SMU DataArts - Cultural Data Profile


How We Figured Our Findings

Our Methodology and Tabular Data and Observations


Our Formula

Our Formula

Return on Fundraising Index:

Total Contributed Revenue/Total Fundraising Expenses (including staff costs)

Total Contributed Revenue

Includes the annual unrestricted, temporarily restricted, and permanently restricted contributions from individuals, corporations, foundations, and government agencies that derive no direct benefit from products or services of the organization in exchange for the funds. It also includes parent organization support, in-kind contributions, net assets released from temporary restriction, revenue from special fundraising events, united arts funding, and tribal and related organization contributions.

Total Fundraising Expenses

All expenses related to fundraising, including fundraising staff salaries and fringe since employee efforts are part of the greater investment in fundraising.


How We Determined Sector

We examined the data to see whether some arts and cultural disciplines hold similar enough characteristics to group them together into Sectors for purposes of our analysis. For example, should all museums be studied together or are there significant enough differences to warrant a separate look at art museums versus other museums (e.g., history, science, children’s museums, etc.) in each analysis? Some sectors clustered but some stand out as unique enough to report on separately. The number of sectors and their clustering may change in future reports as we add data.

We do not assign organizations to arts disciplines, they assign themselves. Organizations self-identify according to the National Taxonomy of Exempt Entities (NTEE), which is a classification system to identify nonprofit organization types. The NCCS website gives an excellent summary description of what NTEEs are and how they came about. Organizations report their NTEE when filing their IRS 990 and they report it as part of the CDP survey. If an organization has a parent organization, we opted for their arts discipline NTEE (e.g., performing arts center) rather than their parent organization’s NTEE (e.g., university), if available. “Arts and Culture” is one of the NTEE’s 10 major groups of tax-exempt organizations (the “A” category), and within Arts and Culture there are 10 subcategories that contain 30 additional subdivisions.

We came up with 11 distinct categories of arts and cultural sectors.

•  Arts Education: Arts Education/Schools (A25) and Performing Arts Schools (A6E)
•  Art Museums: Art Museums (A51)
•  Community: Arts, Cultural Organizations – Multipurpose (A20), Cultural & Ethnic Awareness (A23), Folk Arts (A24), Arts & Humanities Councils/Agencies (A26), Community Celebrations (A27), Visual Arts (A40)
•  Dance: Dance (A62) and Ballet (A63)
•  Music: Music (A68), Singing & Choral Groups (A6B), and Bands & Ensembles (A6C)
•  Opera: Opera (A6A)
•  Performing Arts Centers: Performing Arts Centers (A61)
•  Symphony Orchestra: Symphony Orchestras (A69)
•  Theater: Theater (A65)
•  Other Museums: Museums & Museum Activities (A50), Children’s Museums (A52), History Museums (A54), Natural History & Natural Science Museums (A56), and Science & Technology Museums (A57)
•  General Performing Arts: Performing Arts (A60)

One additional category — Miscellaneous — captures all organizations that did not fit into one of the categories above. This sector includes everything from Film Festivals to Humanities, Historical, and Arts Service Organizations.  

The Make-up of Our 5 Years of Data by Sector


How We Determined Size

Size matters. We would expect that small organizations face different pressures or challenges than medium-sized organizations, which in turn perform differently than large organizations. 

Rather than prescribe arbitrary cut-off points for assigning organizations into small, medium, and large categories based on their total expenditures, we turned to the data to tell us the point in each sector at which performance outcomes differ depending on the organization’s budget size — i.e., where the performance change point lies. To tease this information out of the data, we analyzed unrestricted contributed revenue, total program expenses, and total in-person attendance. It turns out that arts and cultural sectors have different change points. With the addition of new data and new organizations over time, these change points may shift in future reports. Here are the budget ranges of small, medium and large, defined for — and by — organizations in each arts and cultural sector in our dataset.

