The Job Board KPI Guide: How to Measure a Two-Sided Marketplace, Not Just a Website

Most job board operators are measuring the wrong things. They track pageviews, bounce rates, and session durations (metrics designed for content sites and SaaS products) while their marketplace quietly suffocates. You can have 50,000 monthly visitors and still operate a dying job board if your supply-to-demand ratio is broken and employers aren't getting applications. High traffic means nothing when the fundamental exchange isn't happening.

The problem isn't lazy operators. It's that every analytics guide for job boards treats them like websites instead of what they actually are: two-sided marketplaces where value creation depends entirely on the interaction between employers and job seekers. Generic web analytics tell you how many people showed up. They don't tell you if your marketplace is healthy, if liquidity is improving, or if you're on the path to network effects that compound growth.

This guide covers every metric that matters for job board operators, organized not by what Google Analytics makes easy to track, but by what predicts whether your board will scale or stall. The framework draws from NFX's marketplace research, Cavuno's built-in analytics dashboard (designed specifically for two-sided job board dynamics), and first-party experience scaling Himalayas to hundreds of thousands of monthly visitors and sustainable revenue.

You'll learn how to measure demand-side health (job seeker behavior), supply-side health (employer engagement and job inventory), and marketplace health (the interaction between both sides that determines whether you have a real business). We include specific benchmarks, where to find each metric in Google Analytics and Google Search Console, what action to take when numbers are off, and which metrics to ignore entirely.

If you're starting a job board or trying to diagnose why growth has plateaued despite decent traffic, this is the measurement framework you need.

Why standard job board metrics miss what actually matters

Job boards have two distinct user groups whose value is interdependent. A regular website with 100,000 visitors and low engagement needs better content. A job board with 100,000 visitors but no employers posting jobs is a structurally broken marketplace. The traffic is worthless because the core exchange (employers finding candidates, job seekers finding opportunities) isn't happening.

This is the defining characteristic of two-sided marketplaces: cross-side network effects. More employers posting makes the board more valuable to job seekers (more opportunities to apply). More active job seekers make the board more valuable to employers (better candidate pool, faster hires). Each side's participation directly increases value for the other side. Standard SaaS metrics measure one user group doing one thing. Job board KPIs must measure whether two user groups are creating value for each other.

The challenge is asymmetry. One side of the marketplace is almost always harder to acquire than the other. For most job boards, the constraint is supply: getting employers to post jobs consistently. Demand (job seekers) is abundant; everyone needs work. But if you only measure demand-side metrics like visitor count and application submissions, you'll miss the supply-side starvation killing your marketplace. You'll see applications going up and assume health is improving while your job inventory quietly shrinks because employers aren't seeing results.

This is why every analytics guide that organizes metrics by tool ("here's what to track in Google Analytics, here's what to track in Google Search Console") misses the point. The right framework organizes by business question:

• Is the demand side healthy? (Are job seekers finding relevant opportunities and taking action?)
• Is the supply side healthy? (Are employers posting jobs and staying engaged?)
• Are both sides creating value for each other? (Is the marketplace facilitating successful matches?)
• Is that value translating to revenue? (Are you capturing enough value to sustain and grow?)

Layer on top: SEO metrics (how you acquire both sides), technical performance (friction that kills conversions), and email engagement (retention and reactivation). Everything ties back to marketplace health.

The three metric categories that matter

The framework has three core layers (demand, supply, and marketplace health) with supporting metrics layered underneath:

Most job board operators obsess over demand-side metrics because they're easy to measure in Google Analytics. They ignore supply-side and marketplace health until it's too late. By the time you notice employer churn or inventory decline, you've already lost months of momentum.

Demand-side metrics: are job seekers finding and using your board?

Demand-side metrics measure whether job seekers discover your board, engage with listings, and take action. Without demand, you have no value to sell to employers.

Traffic and acquisition metrics

These metrics tell you if job seekers are finding your board and where they come from.

Visitors and sessions — Audience quality matters more than absolute numbers for niche boards. A board serving 5,000 highly targeted visitors in a specific vertical can outperform a generic board with 50,000 visitors because those visitors match the jobs you're listing. Track month-over-month growth rate alongside quality signals like application click rate. You can find traffic data on your Cavuno homepage dashboard, or in Google Analytics 4 if you prefer deeper segmentation.

