A little over two weeks ago, I started seriously looking for a job in tech again.
Not bookmarking jobs.
Not tweaking my LinkedIn headline for the...
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I noticed a pattern last time I was applying places. I was logging applications in notepad. For roughly every 15 applications I would get some type of response ๐
So i realized it is actually a numbers game. 5 real applications catered to a specific job definitely feels like 50. But I get higher responses when I trailer them.
sis it really is! And DONT even get me started on having to create an account on the employers application portal / website. WHY DO I NEED TO DO THAT
Added layer of "how bad do you want it" I suppose. ๐ it could be argued, that those jobs might be easier to get, having weeded out lazy people. LOL
59 applications in two weeks is honestly a lot of data to work with. What I found most interesting is how much the response rate can tell you about the strategy itself โ whether the problem is the CV, the targeting, or simply the market. Tracking applications this way seems much more useful than just applying endlessly and hoping something sticks.
This is a really interesting way to look at a job search because youโre treating it as a system instead of just an emotional experience.
The part that stood out to me is the distinction between โapplication volumeโ and โopportunity generation.โ 59 applications sounds like the main metric, but once you separate rejection, screening, interview, silence, and opportunities coming from outside the funnel, the picture becomes much more useful.
Iโd actually take this one step further and track the funnel like a product funnel:
Application โ Viewed โ Response โ Screening โ Interview โ Offer
Then add the source and role type to each step.
For example, if 40 software-engineering applications produce almost no human interaction while 8 technical-writing applications produce an interview, that doesnโt automatically mean โbecome a technical writer.โ It tells you where to investigate: positioning, targeting, portfolio evidence, market, or simply sample size.
And the Sinch example makes the whole experiment more interesting. A traditional application funnel can be performing poorly while a โbuild โ publish โ demonstrate โ opportunityโ funnel is already producing something tangible.
Thatโs probably the biggest takeaway for me: donโt optimize for the number of applications. Optimize the system that turns your skills and evidence into opportunities.
The role-type table is the part I'd watch most closely: 42 software applications with one screening and no interview yet, 8 writing ones and an interview request within hours, plus the Sinch work arriving through writing as well. You're right that eight is far too small to conclude anything, but those are two separate paths pointing the same way, which says more than either number alone. A cheap test for the next two weeks would be keeping the volume steady and flipping the mix, so writing and DevRel get a real sample and the comparison stops being 42 against 8. Splitting the 20 week-old silences by role type would also show early whether the gap is real or just noise.
I think that day i had to take you out yesdrday rember
That's a lot, I've been applying relentlessly too. I'm trying for a different company but I didn't actually keep track of my applications, leaving the site that I applied in keep track. I'll make a point to keep track.
Thanks for counting instead of guessing. My funnel looks like yours with one difference: I stopped treating an application as a request for a seat. I run a small engineering company, so when I apply, I follow up in writing with what I build and the terms I work on, as a supplier rather than an employee.
Most never answer, same as your 86%. The ones that do answer are already talking about the work, not about whether I fit a checkbox.
And like your Sinch example, everything that actually turned into paid work came from things I had built and published, not from the application form.
I will be curious about your Day 30 numbers.
Thanks