The Make-up of Our 5 Years of Data:

Arts and Cultural Sectors by Size

Arts Sector Small Medium Large

Arts Education 

$182,265 or less

$182,266 - $1,486,102

$1,486,103 or more

Art Museums 

$2,156,010 or less

$2,156,010 - $16,749,562

$16,749,563 or more


$207,353 or less

$207,354 - $1,426,565

$1,426,566 or more

Dance Companies 

$161,817 or less

$161,818 - $1,777,676

$1,777,677 or more


$122,604 or less

$122,605 - $681,362

$681,363 or more

Opera Companies 

$364,780 or less

$364,781 - $4,888,184

$4,888,185 or more

Performing Arts Centers 

$755,135 or less

$755,136 - $4,928,483

$4,928,484 or more

Symphony Orchestras 

$328,930 or less

$328,931 - $3,820,994

$3,820,995 or more


$205,995 or less

$205,996 - $1,825,000

$1,825,001 or more

Other Museums 

$907,455 or less

$907,456 - $8,684,543

$8,684,544 or more

General Performing Arts 

$190,070 or less

$190,070 - $1,623,261

$1,623,262 or more


How We Determined Geographic Market Clusters

Rather than show the data for every city for which we have CDP and TCG data, we do so for 9 clusters of markets. We all have a hunch about which other markets are similar to ours, but cluster analysis allows the data to tell us what markets are similar to one another given a set of traits.

The characteristics we chose for determining similar markets were population, region, density of arts and cultural organizations in each sector, cultural policy (reflected by state grant dollars in the market), and median income in the community. This doesn’t mean that within each sector there won’t be some city-to-city variance on different traits, or that an individual organization’s experience won’t be different from that of the rest of the organizations in its market.

Five very large markets (including the combination of Washington-Arlington-Alexandria and Bethesda-Rockville) stand alone. These five are sufficiently dissimilar that they don’t cluster with any other markets. Four additional clusters of markets emerged. The composition of the market clusters will likely change over time and new clusters will emerge as we incorporate new data from organizations already in our dataset as well as data from organizations in additional states as the CDP expands its reach.

We focus on the geographic trade areas relevant to the arts and cultural organizations for which we have data. For a complete explanation on how we determined the geographic areas relevant to arts and cultural organizations in each market, see the section on Building a Spatial Model. We report on markets according to their Core Based Statistical Area (CBSA), a U.S. geographic area defined by the Office of Management and Budget. The averages we report here are for all organizations.

The population of some markets is more densely concentrated (think dense, high-rise living) than others. The fact that the population is more spread out does not necessarily mean that the city’s arts and cultural organizations are spread out. In some cases they are, but not always. For example, the numbers tell us that in Los Angeles, the population and arts organizations are more or less equally dispersed geographically and that the arts organizations in New York are more concentrated in Manhattan than the population, which spills out into the surrounding boroughs. In San Francisco, three-quarters of the total population fall into the trade area of an arts organization. What we care most about is what’s going on in the organization’s trade area.

When smaller, lower-density markets are located next to larger, higher-density markets, the spatially-adjusted population and competition numbers can be larger than the local numbers. In other words, the size of the trade area for the smaller market can exceed the size of its local market. This is true for customers but even more so for competition. Arts patrons and managers in smaller markets recognize the competition from arts organizations in nearby, larger markets. This is evident in the numbers for the very small markets like Akron, OH (40 miles from Cleveland), Ann Arbor, MI (40 miles from Detroit), and Santa Cruz, CA (30 miles from San Jose and 70 miles from San Francisco). The trade area for the typical organization in these markets features a population of 206,000 people (79% of the average population) and 41 nonprofit arts and cultural organizations (110% of the average number in the immediate market) because their trade area picks up the neighboring big city.

The Traits of the Market Clusters reveal distinct differences in arts and culture dollar activity per capita, the average number of arts and cultural organizations, and average budget size.

What is a KIPI?

A KIPI is the mojo that sets a high performing organization apart from others. Intangible aspects like good decision-making, artistic and managerial expertise, reputation and relationships, intellectual capital, and the quality of the work force all influence an organization’s performance. We call them KIPIs, or Key Intangible Performance Indicators. Because these traits are, by nature, intangible, we cannot easily observe and measure them. And yet we all know how important they are. By using a statistical technique that we call “high performance frontier analysis,” we can estimate how much these intangibles play a role in setting an organization apart from others. This is a method that has helped many other industries understand high performance and the best practices that drive it.

We start by creating a level playing field, much like you see in golf, where the tees are staggered to give men, women, and seniors a more equal chance at achieving the same score. For arts and cultural organizations, we adjust the playing field for numerous organizational characteristics, like budget size and age, since we know that older and larger organizations tend to have higher performance on many performance measures. The organization’s community also plays a role, too, so we adjust the starting point for those characteristics, too.