Top sources — Your referrer mix reveals how much control you have over your demand. Organic search is "owned" demand: you built SEO authority. Aggregator traffic is "rented": Indeed or Google for Jobs can change algorithms tomorrow. A healthy niche board typically sees 40-60% organic traffic, 15-25% direct, and 10-20% from email or social. If you rely on a single aggregator for 70% of traffic, you have a strategic risk. Cavuno tracks top sources in your Analytics dashboard without requiring GA4 setup.

Top locations — Geography should align with your niche. If you run a "NYC tech jobs" board and 60% of traffic comes from India, your demand side is misaligned with your supply side. Employers posting NYC roles need NYC seekers. Check your top locations in the Cavuno dashboard under Locations to verify your audience matches your job inventory.

Top devices — Job seekers skew heavily mobile (60-70% or more), while employers posting jobs skew desktop. If your mobile traffic is under 50%, you likely have a discovery problem: job seekers browse on phones but can't find you. Cavuno shows device breakdown in the dashboard under Devices.

Engagement metrics

Traffic alone means nothing if visitors bounce immediately. Engagement metrics reveal whether job seekers stick around and explore your listings.

Pageviews and pages per session — For job boards, pages per session measures search behavior quality. A job seeker who views 1 page and leaves either found exactly what they needed (rare) or found nothing relevant (common). Healthy niche boards see 2.5-4.0 pages per session. Under 1.5 signals poor search functionality or irrelevant traffic.

Average session duration — Benchmark is 2-4 minutes for job board engagement. Short sessions (under 30 seconds) combined with low pages per session usually means traffic quality issues or landing page problems.

Real-time visitors — Useful for specific moments: launch day, right after a newsletter send, or during a paid campaign. Not useful as a daily habit. Real-time numbers fluctuate too much to be meaningful, and checking them creates anxiety without actionable insight.

Top pages — If your top pages are all blog posts and zero job listings appear in the top 10, your SEO works for content but not for your marketplace. This is common in the early stages. Blog content often ranks faster than job listings and category pages, which take time to build authority. Focus on optimizing category and location pages for job-related keywords alongside your content strategy. See our job board SEO guide for how to accelerate this.

Job seeker conversion metrics

These metrics measure the moment job seekers take action, the entire reason your board exists.

Job application clicks — This is the single most important job board metric. An application click happens when a seeker clicks "Apply" or "Apply on company site" from your listing. This is your core conversion event, equivalent to a purchase on an e-commerce site. Everything else (traffic, pageviews, session duration) exists to drive this action.

Calculate your click-to-apply rate with this formula: (Application clicks / Job views) x 100. If a listing received 1,000 views and 75 application clicks, your CTR is 7.5%.

Benchmarks — Average click-to-apply rate across all job boards runs 4-8%. High-performing niche boards with well-matched audiences hit 10-15%. Below 3% signals problems: poor job descriptions, mismatched audience, or a buried apply button. If your CTR is under 3%, audit your top listings and compare them to competitors. Are descriptions vague? Is the apply button hard to find? Do your job categories attract the wrong audience?

Using application clicks for employer ROI — Application click data gives you concrete proof of value when talking to employers. "Your listing received 847 views and 62 application clicks, a 7.3% CTR" is tangible evidence their job reached qualified seekers. Build this into your employer reporting to justify pricing and renewals. Cavuno tracks total application clicks in the dashboard, giving you aggregate conversion data across your board.

One level deeper: introduce the concept of "qualified application rate" to separate clicks from actual quality. A click that bounces from the employer's ATS in under 10 seconds probably wasn't a qualified candidate. If you can access employer ATS data (rare, but some partners share), compare your CTR against their fill rates to estimate application quality. A board with 6% CTR but 30% fill rate outperforms a board with 12% CTR but 10% fill rate.

If your demand-side metrics look strong but supply-side metrics lag, you likely have an employer acquisition problem: employers don't know you exist yet. If supply looks strong but demand is weak, focus on content marketing and SEO to build organic discovery.

