Research Reports
Featured Research
Discover IA industry trends, software and education patterns among IAs, including our latest surveys:
Salary Survey
The Information Architecture Institute (IAI) conducts an annual salary survey to capture data about the demographics, experience level, compensation, and organization characteristics of information architecture practitioners. It is meant to serve as a barometer for the state of the profession and help professionals to understand and explain their relative value to employers. The information was collected in good faith to serve our community, not to try to identify individuals and their personal compensation. Salary survey data is kept separate from member lists.
The most recent Salary Survey can be found online. Please send any feedback or requests to info@iainstitute.org
The 2014 Salary Survey had several goals, including:
- Increase response rate from prior years
- Elicit greater number of international responses
- Focus the survey on demographics and compensation
- Increase accuracy of compensation results, particularly for the upper salary ranges
- Increase awareness and sensitivity for gender identity
In an effort to reach these goals several significant changes were made to the 2014 survey. The overall number of questions was reduced, which entailed removing sections assessing on-the-job skills, benefits and holidays, and previous positions and education programs. We also simplified the question language to make it easier for people to complete the survey.
Methodology
We conducted the 2014 IAI Salary Survey from March 26 to April 8, 2015. As in past years, we invited members of the IA Institute, IxDA and sigia-l to participate and promoted a link to the survey through IAI newsletters and Twitter account. In total, 642 responses were collected. Respondents who did not enter a salary range were removed for salary calculation purposes.
You may download the expanded results from IA Institute. We removed zip / postal code data from the results due to concerns about the privacy of individuals in places where a small, easily identifiable population of respondents live.
We collected survey responses using a Surveymonkey form. The survey had 16 questions covering age, gender, education, experience, total compensation, freelance rates, management, and teaching levels. We collected job titles as open response to gain a broader sense of how people are professionally identified.
All figures are represented in US dollars. The survey included a link to a currency converter for respondents using non-US currency. To maintain comparability to prior iterations of the survey, we asked respondents to choose a salary range. This makes it impossible to estimate a true average or median salary. In our analysis, we estimated the median for various data points using the salary range and then averaging that figure. To gain a better sense of upper ranges, we included ranges up to $250,000.
We calculated mean salary in two ways: including and eliminating the "More than $250,000" and "Less than $10,000" groups, which do not have a midpoint. We present median salary estimates, based on midpoints, for comparison purposes, but it is better to read the survey results in terms of a percentage that falls within a range rather than a specific salary.
In an effort to gain greater precision, we also asked respondents to provide their salary to the nearest $1000. Though this method had fewer responses, calculations were made and are presented for an additional comparison point.
About the Information Architecture Institute
The Information Architecture Institute (IAI - formerly The Asilomar Institute for Information Architecture ) is a 501(c)6 professional organization that supports the practice of Information Architecture. Through education, advocacy, services, and social networking, IAI supports a community of practitioners, leading the way in demonstrating the value of information architecture to the world at large, and providing a framework for members to improve their skills and enhance their professional standing.
Results Summary
- 642 responses from 33 countries [54 incomplete]
- Mean salary increased 4.4% (non-adjusted US dollars) from 2013
- Modal salary range: $100,000 - 109,999
- Mean salary using midpoints: $101,968
- Mean salary excluding top/bottom ranges: $100,234
- Mean salary based on responses to nearest $1000 [481 responses]: $105,800 (median: $99,000)
- Mean US salary spreads between $144,655 and $91,471 according to region
- Top: Northern California = $144,655
- Bottom: Southwest = $91,471
- Mean salary by gender: Female = $99,893 Male = $104,079
- Bachelor’s represent 34.1%, Master’s 44.1%, Doctorate 2.8%
- Mean salary by education: Bachelor’s = $100,431, Master’s = $103,647, Doctorate = $108,125
- Freelance payment type (removing n/a and skips for 130 responders) [could check all that apply]
- Hourly: 101, 77.7%
- Per diem: 16, 12.3%
- Per project: 38, 29.2%
- Commission: 2, 1.5%
- Equity: 3, 2.3%
- Other: 3 people mentioned working by monthly rate/retainer
- Hourly range: $18 – 350
- Hourly median: $90 ($99.15 mean)
- Per diem range: $150 – 2500
- Per diem median: $670 (mean $774)
- United States: 478 Respondents | 74.5%
- Canada: 42 Respondents | 6.5%
- UK: 36 Respondents | 5.6%
- Australia: 8 Respondents | 1.2%
- Brazil: 7 Respondents | 1.1%
- Germany: 7 Respondents | 1.1%
- Japan: 6 Respondents | 0.9%
- Netherlands: 5 Respondents | 0.8%
- France: 5 Respondents | 0.8%
- Mexico: 4 Respondents | 0.6%
- Establishment of the value and maturity of the practice
- Growth of careers of survey participants (which skews towards more experience)
- General salary gains within the tech industry as a whole.