Even when the playing field is as level as we can get it, organizations still perform differently than one another. That’s where the intangibles come in. Going back to the golf analogy, it’s accounting for the fact that one golfer is simply a better golfer than another so, all else being equal, she scores better. With KIPIs, we can estimate just how much of performance was due to expertise by measuring how far a score is from what we’d expect it to be given the organization’s operating characteristics and conditions. Moving forward, we will begin to explore and understand what the secret is to success for high-performing organizations for those who want to achieve similar results. Not everyone will want high performance on every measure. Each organization will have its own sense of priorities.

The last element that we have to account for is that some differences in performance are random. One of our golfers may have teed off earlier than the other golfer and played in morning fog. An inexperienced golfer can hit a rock near the green and end up getting a lucky bounce into the hole. No one can see what awaits them around a dog leg the first time playing a course. Even understanding the impact of expertise isn’t enough to fully understand what may be going right or wrong. Some performance outcomes are relatively easy and others are very difficult to explain.

Want to see a more detailed answer to “what is a KIPI?” »

Arts & Culture Ecosystem

The Arts & Culture Ecosystem features a complex and interdependent set of relationships among: 1) arts organizations; 2) their communities, reflecting the people who live there, the artists and arts and cultural organizations, and local complementary or substitute businesses and organizations; and 3) the cultural policies that influence the production and consumption of arts and culture (see Figure 1).

Figure 1: Modeling the Arts & Culture Ecosystem


To understand what drives the performance of individual arts organizations that reside in distinct communities around the country, we attempt to model all of these different factors. Doing so requires collecting, integrating, and aggregating data from a variety of sources. At present, our data collection covers fiscal years 2007-2012 and our models and results focus on performance in 2008-2012, with data from 2007 acting as a baseline.

Building a Spatial Model: Arts & Cultural Organizations and a Sense of Place »

Arts and Cultural Organization Data

We have arts and cultural organization data from three distinct sources:

By cross-referencing these distinct data sources, we have identified 55,449 unique arts and cultural organizations that reported activity during fiscal years 2007-2012. These 55,449 organizations form our Organizational Index database, which includes addresses, longitudes, latitudes, and overlapping organization identification numbers when an organization appears in multiple datasets. We went line-item by line-item in the organizational surveys to match responses to the same question asked in multiple surveys, determining whether the survey question was asking for identical information or whether it would be possible to create exact equivalents with the information available.

As discussed in the section on How We Determined Geographic Market Clusters, the longitudes and latitudes allow us to model the geographic proximity of arts and cultural organizations to each other, to other complementary or substitute business activities (e.g., hotels and restaurants), and to potential audiences that live within the organization’s trading radius.

The organizational data sources vary in terms of population coverage and in terms of data completeness. Data from the National Center for Charitable Statistics (NCCS), which collects and disseminates data from IRS 990 tax form filings, provides the most complete coverage. The number of arts and cultural organizations filing IRS form 990s varies each year, ranging from a low of 38,861 in 2007 to 42,550 in 2011. CDP provides the most complete data, collecting more than 1200 data points for individual arts organizations on an annual basis. CDP’s current coverage is 13 states and the District of Columbia. From 2007-2012, the CDP data represent approximately 30,000 individual records for some 15,000 organizations. Some organizations respond to the CDP survey only once; perhaps some of these organizations no longer exist. Other organizations have responded 2-3 years, reflecting the roll-out of CDP’s services over time. And we have detailed CDP data for many organizations for 4-6 years.

We use the organizational data for two purposes.

  1. To model Arts & Cultural Organizations’ activities, practices, decisions, and outcomes, as depicted in Figure 1. Only the CDP and TCG data are comprehensive enough for this purpose. Because TCG data are limited to a single arts sector, our Arts Ecology modeling efforts tend to focus on CDP-covered markets.

  2. To model total arts and cultural activity at the Community level, as depicted in Figure 1. Some measures appear in all three data sources. When that occurs, our default is to use the CDP measure if it exists. If not, we then use the TCG measure. Finally, we use the IRS measure. We combine four measures of total arts and cultural activity in the Community, specifically Total Assets, Total Expenses, Total Contributed Revenue and Total Program Revenue. We also incorporate a measure of the number of organizations in each arts and culture sector.

