What Makes a Good Resume? One That Gets You to the Next Round: How to Tailor Your Resume to the Job Description

Why this topic matters

The first hurdle in a job search is usually your resume. But ask a hundred people how to write one and you’ll get a thousand answers. Which one should you follow? The Data-Driven Job Search view is simple: a good resume is one that gets you to the next round. In other words, any resume that gets you a positive response is a good one. This article shows how to tailor your resume to the job description so it does exactly that.

What usually happens

“Put your experience first.” “Leave out anything unrelated.” “Career changers should lead with education and skills.” “Put achievements related to that country at the top.” “Include your age so they know you have lots of potential.” “Don’t list your nationality…”

Whenever resumes come up, everyone has their own tricks and their own context, so you end up with a pile of different advice. I believe each person is offering what they think fits, based on their own experience. The challenge is:

Which one is right?

Before getting into that, let’s look at what a resume does at each stage. Going back to the key numbers, a resume mainly affects:

• Applications (volume): A good resume can help you apply with more confidence, but it can also have you constantly spending time tailoring it. So its effect at this stage cuts both ways.
• Positive response rate: A good resume really can get you positive responses. Both the ATS and recruiters lean heavily on your resume here, so this is where it matters most.
• Interview rate: Can a resume get you an interview? Sometimes, but not often, unless your experience is such a strong match that you skip straight to interviews. For most people, the interview rate measures how many positive responses turn into interviews, and that depends more on other qualifications (visa, years of experience and so on).
• Offer rate: Can a resume get you an offer? I’ve seen a few such cases online, but for most people the odds are tiny. However good your resume is, you still have to go through interviews. A good resume does little to help you pass an interview, and if you can’t answer questions about it well, it can actually make people doubt your expertise.

So from the Data-Driven Job Search point of view, whether a resume is “good” or “bad” comes down mainly to the positive response rate. The reverse isn’t necessarily true, though: your positive response rate doesn’t depend only on your resume. Referrals, cold emails and cover letters count too.

For resumes, then, the main thing to look at is which version gets the highest response rate for which type of role. That said, there are some general principles for what makes a resume get more responses.

Core idea: what makes a good resume get responses

Step back and look at the purpose of a resume: it answers the company’s needs. On one page, you convince the recruiter that “my experience can meet your needs.” Look closely and there are two parts: experience that meets their needs.

The company’s needs

How do you see what the company needs? That brings us back to the job description (JD) that almost every opening has.

Inside the company, the team with the need usually sits down with a recruiter to discuss what kind of role to open, and what they agree on becomes the JD. A good JD says clearly what they want, so you can tell at a glance how well you match. You could say the JD is the company’s resume, and they hope you’ll respond positively to it (by applying).

How do you read a JD? Most have basic requirements, preferred requirements and a description of the team or culture, and some also cover benefits and other information. For example, here is what one company on LinkedIn asked for in a Senior Software Engineer role:

1. Basic requirements are often called the must-haves. These are the core needs. Meet as many of them as you can, and if you can’t, these are the first gaps to close. In this example they’re labeled Requirements: four or more years of professional experience, plus some languages, the work environment and the architecture (GCP).
2. Preferred requirements are often called “good to have” or “better to have.” Once you meet the basics, this is where candidates are compared. Here it says experience with real-time APIs and containers would be great.
3. Team or culture description usually introduces the company. What matters here is that many words related to team culture are hidden in it, so read it carefully. This company used the space for Responsibilities (daily life) instead.

Now that you know what the company needs, how do you use it? The method isn’t complicated: “mirror the wording” and “gap analysis.”

Step by step: how to tailor your resume to the job description

Mirror the wording

I strongly recommend reusing the keywords, and even the sentence patterns, from the job description as much as you can. If you’re not sure how to rephrase things, ask an LLM to help. Here’s why this matters:

• Recruiters wrote the JD. They know those words and phrases better than whatever other language or keywords we might use instead.
• For competitive roles, your resume usually goes through a system (an ATS, or applicant tracking system) before a recruiter ever sees it, and the main thing it screens for is whether these keywords are used.

