Streamlining Your Job Application Process with Clay

What is going on everybody? It is Patrick from Clay here back with another banger. This post is about jobs. We all likely either need one or have one. This content is for people that are looking to get a new one. We're going to use Clay to streamline the job application process and get to decision makers a little quicker than the Fort Knox that is LinkedIn jobs. We're taking matters into our own hands here and importing LinkedIn jobs into Clay, finding the main decision makers' emails, and reaching out to them ourselves, ideally circumventing the application process.

There are, of course, other ways to do this, but this is one that I prefer because it helps you stand out as a candidate for jobs you might be applying for. So without further ado, let's get into it.

Finding Jobs

The first move we're going to make is go to new table, and hover right over to find jobs from LinkedIn. For this example, I was thinking we do something along the lines of marketing manager. That is probably a job I would be applying to if I wasn't already chained to the shackles of Clay. Just kidding, guys. I like my job. Ideally, I'd like to get a job that isn't an internship, so we'll exclude the words 'intern,' and we'll leave it at that. I don't want to work anywhere outside of New York, so I'm going to narrow it down to New York City and limit my results to one hundred.

Enriching Jobs

Once we have our jobs imported into the table, the first thing we're going to do is find contacts at the company. You can easily do it using Clay.

Now once you have contacts from the company, how are we going to vet through them programmatically and figure out which ones are the best for us to contact? Luckily, we have an awesome OpenAI integration to help with that.

Using OpenAI to Identify Key Contacts

I wrote a prompt: "I'm trying to figure out which employees at a company are most likely to be in charge of job applications. I'm going to give you a list of names. Give me the most likely person to be in charge of vetting and job applications and hiring new employees in the marketing department." I inputted all the names from the results, and it formatted the output as just a name and job title, which is important for the next step.

We got responses like cofounder and head of marketing, recruiter, and head of strategy of marketing. These are the people we want to reach out to. After that, I decided to use a formula to isolate the name to prepare for the next integration.

Finding Validated Work Emails

Next, I ran what we call a waterfall integration, which means we're using several different data providers to find the same data point—in this case, a work email. This allows us to get better data accuracy. If we only used one provider, we wouldn't have all the emails we wanted.

So, I went to enrich data, waterfall, work email, and input the full name and company domain. It runs all these integrations at once for you. If PropsVio finds it first, it won't run the others, saving credits and finding the highest accuracy possible. As you can see here, we have validated work emails for several prospects.

Personalizing Your Outreach

Now we have the emails for the prospects, but we don't have any personalization included in our email. It would just be generic. My thought process here was that for personalization, we should focus on the company mission. Companies want people who rally behind their mission and are willing to put in the work.

I decided to enrich the company, get their description, and plug it into an OpenAI prompt, then integrate that result into my email. This makes it seem like I did my research, and I hope the decision maker finds it valuable.

All I had to do was run our enriched company integration with the company LinkedIn URL, and it outputs a ton of information. What we're looking for is the company description. Once I got that, I used our OpenAI integration to create a personalization. My prompt was: "Using the company description, tell me one thing that company name likely does very well for their customers. Format your answer as an action."

After running this, I got great outputs that are successful and accurate. I edited them for format, removing punctuation and normalizing the company name, so it didn't seem robotic.

Writing the Email

Now, let's get into writing the email. I created a campaign called job finder and imported our leads via CSV. I mapped out the variables I needed in the email: job title, normalized company name, prospect's first name, validated work email, and personalization.

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Here's the email copy I wrote:

Hey {(firstName}},

Was scrolling Linkedin and noticed that y'all might be looking for some help in the marketing department.

I'm a huge fan of ((companyName)}. You've have proven to be some of the best at {{Edited Output}}. Would love to throw my hat in the ring.

A quick background:

• Grew an iOS app to 250,000+ users via organic marketing

• Headed socials at Clay.com and have doubled most of their social media growth metrics within a month

• Ranked 49th in Brooklyn in Tetris

Open to a call sometime this week to talk about the position?

Patrick Spychalski

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This email feels naturally written and seems like I could have possibly written it myself. After that, it comes down to running the campaign and sending out emails, hoping for some positive responses.

Final Thoughts

I hope this process was valuable to you guys. It's a great way to apply for jobs without filling out each application individually. Some may be annoyed by the direct email, but others will be impressed by the initiative you took. Even if they think it's automated, it's a pretty good automated email.

If it’s a marketing position, ideally, they still hire you. Feel free to reach out to me on LinkedIn if you have any questions, and I hope this brings you inspiration for your future job prospecting activities. Happy applying!