Supply-side metrics: is your job inventory healthy?

Your demand-side traffic means nothing if your supply side is broken. You can drive 50,000 monthly visitors to a board with 300 stale jobs and watch them bounce. Supply-side metrics tell you whether your job inventory is serving your market and whether employers are getting enough value to stick around.

Most job board operators obsess over traffic and ignore the supply side until it's too late. Declining job-posted rates show up 2-3 months before traffic collapses. By the time you notice fewer visitors, your inventory problems are already deep.

Job inventory metrics

Total active jobs is your baseline supply metric. But more isn't always better. 10,000 stale aggregated jobs are worse than 200 fresh curated listings. What matters is relevance to your niche. A niche board with 150 highly targeted jobs will outperform a generic board with 5,000 irrelevant listings.

Jobs posted per week or month measures velocity. This is a leading indicator of marketplace health. If your job-posted rate declines for two consecutive months, you have a supply problem, and traffic will follow within 60-90 days. Track this weekly.

Ratio of curated vs. aggregated jobs reveals positioning. A high percentage of aggregated jobs isn't inherently bad. If you're operating a niche board and carefully curating which companies and roles you backfill, aggregated inventory can be just as relevant as direct posts. The problem arises when you're scraping generic feeds without filtering, making your board indistinguishable from every other aggregator. Track this ratio and assess whether your aggregated jobs actually match your niche. Learn more about job wrapping and building a job board aggregator.

Job freshness measures what percentage of active jobs were posted in the last 7, 14, or 30 days. Stale inventory kills seeker trust faster than anything else. Benchmark: 60%+ of your active jobs should be within the last 30 days. If you're under 40%, you're showing job seekers a graveyard.

Employer engagement metrics

Active employer count tracks unique employers with at least one job posted in the last 90 days. This shows how many companies are using your board right now, not how many have accounts or posted once two years ago.

Repeat posting rate is the percentage of employers who post more than once. This is your retention proxy. The healthy range varies by board maturity and pricing model, but directionally: if almost nobody posts a second time, you're not delivering enough value. Track this over time and look for improvement as you grow your seeker base.

Employer churn rate measures employers who posted in one period but not the next. Track this quarterly to catch retention problems early. Rising churn usually points to either poor candidate quality or competitors offering better reach. The absolute number matters less than the trend. A sudden spike deserves investigation.

Average jobs per employer reveals concentration risk. If one employer accounts for the majority of your inventory, you're one cancellation away from a supply crisis. Watch whether your supply is diversifying over time or becoming more concentrated.

Time from signup to first post measures activation speed. The faster employers post after signing up, the healthier your onboarding flow. If most employers who sign up never post at all, there's friction in the process. Simplify your posting flow and consider follow-up emails to nudge them.

One critical insight most operators miss: more employers isn't always better. This is a negative same-side effect from network effects frameworks. As you add more employers competing for the same candidates, the value for each individual employer decreases. You need to monitor whether adding employers still improves your marketplace or starts degrading it. Niche boards have a natural advantage here because the competition is pre-filtered: every employer is targeting the same specialized talent pool.

Revenue metrics

Revenue from Stripe is your north star business metric. Whether you track this as MRR (for subscription models), total posting revenue (for pay-per-post models), or a blend of both depends on your monetization strategy. What matters is that revenue is growing relative to your marketplace activity. Where to find it: Cavuno dashboard → Revenue section (via Stripe integration), or your Stripe dashboard directly.

Job posting revenue trends should be tracked month-over-month and quarter-over-quarter. Track this separately from traffic. If traffic grows 30% but revenue only grows 5%, it could mean your monetization is underperforming, or it could mean you're successfully growing the job seeker side of the marketplace, which is a prerequisite for charging employers more. Context matters: understand which side you're growing before drawing conclusions.

Revenue per job posting is total posting revenue divided by total paid posts. Benchmark: general boards see $50-150 per post, while niche or premium boards command $200-500+ per post. If you're below $50, you're either underpricing or attracting low-value employers.

ARPU (average revenue per user) is total revenue divided by active paying employers. This shows what each employer relationship is worth and how effective your upselling is. If ARPU is flat or declining while customer count grows, you're not expanding account value. You're adding more small customers.

