What do US marketing ops salaries look like by region, per BLS data?

What to take away

Why salary data matters for martech workflow automation

Marketing ops leaders use BLS regional pay bands as an input to martech planning, not just compensation talks. Labor is often the largest cost in a workflow automation program, so regional salary differences shape build versus buy decisions, hiring location, and how much manual work you can remove with tooling.

A California or New York salary premium may justify more investment in automation and integration work. A lower-cost market may justify hiring specialists instead. Use the BLS bands to budget the people side of your martech stack, then tie those numbers to the workflows you plan to automate.

What BLS occupational data can and cannot tell you about marketing ops pay

The Bureau of Labor Statistics runs the Occupational Employment and Wage Statistics program, usually shortened to OEWS. It surveys employers rather than workers. Employers report how many people they employ in each occupation and what those people earn.

The most recent May releases put the national median for marketing managers (code 11-2021) near $157,000 a year. The middle half of that market runs from about $115,000 to $208,000. Market research analysts and marketing specialists (code 13-1161) show a national median near $75,000.

The bureau explains the design and limits of its data collections in its overview of BLS statistics. Two features matter for anyone building a salary band.

First, the numbers are estimates built from a sample, so every figure carries a relative standard error. Second, occupations are defined by the Standard Occupational Classification system, not by what your company calls the job.

That second point is where marketing ops professionals get tripped up. There is no SOC code called "marketing operations manager." The work is spread across several codes, and the code you land in changes the number you see.

A demand generation manager with a marketing automation background may be counted as a marketing manager. The same person at a different employer may be counted as a market research analyst.

What the series cannot tell you matters just as much. OEWS reports base wages and salaries. It leaves out bonuses, stock, commissions and equity. At software companies those extras can add 20 percent or more to total compensation.

The series also does not separate marketing ops from general marketing management. OEWS gives you a defensible floor and a regional multiplier. It does not give you a total compensation figure for a marketing operations hire at a growth-stage software company.

Use it for the shape of the market: which metros pay more, how the percentiles spread, and how your offer compares with the median employer in your area. Then layer private survey data on top.

One more limit: the series lags. The May estimates appear the following spring, so the numbers you cite in a negotiation are usually about a year old when they are published. That is normal and expected, and it is still the best free regional comparison available.

If you are mapping the function more broadly before you set bands, it helps to read marketing operations with a skeptical eye. Job titles in this field are inconsistent across employers.

Marketing manager and marketing specialist wage bands by state

The marketing manager code is 11-2021, and it is the closest single proxy for senior marketing ops leadership. The bureau publishes state and metro detail for it in the OEWS tables for marketing managers.

The highest-paying states cluster on the coasts and in a few technology centers. California and New York sit at the top of the distribution, Washington and Massachusetts follow closely, and Colorado and Texas land in the upper middle. Florida and much of the Midwest trail on nominal pay.

Read the state table by percentile rather than by mean. A small number of very highly paid managers in large metros pulls the mean upward. The median is a better anchor for a typical hiring band, and the 10th and 90th percentiles show how wide the market spreads.

Here is how the two main codes differ in what they capture.

The specialist code, 13-1161, covers market research analysts and marketing specialists together. The bureau publishes its state and metro detail in the OEWS tables for market research analysts and marketing specialists. This is where most early-career marketing ops people are counted.

Typical state medians for that code run near $90,000 in California, $88,000 in New York and $87,000 in Washington. Texas sits near $73,000 and Florida near $66,000, against a national median around $75,000.

The gap between the two codes is the single most useful fact for a salary conversation. Moving from a specialist title to a manager title often means moving into a different wage distribution entirely, not just a step up within one.

State-level figures also hide metro variation. A marketing manager in upstate New York and one in Manhattan are both in the New York state table, and the state median sits between them. The New York metro median typically runs $15,000 to $25,000 above the statewide figure.

Always drop to the metro table before you quote a number to a candidate.

Adjacent roles: systems analysts, database architects, BI analysts and data scientists

Marketing ops work bleeds into IT and analytics, and the bureau counts those parts of the job under different codes. If your role includes marketing automation administration, data pipeline ownership or attribution modeling, one of these bands may describe you better than the marketing manager code.

Business intelligence analysts are the closest match for reporting and dashboard work. The bureau publishes their employment and wage detail in the OEWS tables for business intelligence analysts.

Pay here tends to run above the marketing specialist band because the code sits inside the computer and mathematical group. Typical medians land between $95,000 and $115,000.

Database architects and administrators own the marketing database, the customer data platform and the integration layer. Their wages are higher still, typically $115,000 to $150,000, and they are concentrated in metros with large technology employers.

Data scientists sit at the top of the analytics ladder. Their code covers a wide range of work, from experimentation to predictive modeling, and the pay distribution is correspondingly wide. Typical medians land between $110,000 and $135,000, and the top decile clears $180,000.

Computer systems analysts are the generalists of the group. They appear in almost every industry, so their wages track local industry mix more than any marketing-specific factor. Typical medians land near $100,000 to $105,000.

Three practical implications follow.