Don’t underestimate this simple step. In the US, at least, more than half of the keywords go unused.

A study by Cultivated Culture found that, on average, resumes mention only about 51% of the keywords in the job description.

This also reflects the “resume templates” you see everywhere now that everyone wants to be efficient. Using a template is fine; it helps you build an early resume faster. Sending the same resume out in bulk is also fine. But when employers are also getting a flood of applications, a small difference can decide who moves forward.

In practice, you can:

1. Paste the JD and your skills and experience into an LLM and ask it to generate an ATS-friendly resume.
2. Search Google for “ATS score checker.” There are plenty of tools that will score your resume as it stands.
3. The most accurate option is to have a recruiter for the role you’re targeting look at it. That’s hard to arrange and takes longer, so I don’t recommend it for anything other than your Dream Job.

Gap analysis

The other key technique is gap analysis. You list the requirements one by one, see which skills or achievements you have that hit them directly or partly, and then write those into your resume. Using the same job as an example, it looks like this:

1. Copy the JD into a spreadsheet.
2. Pull out the keywords in the JD.
3. From the keywords, pick out what you can do (whether it hits the requirement directly or only partly). I like using traffic lights as a quick filter:
   • Red: no experience at all
   • Yellow: partial or adjacent experience
   • Green: I can do this
4. Then sort them and put the most important achievements at the top.

As I’ve mentioned before, it’s really hard to find a perfect match on both sides.

If you match very few of the basic requirements right now (lots of red lights on the basics), expect this job to be hard to get a positive response from. That doesn’t mean you shouldn’t apply. What matters is how you compare with the other candidates applying at the same time. If you’re better than them, you can still make it to the next round.

Requirements where you still have a gap can become the first skills to build. For planning your time, I suggest analyzing the JDs of several Target jobs, finding the red lights that show up across their shared basic requirements, and spending your time on those skills.

Quantify your achievements for their situation

As a data-driven method, what we care about most is, of course, quantifying achievements.

The question I usually ask is: “How can I quantify the keywords they need?” I also suggest thinking about the context and the situation described in the role when you list quantified achievements. Taking the basic requirements above as examples:

• For HTTP and API experience, I’d assume they need someone who works with quite a few client teams. So I’d quantify around how many different teams’ APIs I integrated with and how I handled HTTP exceptions.
• For Kubernetes, I’d describe how I used it to handle high volume, such as XXX TPS, and the management setup I built around it.

The details depend on the job and your own skill tree.

Common mistakes to avoid

• Don’t apply a resume template blindly and ignore the keywords and requirements in the job description.
• Don’t focus only on what you want to write and ignore the role’s basic and preferred requirements.
• Don’t ignore ATS screening. Using the wrong keywords can get your resume filtered out by the system.
• Don’t expect your resume alone to get you an offer. Interview performance matters just as much.

Summary

In a job search, the core purpose of a resume is to get a positive response from the company so you can move on to the next stage. There’s no shortage of resume advice, but from the Data-Driven Job Search point of view, a “good” resume is one built to raise your positive response rate.

To do that, first understand what the company needs: read the job description (JD) closely and identify the basic and preferred requirements. Then use the JD’s keywords and sentence patterns in your resume so it gets through the ATS and catches the recruiter’s attention.

Next, do a gap analysis: map the role’s requirements against your own experience, find where you match best, and put those skills and achievements first. Finally, quantify your achievements in the context of the company’s situation, so the recruiter can see clearly how you meet their needs.

With these strategies you can raise your resume’s positive response rate, get to the interview stage more often, and build a solid base for landing the job.

A little about me: I’m Coach Chiao (George), a career coach. I’ve spent more than ten years on facilitation and coaching, with over 3,000 coaching hours and 700 workshops. I moved from Taiwan to a job overseas myself and received several offers, including roles at TikTok in Singapore, Mozilla in the UK and GitLab in the US. I ended up joining Amazon in the US as a software engineer. I later turned what I learned from that job search into a complete framework you can follow. Since 2021 I’ve helped more than 180 mentees (SWE, PM, DE, BA) land offers abroad within nine months, and I specialize in using data to guide your job search.