AdSense RPM (revenue per 1,000 pageviews) measures display ad performance on your job board traffic. General boards see $3-8 RPM, while niche boards with high-intent traffic in lucrative verticals (finance, tech, healthcare) can hit $8-20+ RPM. Where to find it: your Google AdSense dashboard.

LTV:CAC ratio compares customer lifetime value to acquisition cost. If you're spending $200 to acquire an employer who pays $150 once and churns, you're underwater. Benchmark: 3:1 is the healthy standard. Every dollar spent acquiring a customer should return three dollars in lifetime revenue. Under 2:1 means you're burning money. Over 5:1 means you're probably under-investing in growth.

For more on monetization strategy, see job board monetization.

Marketplace health metrics: the KPIs no one talks about

Traffic and application volume matter, but they ignore the metrics that determine whether your marketplace survives. These are the indicators venture capitalists use to evaluate two-sided platforms, and the ones that predict whether employers and job seekers will stick around or churn out.

Supply/demand balance: the core indicator

Jobs-to-applicant ratio — Divide your total active jobs by your total active seekers (or total applications in a given period). This is a key marketplace health indicator. In early stages, having more seekers than jobs is ideal. It means employers who do post get strong application volume, which proves ROI and drives word-of-mouth. The balance becomes critical as you scale: too many jobs with too few seekers means employers get no applications and churn. The goal is growing both sides, but demand (seekers) typically needs to lead supply (employers) for the marketplace to feel valuable.

Applications per job posting — This measures demand-side liquidity. The range varies enormously: major platforms like Indeed see 100-250+ applications per posting, while niche boards typically see far fewer but more relevant applicants. What matters isn't hitting a specific number. It's whether employers feel they're getting enough qualified candidates to justify the cost. Track this metric over time and correlate it with employer retention to find your board's sweet spot.

Category-level balance — Your aggregate ratio hides critical problems. You might have 100 applicants per marketing job but zero per engineering roles. Segment by category, geography, and job level. A marketplace that's liquid in one vertical but dead in another will hemorrhage users in the underserved segment.

The NFX framework calls this "marketplace liquidity": the percentage of listings that successfully attract sufficient interest within a reasonable timeframe. A liquid marketplace means both sides consistently get what they came for. Watch for "asymptotic marketplace effects": after a certain supply level, each additional listing provides diminishing value. Adding more aggregated jobs can hurt your marketplace by diluting quality and overwhelming seekers.

Network effects indicators

Cross-side growth correlation — When you add more jobs, does seeker traffic increase? When you add more seekers, do more employers want to post? Plot both metrics over time. Positive correlation signals healthy network effects. Flat or negative correlation means your flywheel is broken.

Organic demand growth rate — Calculate the percentage of new seekers arriving without paid acquisition. Rising organic demand means your marketplace is generating genuine word-of-mouth and SEO gravity. If you're stuck at 20-30% organic and can't break higher, you likely haven't achieved product-market fit.

Critical mass indicators — NFX defines critical mass as the point where network value exceeds standalone product value. Early signals include employers renewing without prompting, seekers returning weekly without email nudges, and organic traffic exceeding paid referral traffic. Track your repeat visitors to new visitors ratio. When this consistently stays above 30-40%, you're approaching critical mass.

Multi-tenanting rate — Measure the percentage of employers also posting on Indeed, LinkedIn, or competing boards. High multi-tenanting means your board isn't differentiated enough. Track your exclusive posting rate. Rising exclusivity indicates growing network effects and real marketplace power.

The NFX framework emphasizes finding your "white-hot center," the densest, most active cluster within your marketplace. This might be your most engaged category, geography, or user segment. Focus your optimization efforts there first. Activity radiates outward from these pockets of high engagement.

Fill rate and time-to-fill

Fill rate — Calculate the percentage of posted jobs that receive at least a minimum number of applications (typically 3-5) within the posting duration. This is the employer-side equivalent of conversion rate. Benchmark: 70%+ is healthy. Below 50% means half your employers are getting no value and will churn.