A marketing ops manager who owns a customer data platform and a set of governed workflows is doing work that spans at least three of these codes. That is a strong argument in a banding discussion, and it is one that how to manage marketing operations often misses when it relies on a single job title.

Tech hubs versus secondary markets: California, New York, Texas, Washington and Colorado

Five states carry most of the conversation about marketing ops pay, and each behaves differently.

California has the widest distribution and the highest top end. The state median sits near $172,000, but San Francisco and San Jose run $190,000 to $215,000 while Fresno and the Central Valley sit near $120,000. A statewide California figure is almost meaningless on its own; use the metro table.

California employers also carry the compliance load of the California Consumer Privacy Act and the California Privacy Rights Act, which adds privacy operations work to many marketing ops roles.

New York has the same split. Manhattan and the surrounding metro area pay at the top of the national range, typically $185,000 to $200,000, while upstate metros pay closer to the national median. New York also concentrates finance and media employers, which tend to pay cash-heavy rather than equity-heavy.

Texas is the largest secondary market story. Austin, Dallas and Houston pay well below California and New York on nominal terms, typically $140,000 to $158,000 for marketing managers. The cost of living gap is wider than the pay gap, so real purchasing power is competitive. Texas has no state income tax.

Employers relocating operations functions from the coasts have pushed Austin wages up faster than the state median suggests.

Washington is a two-metro state in practice. The Seattle area dominates, with marketing manager medians near $175,000, and the rest of the state looks more like the national median. Washington also has no state income tax.

Colorado sits in the upper middle nationally, with Denver and Boulder carrying most of the technology employment and medians near $152,000 to $160,000. Colorado's pay transparency law has made posted ranges common, which gives candidates an unusually good view of the local market.

You can pull state and metro detail for any of these from the bureau's statistics by geography pages.

How AMA survey figures compare with the BLS series

The American Marketing Association runs its own salary surveys of practitioners, and its figures differ from the government series for structural reasons rather than because one is wrong.

The AMA samples people who belong to a professional association and respond to a survey. That group skews toward larger employers, more senior titles and more brand-side marketing work. Self-reported pay also captures total cash compensation more readily than employer-reported wage data.

The BLS samples employers and reports wages and salaries. It covers the whole economy, including small businesses and non-marketing industries that employ marketers. Its coverage is broader and its definitions are stricter.

Expect the AMA numbers to run higher for senior roles and to show a wider top end. At director level the gap typically runs 10 to 20 percent above the BLS median for the closest matching title.

Expect the BLS numbers to be more reliable for medians, for state comparisons and for roles below the director level.

The practical approach is to use both, in this order.

Neither source breaks out marketing operations as its own occupation. That gap is why so many marketing operations questions come back to which benchmark to trust, and the honest answer is that you triangulate rather than pick one.

Reading the OEWS tables without over-claiming precision

OEWS estimates carry relative standard errors, and the bureau suppresses or flags cells where the sample is too thin to publish a reliable number. A metro-level estimate with a high relative standard error is not a precise figure, and quoting it to the dollar overstates what the data supports.

Use these habits when you read a table.

A worked example

Suppose you are hiring a marketing operations manager in Denver. You start with the Colorado state median for marketing managers, about $152,000. You then pull the Denver metro row, which is higher, typically near $158,000, because the metro concentrates the technology employers.

You check the relative standard error and find it acceptable, so you keep the metro median as your anchor. You then look at the business intelligence analyst band for the analytics-heavy portion of the role. In tech-heavy metros that band can match or pass the marketing manager median.

Finally you add the AMA figure for a comparable title, which lands above both because it includes bonus. You set the band with the BLS metro median as the floor, the AMA figure as the upper reference, and a note explaining why the range is wide.

That is a defensible band. It cites public data, it explains the spread, and it does not pretend the government series measures something it does not.

Timing your citation to the BLS release schedule

OEWS estimates for a given May are published the following spring, and the bureau also issues a preliminary set of national and state estimates earlier in the cycle. Metro detail typically follows with the full release.

That timing matters for two reasons. A compensation proposal written in the fall is usually citing data that is well over a year old, and reviewers will ask. If you cite a rolling web page rather than a specific release, your number can change under you when the next vintage is published.

So cite the release, not the page. Name the May reference period and the occupation code, and keep a copy of the table you used. If the next release moves the median, you can show what changed and why.

It also helps to watch the wider set of hubspot ops hub vs zapier that affect demand for the role, because pay follows hiring volume with a lag. When companies freeze headcount, the top of the range softens first.

For marketing ops leaders, the release cycle sets a natural review rhythm. Revisit bands once a year, after the new estimates land, rather than continuously. Continuous adjustment creates noise and invites exceptions.

For marketing ops professionals, the cycle sets expectations about what a recruiter can verify. A recruiter working from last year's published median is not being evasive. That is simply the most recent public number available.

One last point on tooling. The vendors who publish marketing data governance comparisons rarely tie their pricing claims to wage data, so treat their salary-adjacent claims as marketing rather than benchmark evidence.

Common questions