The resulting company database features more than 230,000 unique records for the five-year (2008-2012) period -- more than 46,000 organizations per year. We modeled the Arts and Culture Ecosystems nearly 300 metropolitan and micropolitan statistical areas. In 2012, these markets represented 69% of the US population. Our coverage will increase with time, and the findings presented in this report should be interpreted within the context of our current reach and coverage.

Community Data

As noted above, we used Arts and Cultural Organization data to model total arts activity in the Community. We also collected Census Bureau data to create a more complete model of the Arts Ecology at the Community level. These Census Bureau measures include:

  • Arts-related estimates of the number of arts and entertainment organizations, number of employees at arts and entertainment organizations, and number of independent artists;

  • Leisure complements & substitutes: e.g., number of hotels, restaurants, cinemas, and sports teams.

  • Individual-level estimates: for example, total population, per capita income, the percentage of individuals with college degrees, and the percentage of individuals in the labor force;

  • Household-level estimates: for example, percentage of households with income greater than $200,000;

We included data from the Internet Broadway database so that we can examine the effects of arts-related tourism in New York since it is such a large anomaly in the arts and culture ecosystem.

The Community data estimates were collected on an annual basis and geocoded by longitude and latitude at the census tract or zip-code level. These measures combined to create a Spatial Model with 215,000 records, representing data for roughly 40,000 zip codes over five years. We did this because arts organizations don’t exist in a vacuum. Geocoding lets us match each organization to its local market and examine how much that market’s characteristics affect the organization, and in what ways.

Cultural Policy Data

We model the effect of Cultural Policy using measures of grant-making activity from federal and state agencies, specifically:

  • Using data from the National Endowment for the Arts and Institute of Museum and Library Services, we incorporate the number of grants and level of Federal funding for the Community.

  • Using data from the National Association of State Arts Agencies, we incorporate the number of grants and level of State funding for the Community.

Tabular Data and Observations

Overall Trends 2014 - 2017

RETURN ON FUNDRAISING TREND (1,888 ORGANIZATIONS) 2014 2015 2016 2017 2014-2017 change 2014-2017 change, adjusted for inflation
Total Contributed Revenue/Fundraising Expenses (incl. Personnel) $8.80 $8.66 $9.04 $8.56 -2.7%  
Ave. Total Contrib. Rev./ $1,377,720 $1,381,534 $1,405,706 $1,361,188 -1.2% -5.9%
Ave. Fundraising Expenses $156,568 $159,568 $155,415 $158,982 1.5% -3.3%
Ave. Dev. Salary Expense $85,250 $89,692 $95,118 $99,193 16.4% 10.8%
Ave. Staff Comp. as a % of Total Fundraising Expenses 54.4% 56.2% 61.2% 62.4%    
  • Organizations are spending less on fundraising, and the returns generated per dollar spent on fundraising are lower. Total fundraising expenses decreased by 3.3% while total contributed revenue fell by 5.9% from 2014 to 2017, after adjusting for inflation.
  • Organizations spent more over time on fundraising personnel and far less over time on non-personnel fundraising expenses. Development compensation expense growth exceeded overall fundraising expense growth. The average organization shifted from allocating 54.4% of fundraising expenses to staff to an allocation of 62.4%, with the percentage increasing annually. The old saying in fundraising is that people give to people, so it makes sense to invest in personnel for successful relationship cultivation and development.


Sector Data for 2017

Return on Fundraising Trend Arts Education Art Museums Community Dance Music Opera PACs Symphony Orchestras Theater Other Museums General Performing Arts
Total Contributed Revenue/Fundraising Expenses (incl. Personnel) $8.77 $8.38 $10.53 $8.81 $7.75 $9.53 $9.90 $8.42 $7.28 $8.85 $6.13
Avg. Total Contrib. Rev./ $916,458 $8,404,549 $423,917 $601,646 $247,889 $4,187,026 $2,793,701 $1,597,164 $853,467 $5,055,241 $665,467
Avg. Fundraising Expenses $104,443 $1,002,963 $40,272 $68,253 $32,003 $439,281 $282,154 $189,738 $117,179 $571,263 $108,528