Time to first application — Measure how quickly a new posting gets its first application. For niche boards, 24-48 hours is great. A week with zero applications signals your demand side is too thin or your matching is broken.

Average time-to-fill — Track the time from posting to marked as filled or expired. This varies wildly by industry. Software engineering roles might fill in 30 days while executive positions take 90+. Benchmark within your specific niche and track whether this metric improves as your marketplace matures.

Email and job alert metrics

Core email metrics and job alert benchmarks

You need to track six metrics for every email campaign and alert you send. Job alerts perform differently than standard marketing emails. Your benchmarks should reflect that reality.

Open rate — The recruitment and staffing industry averages around 19-25% for email open rates. Job alerts can outperform this because subscribers explicitly requested them, but open rates are increasingly unreliable as a standalone metric due to Apple Mail Privacy Protection inflating numbers. Use open rate as a directional signal, not a precise measurement.

Click rate — General marketing sits at 2-3%. Job alerts have the potential to do better since each email contains multiple actionable job links. The recruitment industry averages around 1.8% CTR. If you're beating that, your matching and formatting are working. If you're below it, your job matches may not be relevant enough.

Click-to-open rate (CTOR) — Divide clicks by opens. This isolates content quality from deliverability issues. CTOR is more useful than open rate or click rate alone because it tells you whether people who open your emails find the jobs compelling.

Unsubscribe rate — General marketing: 0.2-0.5%. Job alerts should stay under 0.3%. Higher than 0.5% signals poor matching or excessive frequency. Track unsubscribe rate over time to spot problems early.

Bounce rate — Hard bounces above 2% indicate list hygiene problems. Clean your list regularly. Soft bounces above 5% suggest temporary issues but watch for patterns.

Spam complaint rate — Must stay below 0.1%. If job alerts trigger complaints, your opt-in process isn't clear or subscribers don't remember signing up.

Finding the right send frequency

Weekly digests are the default for most job boards. They bundle enough new listings to be valuable without overwhelming subscribers. For low-volume niches, biweekly can work better than weekly if you'd otherwise be sending thin emails with only 1-2 new jobs.

The metric that decides your frequency: unsubscribe rate. If it creeps above 0.3%, you're likely sending too often for the value you're delivering. Track this over time and adjust accordingly.

Cavuno's built-in job alerts handle weekly frequency out of the box.

SEO and search visibility metrics

Google Search Console fundamentals

Impressions — Total search visibility. This is your leading indicator: impressions grow before clicks do. Rising impressions with flat clicks means your titles and meta descriptions need work. Searchers see you but don't click.

Search clicks — Organic traffic from Google. Compare this against your analytics platform to reconcile discrepancies. Search Console shows clicks from Google only. Your analytics shows all traffic sources.

Average CTR by page type — This is the key insight most competitors miss. Blog posts should hit 3-8% CTR. Category and tag pages should hit 1-4%. Individual job listings often sit under 1% because of high impressions but low click intent. Searchers scan listings in the SERP but click selectively. Don't panic about low listing CTR. It's normal.

Average position — Track by page type. Focus on category pages and blog posts. Individual listing rankings are too volatile since they appear and expire constantly. One important nuance: as you rank for more queries, your average position often drops before traffic increases. This is normal. New rankings tend to start on page 2-3 before climbing, which pulls the average down. Don't be alarmed. Look at total clicks alongside position trends.

For a deeper dive, see our job board SEO guide. Building domain authority through link building for job boards is equally critical for long-term organic growth.

Google for Jobs performance

Google for Jobs impressions and clicks — In Search Console, use the Search Appearance tab and filter for "Job listing" and "Job details" to see how your structured data listings perform in the Google for Jobs carousel. This breaks out impressions, clicks, and CTR specifically for your job listings appearing in the Jobs experience — separate from your standard organic results. Google for Jobs impressions often exceed standard organic by 5-10x for job boards, making this a massive traffic channel most operators overlook.

Structured data validation pass rate — Use Rich Results Test and the JobPosting report in Search Console. Invalid structured data means invisible in Google for Jobs. Your pass rate should be 100%. Anything less means you're leaving traffic on the table. Cavuno actively monitors structured data validation and proactively fixes issues as they're identified, so this is handled for you out of the box.

