. Doing all of this in clay would've cost probably a couple hundred thousand credits.
Muzafar C.
·
·
here's a quick sheets script if you want to play with ai in google sheets for small bits and bobs. Just needs a free key from https://console.groq.com/playground usage: =ai("prompt",CELL,"prompt") etc. Has its limitations but a fun little exercise.
❤️2
Muzafar C.
·
·
the above runs into rate limits, so a neat way to learn is to feed the script to gpt + ask to add batch functionality etc