Sector, Trends 2014 - 2017

  2014 2015 2016 2017 2014-2017 change 2014-2017 change, adjusted for inflation
Arts Education $8.06 $7.14 $10.03 $9.22 14.4%  
Ave. Total Contributed Rev/ $816,534 $770,348 $1,097,954 $1,114,788 36.5% 30.0%
Ave. Fundraising Expenses (incl. staff) $101,320 $107,869 $109,424 $120,904 19.3% 13.6%
Art Museums $12.32 $10.65 $10.89 $8.52 -30.9%  
Ave. Total Contributed Rev/ $13.054,204 $11,370,364 $12,356,064 $9,637,143 -26.2% -29.7%
Ave. Fundraising Expenses (incl. staff) $1,059,382 $1,067,263 $1,134,836 $1,131,486 6.8% 1.7%
Community $7.81 $7.37 $10.78 $10.07 28.8%  
Ave. Total Contributed Rev/ $394,584 $387,625 $414,297 $433,910 10.0% 4.7%
Ave. Fundraising Expenses (incl. staff) $50,509 $52,600 $38,441 $43,108 -14.7% -18.7%
Dance $8.82 $8.39 $8.67 $8.69 -1.4%  
Ave. Total Contributed Rev/ $701,278 $713,727 $655,258 $687,803 -1.9% -6.6%
Ave. Fundraising Expenses (incl. staff) $79,527 $85,061 $75,552 $79,140 -0.5% -5.2%
Music $6.29 $6.41 $8.04 $7.49 19.0%  
Ave. Total Contributed Rev/ $227,729 $253,988 $284,861 $281,732 23.7% 17.8%
Ave. Fundraising Expenses (incl. staff) $36,186 $39,608 $35,435 $37,618 4.0% -1.0%
Opera $8.42 $8.21 $9.74 $9.49 12.7%  
Ave. Total Contributed Rev/ $4,856,568 $5,034,544 $4,678,355 $5,017,020 3.3% -1.6%
Ave. Fundraising Expenses (incl. staff) $576,514 $613,298 $480,117 $528,518 -8.3% -12.7%
PACs $9.91 $9.47 $8.32 $9.23 -6.8%  
Ave. Total Contributed Rev/ $2,959,229 $3,034,518 $3,012,996 $2,874,779 -2.9% -7.5%
Ave. Fundraising Expenses (incl. staff) $298,738 $320,387 $362,090 $311,349 4.2% -0.7%
Symphony Orchestras $8.44 $9.22 $7.91 $8.48 0.5%  
Ave. Total Contributed Rev/ $2,088,437 $1,976,166 $1,647,254 $1,776,272 -14.9% -19.0%
Ave. Fundraising Expenses (incl. staff) $247,478 $214,220 $208,246 $209,517 -15.3% -19.4%
Theatre $7.61 $7.61 $7.93 $7.35 -3.5%  
Ave. Total Contributed Rev/ $906,932 $961,086 $991,299 $961,089 6.0% 0.9%
Ave. Fundraising Expenses (incl. staff) $119,142 $126,373 $125,022 $130,785 9.8% 4.5%
Other Museums $6.92 $8.97 $8.36 $8.65 25.0%  
Ave. Total Contributed Rev/ $4,579,645 $5,980,863 $5,526,120 $5,681,419 24.1% 18.2%
Ave. Fundraising Expenses (incl. staff) $661,825 $666,952 $660,800 $656,850 -0.8% -5.5%
General Performing Arts $6.09 $5.85 $6.13 $6.11 0.4%  
Ave. Total Contributed Rev/ $753,234 $751,352 $820,008 $807,164 7.2% 2.1%
Ave. Fundraising Expenses (incl. staff) $123,747 $128,529 $133,788 $132,034 6.7% 1.6%
  • Total contributed revenue decreased for 5 out of total 11 sectors from 2014 to 2017 in inflation-adjusted figures. Art Museums had a 29.7% decrease in their contributed revenue over time while Arts Education organizations had an increase of 30%. One organization skewed the average high for the Art Museum sector in 2014 and 2015. However, eliminating this organization from the analyses would still leave contributed revenue 16% lower in 2017 than in 2014 for remaining Art Museums. The Art Museum sector was the only one where an increased investment in fundraising resulted in lower total contributed revenue.
  • Orchestras had roughly the same level of decrease in both total contributed revenue and fundraising expenses, leaving the 2017 level of Return on Fundraising very similar to that of 2014 since the index is a ratio.
  • In the Community, Music and Other Museums sectors, organizations tended to spend less on fundraising but reap higher returns in total contributed revenue over time.
  • Theater companies spent more on fundraising and achieved some growth in total contributed revenue, but not commensurate with the increased level of investment.
  • Fundraising expenses were higher in 2017 than in 2014 in inflation-adjusted figures for these 4 sectors: Arts Education, Theatre, Art Museums and General Performing Arts. The average organization in every sector allocated a greater proportion of fundraising expenses to staff over time.
  • Arts Education experienced the largest growth in average amount spent on development compensation over the 4 year period at 27.4%. Growth in development compensation for Opera companies fell 2.6% shy of inflation (not shown in the table) – the only sector to see a decrease.