Index coverage and crawl efficiency

Pages indexed vs. submitted — For large boards with thousands of listings, Google may not index everything. Check the "Pages" report in Search Console. If indexed pages are 50% of submitted pages, you have crawl budget or quality issues.

Expired job handling — 404s waste crawl budget. Stale content risks penalties. Best practice: 301 redirect expired jobs to parent category or show an "expired" page with related active listings. Never leave dead job pages returning 404s.

Crawl budget efficiency — For boards with 5,000+ pages, monitor Googlebot efficiency. Faceted navigation (filters for location, category, salary, remote status) creates thousands of duplicate URLs. Use canonical tags and robots directives to prevent crawl waste. Two factors that directly improve crawl budget: site speed (faster pages mean Googlebot can crawl more pages in the same time) and backlinks and traffic, which signal to Google that your site deserves more frequent crawling.

Technical performance metrics (Core Web Vitals)

The Core Web Vitals that impact job board rankings

LCP (Largest Contentful Paint) — Target under 2.5 seconds. For job boards, the LCP element is usually the job listing content block or the search results list. Heavy company logos can bloat LCP. Compress images and lazy-load below-the-fold content.

CLS (Cumulative Layout Shift) — Target under 0.1. Job boards are susceptible to CLS from late-loading ad units (especially AdSense) pushing job listings down the page. Lazy-load ads with defined dimensions to reserve space. CLS is often the hardest metric for monetized job boards to pass.

INP (Interaction to Next Paint) — Target under 200 milliseconds. This matters most for search filters and faceted navigation. How fast does the page respond when a user clicks a category filter or toggles remote-only? Heavy JavaScript frameworks can tank INP.

FCP (First Contentful Paint) — Target under 1.8 seconds. First paint of any content on screen. Fast FCP keeps users engaged while the full page loads.

TTFB (Time to First Byte) — Target under 800 milliseconds. Server response time. Check your hosting performance if TTFB exceeds 1 second consistently.

Google uses the 75th percentile (P75) of real user data, not averages. The worst 25% of page loads don't count, but your P75 must pass thresholds. Check CrUX data in Search Console under Core Web Vitals report. This shows Google's actual ranking data.

Job boards follow a specific pattern here: individual listing pages tend to have better Core Web Vitals than search results pages. Fewer elements, simpler layout. Category pages with hundreds of listings and multiple filters are your most likely failure points. Prioritize optimizing these pages first.

A monthly reporting template for job board operators

The metrics that matter monthly vs. weekly vs. daily

Most operators check their dashboards too often or not enough. The right cadence depends on the metric and your stage.

Daily metrics — Only if you're running active campaigns or just launched. Check real-time visitors (to spot traffic anomalies during paid campaigns) and application clicks (to catch broken forms or integration issues). Otherwise, daily checking creates noise, not insight.

Weekly metrics — Your operational heartbeat. Review traffic trends (are you up or down week-over-week?), top-performing pages, email campaign performance, and job posting volume. This cadence lets you spot problems early without reacting to daily variance.

Monthly metrics — The full strategic review. Run through your entire dashboard: all demand metrics, all supply metrics, marketplace health ratios, revenue trends, employer retention and churn, SEO position tracking, and a Core Web Vitals audit. This is where you identify patterns, adjust strategy, and set priorities for the next 30 days.

The mistake most operators make is checking everything daily, creating anxiety and overreaction, or only looking at revenue monthly and missing early warning signals. Match the metric to the right review cycle.

One framework that helps: separate your metrics into inputs and outputs. Outputs are the results you care about: application clicks, revenue, employer retention. Inputs are the activities you directly control: jobs posted per week, email send frequency, content published, employer onboarding improvements. Amazon's Weekly Business Review process is built on this distinction: when an output metric drops, don't stare at the number. Trace it back to which input changed. Revenue down? Check whether job posting volume declined, or whether email click rates dropped, or whether you lost a key employer. This turns your dashboard from a scorecard into a diagnostic tool.

The one-page monthly dashboard

Here's a template you can copy and fill in monthly. Focus on trend direction and whether action is needed, not just the absolute numbers.

