Last week, a customer mentioned the “mild nuance in methodology” Compa uses to match jobs to its offers-based market data product, Index. She wrote, “job titles make a large difference in the data insights it generates.”
And she’s right.
Like with most things, context matters… a lot. Pricing a job is no different.
The price (or cost) of a job is meaningless without context. How you define a job has everything to do with how much it’s worth.
And job pricing context pours out of job descriptions.
Look at this software dev role from Adobe.
It details everything from familiarity with RESTful APIs to hybrid work schedule to specific tool experience like Splunk and New Relic.
It also shows a tight-ish salary range based on location, experience, and skills (all of which plaster the post top to bottom).
Ok, so how does Compa use all this context in its market data matching process?
We start by using technology, not people, to pull in as much context as possible.
Index participants submit offer data via API or automated report straight from their Applicant Tracking System (ATS).
Offer data includes things like job locations, pay elements, offer status, and of course, job descriptions… stuff hidden from job codes and job family summaries.
And because it's connected directly, we are context rich instead of context poor.
With matching, more is better.
Then our comp analysts go to work armed with skill and technology. They dig for clues, finding how each offer best lines up with Compa’s job architecture.
Having matched hundreds of thousands of offers this past year, the team and its tech find trends and outliers with remarkable efficiency.
They also use other things like sample offer letters and notes from customers for even more context.
What does all this do for Compa’s market data?
Well, like Rashi mentions in her LinkedIn comment, it makes a big difference in data quality and insights.
Accuracy and precision get a bump… speed too. Compa releases data every 2 weeks.
That means new job families, new countries, and big shifts in equity spend find your comp team’s planning sessions in days, not months.
Finally, you get data on niche or emerging jobs faster than anywhere else.
Compa’s CEO, Charlie, shared the AI premium in his latest newsletter. That data won’t show up in surveys for another few months at best.
And as Compa Index collects hundreds of thousands of AI job descriptions perhaps we’ll finally figure out if AI is a job or a skill.
Either way, you’ll have more than enough context to know how much it costs.
