Your Job Feed Is Only as Good as Where the Data Comes From

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When a job board operator evaluates a new data feed, the conversation almost always centres on the same three things: how many listings it contains, what format it delivers in, and how frequently it updates. These are reasonable things to ask. They are also the wrong place to start.

None of those questions tell you where the data actually came from. And where it came from determines everything about its quality before it reaches you.

Why Source Distance Matters More Than Most Operators Realise

Think about what a job listing actually is at its origin. An employer opens a role. Someone on their team writes the job description, sets the requirements, specifies the location and the salary if they choose to share it, and publishes it on the company’s career page. At that moment, the listing is accurate, complete, and live.

Now consider what happens to that listing as it travels toward your job board.

Here is what typically happens to that listing before it reaches you. A data vendor collects it from the career page, but not instantly. They crawl on a schedule, so the listing is already hours old when it enters their system. They process it, clean it up where they can, and pass it along. An aggregator picks it up from the vendor, adds it to their own collection, and passes it along again. Another platform pulls from the aggregator. By the time the listing arrives in your feed, it has passed through three or four different systems, each one introducing its own delay, its own decisions about formatting, and its own gaps. 

What lands on your job board is not the listing the employer posted. It is a version of it, shaped by every system it passed through on the way.

The Problem With Inherited Data

Every intermediary in that chain introduces something. A job board collecting once a day introduces a lag of up to 24 hours. An aggregator pulling from that board inherits the lag and adds its own collection cycle on top. By the time multiple sources have each collected and re-collected the same listing, the same role may appear on your platform under several slightly different variations, each carrying its own version of the original information.

This is not a hypothetical problem. It is how most job feeds are built, and it is why operators regularly encounter listings with inconsistent titles, unparsed locations, missing salary fields, and duplicate entries they cannot easily trace back to a single source. The data is not wrong because anyone made a mistake. It is degraded because distance from the origin is how job data naturally loses quality.

The Information Half-Life

Job data has a short shelf life. A listing that closes on Monday afternoon is no longer live, but a feed that collected it on Monday morning and updates on Tuesday evening will keep showing it to candidates throughout that window. In sectors where roles fill quickly, a 24 to 48 hour lag between a listing going live or going closed at the source and that change appearing in the feed is not a technical nuance. It is the difference between a candidate applying to a real opportunity and spending time on one that no longer exists.

The further a data source sits from the original career page, the longer this gap tends to be. Each additional layer in the chain means one more collection cycle, one more processing step, and one more delay before the change propagates to the final destination.

What Removing the Chain Actually Changes

When data is sourced directly from the employer career page, with no intermediaries between the source and the operator receiving it, the accumulated limitations of the chain disappear. The listing that went live at the source is the one that arrives in the feed. The role that closed this morning is the one that drops from the feed today rather than three days later. The title, the location, and the skills are as the employer wrote them, processed once and delivered without the drift that multiple handling introduces.

The quality of the feed stops depending on how well each intermediary along the way managed the data. It depends entirely on the quality of the collection at source, which is a much simpler problem to solve and a much more consistent one to maintain.

Propellum sources exclusively from employer career pages across 15+ countries, with no job boards or aggregators in the chain. Every listing travels one step: from the employer to the operator. Over a billion records processed across 25 years, with freshness and accuracy controlled at the point of origin rather than inherited from whoever handled it last.

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Frequently Asked Questions

Why does job data source quality matter for a job board?

Because quality is set at the point of collection and degrades at every step away from the original source. A feed that has passed through multiple intermediaries carries the lag, formatting inconsistencies, and duplicates that accumulated in transit. A feed sourced directly from employer career pages starts at the origin and delivers what the employer posted, without the noise introduced by intermediate handling.

What is the job data provenance chain?

The sequence of sources a job listing passes through between the employer career page and the job board receiving it. Each step introduces freshness lag, potential formatting changes, and duplicate risk. A chain of career page to job board to aggregator to your platform means the data has been handled three times before you receive it, accumulating the limitations of each handler.

How does data freshness degrade in a multi-hop job feed?

Each intermediary collects on its own schedule. A job board collecting daily introduces a 24-hour lag. An aggregator pulling from that board adds its own cycle on top. By the time data arrives at the end of a multi-hop chain, it may be two to three days old regardless of how frequently the final delivery updates.

What is the difference between career page sourcing and job board scraping?

Career page sourcing collects from the employer’s original posting, one step from the source. Job board scraping collects from a platform that has already processed and potentially reformatted the same listing. Career page data carries no inherited lag or noise. Scraped data carries everything the upstream board introduced before delivery.

How do duplicates enter a job feed?

When the same listing is collected from multiple sources, each copy arrives as a separate record unless deduplication is applied before delivery. In a multi-hop chain, the same role may have been picked up by several boards and aggregators, each delivering their own version. Career page sourcing eliminates the problem at origin because the listing is collected once and deduplicated at that point rather than after it has already multiplied across sources.