Cavuno's built-in analytics dashboard covers traffic, engagement, application clicks, revenue, and email in one place. No need to stitch together multiple tools. Google Search Console and advanced marketplace metrics require additional setup.

Five common measurement mistakes job board operators make

Mistake 1: obsessing over traffic while ignoring supply/demand balance

You need a critical mass of traffic before you can monetize the employer side effectively. But once you have meaningful seeker traffic, doubling it further won't help if nobody's posting jobs. The operators who stall are the ones who keep optimizing for traffic long after they should have shifted focus to supply. Track both sides, and know which one is your current constraint.

Mistake 2: treating all pageviews equally

A pageview on a job listing from a relevant seeker is worth 100x a blog pageview from a random searcher. Segment by page type: job listings vs. blog/content vs. category pages. A site with 80% job listing pageviews is healthier than one with 40%, even if total pageviews are lower.

Mistake 3: ignoring employer-side metrics entirely

Most guides and operators focus exclusively on job seeker traffic. Employers are your revenue source. If you're not tracking retention, repeat posting rate, and activation speed, you're flying blind on the business side.

Mistake 4: using vanity metrics in employer reports

"Your listing got 10,000 impressions" is meaningless. "Your listing received 47 application clicks from candidates in your target market" is a concrete proof point. Focus on application clicks and click-through rate per listing.

Mistake 5: not segmenting Search Console data by page type

Blog posts, job listings, and category pages perform completely differently in search. A 2% average CTR means nothing if blog posts get 6% and listings get 0.5%. Segment by URL pattern to see where your SEO is actually working.

Frequently asked questions

What is the most important metric for a job board?

Application click rate is the single most important job board metric. This measures the percentage of job views that result in a click to apply, showing whether your marketplace is creating real value. A healthy click-to-apply rate is 4-8% for general boards and 10-15% for niche boards with well-matched audiences.

How often should I check my job board analytics?

Match the metric to the right review cadence. Check traffic and application clicks weekly to spot problems early. Run a full strategic review monthly covering all demand, supply, marketplace health, revenue, and SEO metrics. Only check daily if you're running active campaigns or just launched.

What is a good application click rate for job boards?

Average click-to-apply rate across job boards is 4-8%. High-performing niche boards with well-matched audiences hit 10-15%. Below 3% signals problems with job descriptions, audience mismatch, or buried apply buttons. Compare your rate against these benchmarks and investigate if you're consistently below 4%.

How do I measure marketplace health for a job board?

Marketplace health is measured through supply/demand balance metrics: jobs-to-applicant ratio, applications per posting, fill rate (percentage of jobs receiving 3+ applications), and cross-side growth correlation. Track whether adding more employers improves or degrades value for job seekers, and vice versa.

What percentage of job board traffic should be organic?

A healthy niche job board typically sees 40-60% organic traffic, 15-25% direct traffic, and 10-20% from email or social. If you rely on a single source (like Indeed or Google for Jobs) for over 70% of traffic, you have strategic risk from algorithm changes.

Measure what matters, ignore the rest

Job boards are marketplaces, not media sites. Your measurement framework should reflect that. Traffic metrics matter, but only as inputs to what drives success: a balanced, liquid marketplace where employers get qualified applicants and seekers find relevant opportunities.

The hierarchy is clear: marketplace health (supply/demand balance, application clicks per listing, employer retention) matters more than job-specific conversions (application click rate, time on listing), which matter more than traffic metrics (pageviews, visitors), which matter far more than vanity metrics (impressions, social shares).

Start with the monthly template above. Don't try to track everything at once. Pick the 5-6 metrics most relevant to your current stage. Early stage? Focus on supply: active listings, employer activation rate, and days to first listing. Growth stage? Optimize demand: job listing traffic, application click rate, and SEO performance. Mature stage? Revenue and retention: MRR, repeat posting rate, employer retention, and revenue per employer.

The operators who win aren't the ones with the most data. They're the ones who measure the right things, act on what they learn, and ignore everything else.

Cavuno's built-in analytics dashboard tracks traffic, engagement, application clicks, revenue, and email performance out of the box, so you can focus on the metrics that matter instead of stitching together five different tools. Start your job board