Salary Data Methodology
How we collect, process, and present marketing operations salary data.
Data Collection
MOps Report tracks marketing operations job postings from job boards, company career pages, and aggregator APIs. We focus on roles with titles containing marketing operations, marketing technology, MOps, or closely related variants.
Our current dataset includes 295 tracked positions. Of these, 203 (68.8%) include disclosed salary ranges. Roles without salary data are included in volume and trend analyses but excluded from compensation statistics.
Salary Normalization
Job postings report compensation in different formats: annual salary ranges, hourly rates, and occasionally total compensation. We normalize all figures to annual base salary. Hourly rates are converted assuming 2,080 hours per year. Total compensation figures are broken into base and variable where possible.
When a posting provides a range (e.g., $80,000-$120,000), we record both endpoints. Aggregates on this site show the average of low endpoints (Avg Low) and the average of high endpoints (Avg High) for each group. The median uses the midpoint of each posting's range.
Seniority Classification
We classify roles into five seniority levels based on title analysis:
- Entry: Coordinator, Specialist, Associate, Analyst (0-2 years typical)
- Mid: Manager, Senior Specialist, Lead (3-5 years typical)
- Senior: Senior Manager, Principal, Staff (5-8 years typical)
- Director: Director, Senior Director, Head of (8-12 years typical)
- VP: Vice President, SVP, EVP (12+ years typical)
Roles with ambiguous titles are classified as Unknown and excluded from seniority breakdowns.
Location Classification
We map each posting to a metro area based on the listed location. Remote roles are tagged separately. Postings that list only a state or "United States" without a specific metro are classified as Unknown for location analysis but may still appear in remote vs. onsite comparisons.
Remote vs. Onsite
Roles are classified as remote if the posting explicitly states remote, work from home, or distributed. All other roles are classified as onsite, which includes hybrid arrangements. This is a conservative approach that likely understates the true share of remote-flexible positions.
Update Frequency
The dataset is refreshed weekly. Historical data is preserved for trend analysis. All statistics on the site reflect the most recent data pull.
Limitations
Our data has inherent limitations you should understand:
- Disclosure bias: Only 68.8% of tracked postings include salary. States with pay transparency laws (California, New York, Colorado, Washington) are overrepresented.
- Title variance: Marketing operations roles have inconsistent titling across companies. Our classification catches most patterns but may miss some edge cases.
- Sampling: We track postings from major job boards and company sites, but do not capture every listing. Internal promotions and referral-only roles are not represented.
- Timing: Compensation reflects what employers are offering today. Accepted offers may differ from posted ranges due to negotiation.
Related Pages
Source: MOps Report analysis of 295 marketing operations job postings (203 with disclosed salary data). Updated 2026-04-04.
Frequently Asked Questions
Where does MOps Report salary data come from?
All salary data comes from public job postings that disclose compensation ranges. We track 295 marketing operations positions, of which 203 (68.8%) include salary information.
How often is the salary data updated?
We update our dataset weekly. Each update includes new postings, removes expired listings, and recalculates all aggregates.
Why do some pages show different numbers?
Different pages slice the data differently. The salary index shows overall statistics, while seniority and location pages show subset-specific numbers. All numbers are internally consistent within each view.
Can I use this data for salary negotiations?
Yes. Our data provides a market benchmark. Combine it with your specific experience, skills, and the employer's context for the strongest negotiation position.