Size Data for 2017

  Small Medium Large
Total Contributed Revenue/Fundraising Expenses $16.57 $10.06 $8.06
Ave. Total Contrib. Rev./ $75,598 $657,868 $6,219,523
Ave. Fundraising Expenses $4,561 $65,403 $771,617

Size Trends 2014 - 2017

  2014 2015 2016 2017 2014-2017 change 2014-2017 change, adjusted for inflation
Small $12.00 $13.04 $15.88 $16.36 36.3%  
Ave. Total Contributed Rev/ $77,479 $79,883 $81,932 $79,871 3.1% -1.8%
Ave. Fundraising Expenses $6,456 $6,126 $5,161 $4,883 -24.4% -28.0%
Medium $8.26 $8.21 $11.63 $10.27 24.3%  
Ave. Total Contributed Rev/ $655,606 $622,406 $805,343 $683,582 4.3% -0.7%
Ave. Fundraising Expenses (incl. staff) $79,395 $75,834 $69,262 $66,588 -16.1% -20.1%
Large $8.86 $8.67 $8.33 $8.06 -9.0%  
Ave. Total Contributed Rev/ $8,119,000 $7,497,244 $6,938,594 $6,771,023 -16.6% -20.6%
Ave. Fundraising Expenses (incl. staff) $916,625 $864,390 $833,358 $839,931 -8.4% -12.7%
  • Average total contributed revenue and fundraising expenses decreased for organizations of every size from 2014 to 2017. Large organizations had the largest decrease in total contributed revenue at -20.6%. Small organizations had the largest decrease in fundraising expenses at -28.0%.
  • Both Small and Medium organizations’ cut-backs in fundraising expenses had only minimal effect on the level of total contributions, leaving them higher in absolute dollars but lower in inflation-adjusted figures. The reverse was true for Large organizations.
  • Small organizations tend to spend less on fundraising personnel compensation as a percent of total fundraising expenses: 49% for Small organizations, 62%-64% annually for Medium and Large organizations (not shown in the table). Small organizations tend to be far more reliant on volunteer labor than their larger counterparts.


Geography Data for 2017

Return on Fundraising Trend New York-White Plains-Wayne, NY-NJ Los Angeles-Long Beach-Glendale, CA Chicago-Naperville-Arlington Hgts, IL San Francisco-Redwood City-South SF, CA Washington-Arlington-Alexandria; Bethesda-Rockville Larger Markets
Medium Markets
Small Markets
Very Small Markets
Total Contributed Revenue/Fundraising Expenses (incl. Personnel) $8.73 $7.61 $7.27 $7.92 $9.40 $9.31 $8.67 $7.73 $9.98
Avg. Total Contrib. Rev./ $4,039,254 $581,902 $866,612 $2,056,668 $766,308 $1,093,204 $1,133,234 $517,011 $560,372
Avg. Fundraising Expenses $462,757 $76,464 $119,283 $259,689 $81,560 $117,464 $130,648 $66,909 $56,144

Geography, Trends 2014 - 2017

  2014 2015 2016 2017 2014-2017 change 2014-2017 change, adjusted for inflation
New York-White Plains-Wayne, NY-NJ $10.48 $11.17 $8.96 $8.64 -17.6%  
Ave. Total Contrib. Rev./ $5,784,621 $6,206,118 $5,048,625 $5,091,515 -12.0% -16.2%
Ave. Fundraising Expenses $551,837 $555,361 $563,285 $589,390 6.8% 1.7%
Los Angeles-Long Beach-Glendale, CA $6.91 $6.99 $7.78 $7.29 5.6%  
Ave. Total Contrib. Rev./ $417,638 $456,615 $520,876 $560,709 34.3% 27.9%
Ave. Fundraising Expenses $60,481 $65,302 $66,990 $76,878 27.1% 21.1%
Chicago-Naperville-Arlington Heights, IL $7.50 $7.89 $7.64 $7.11 -5.2%  
Ave. Total Contrib. Rev./ $1,349,061 $1,325,934 $1,193,323 $1,031,433 -23.5% -27.2%
Ave. Fundraising Expenses $179,915 $168,066 $156,239 $145,158 -19.3% -23.2%
San Francisco-Redwood City- South SF, CA $5.65 $5.37 $6.53 $7.92 40.2%  
Ave. Total Contrib. Rev./ $1,827,806 $1,711,137 $1,809,181 $2,397,559 31.2% 24.9%
Ave. Fundraising Expenses $323,397 $318,532 $277,256 $302,579 -6.4% -10.9%
Washington-Arlington-Alexandria; Bethesda-Rockville-Fredericksburg, DC-VA $6.78 $6.86 $9.34 $9.55 40.9%  
Ave. Total Contrib. Rev./ $640,211 $690,129 $849,137 $880,186 37.5% 30.9%
Ave. Fundraising Expenses $94,454 $100,546 $90,930 $92,133 -2.5% -7.1%
Larger Markets $9.52 $7.88 $8.71 $9.41 -1.2%  
Ave. Total Contrib. Rev./ $1,397,184 $1,158,330 $1,269,291 $1,331,327 -4.7% -9.3%
Ave. Fundraising Expenses $146,748 $146,940 $145,665 $141,513 -3.6% -8.2%
Medium Markets $9.75 $9.27 $10.52 $8.63 -11.5%  
Ave. Total Contrib. Rev./ $1,271,447 $1,264,633 $1,470,281 $1,225,052 -3.6% -8.2%
Ave. Fundraising Expenses $130,399 $136,357 $139,801 $141,902 8.8% 3.6%
Small Markets $8.99 $7.83 $7.16 $7.77 -13.6%  
Ave. Total Contrib. Rev./ $611,555 $607,373 $559,804 $606,452 -0.8% -5.6%
Ave. Fundraising Expenses $68,040 $77,521 $78,145 $78,078 14.8% 9.3%
Very Small Markets $8.95 $8.64 $10.80 $10.48 17.1%  
Ave. Total Contrib. Rev./ $530,563 $571,779 $640,696 $637.454 20.1% 14.4%
Ave. Fundraising Expenses $59,291 $60,821 $59,328 $60,821 2.6% -2.3%
  • Average total contributed revenue was higher over time in Los Angeles, San Francisco, DC-VA, and Very Small Markets while it dropped in all other markets.
  • The greatest growth in total contributed revenue was in Washington, DC where it rose to 30.9% from 2014 to 2017, followed by San Francisco with growth of 24.9%.
  • Average fundraising expenses decreased most over time in Chicago, whereas the biggest growth in this area occurred in Los Angeles.
Percentage of Fundraising Expenses allocated to Fundraising Personnel Compensation, per Market & Year
Market 2014 2015 2016 2017
NYC 57% 60% 65% 65%
LA 71% 71% 77% 67%
CHICAGO 45% 49% 59% 61%
SF 44% 45% 53% 52%
DC 52% 53% 58% 56%
Large 56% 54% 58% 65%
Medium 60% 61% 62% 64%
Small 61% 59% 61% 59%
Very Small 51% 61% 65% 69%
  • LA organizations had the highest percentage of fundraising expenses allocated to fundraising staff compensation from 2014 to 2016, which then fell more in line with the other markets in 2017.
  • San Francisco organizations have the lowest percentage of fundraising expenses allocated to fundraising staff compensation every year from 2014 to 2017.

Return To Main Page

Discover more in the Unrestricted Contributions Index and By Source Indices study.

Fundraising Report Home

The State of the Arts: Our Past Reports

See trends and resources from our reports on fundraising, bottom line, expenses, marketing, and staffing. We care about numbers, not for their own sake, but because we believe that healthier arts and cultural organizations will have more resources to invest in artistic and cultural offerings and in community engagement.

See Past Reports

Run Your Reports In The Cultural Data Profile