- For 2014, the increase may also reflect the extension of the salary ranges to gather more data points from higher-ranges.
- Most meaningful geographical data for analyses (country, city, region, etc)
- Easiest way to gather location data without infringing on privacy concerns
- Expand the conversation on gender identity to be more sensitive and inclusive
- Continue international outreach to gather more representative data
- Increase outreach to early-career practitioners for more representative data
- 2013 Salary Survey
- 2012 Salary Survey
- 2011 Salary Survey
- 2010 Salary Survey
- 2009 Salary Survey
- 2008 Salary Survey
- 2007 Salary Survey
- 2006 Salary Survey
- 2005 Salary Survey
- No survey released in 2004
- 2003 Salary Survey
Freelance rates (not excluding “outliers” and using midpoints when range given):
Respondent Demographics
International
Other countries responding: Denmark, India, Spain, Sweden = 3 each; Italy, Norway, Switzerland, Turkey = 2 each; Single responses from (listed alphabetically): Argentina, Armenia, Austria, Belgium, Colombia, Greece, Ireland, Kazakhstan, Maldives, Singapore, Slovenia, South Africa, UAE, Ukraine, and Uzbekistan.
Responses were received from 33 countries. As with prior years, the United States resulted in the overwhelming majority, followed by other English-speaking nations: Canada, UK, and Australia.
United States
US Responses by State
Respondents represented 33 states and Washington DC, with few responses from the Mountain West region and the southern states, and no responses from Alaska and Hawaii.
US Responses by Region
| REGION | RESPONSES | % |
|---|---|---|
| Midwest | 134 | 28.5 |
| Northeast | 108 | 22.9 |
| Mid-Atlantic | 87 | 18.5 |
| Northern California | 32 | 6.8 |
| Pacific Northwest | 32 | 6.8 |
| Southeast | 27 | 5.7 |
| Southern California | 23 | 4.9 |
| Southwest | 19 | 4.0 |
| Mountain West | 9 | 1.9 |
Within the US, the Midwest produced the most responses. The east coast (Northeast, Mid-Atlantic, Southeast), with 47.1% of responses, was more represented than the west coast (Northern and Southern California, Pacific Northwest), with only 18.5% of responses.
Age
| AGE RANGE | RESPONSES | PERCENTAGE (%) |
|---|---|---|
| Younger than 21 | 1 | 0.2 |
| 21-25 | 26 | 4.1 |
| 26-30 | 99 | 15.4 |
| 31-35 | 146 | 22.8 |
| 36-40 | 123 | 19.2 |
| 41-45 | 120 | 18.7 |
| 46-50 | 68 | 10.6 |
| 51-55 | 30 | 4.7 |
| 56-60 | 20 | 3.1 |
| 61-65 | 7 | 1.1 |
| Older than 65 | 1 | 0.2 |
Most of the respondents (60.7%) were between the ages of 31 and 45.
Education
| LEVEL | RESPONSES | PERCENTAGE (%) |
|---|---|---|
| High School | 10 | 1.6 |
| Some college (Associate’s / Tech. Certificate) | 48 | 7.5 |
| Bachelor's degree | 218 | 34.1 |
| Some graduate school | 53 | 8.3 |
| Master’s degree | 282 | 44.1 |
| Doctorate | 18 | 2.8 |
| Other | 10 | 1.6 |
The community is well-educated, with 89.4% of respondents having a Bachelor’s degree or higher, and 46.9% of respondents having an advanced degree.
Industry Experience
Number of years
| Number of Years | Responses | % |
|---|---|---|
| < 1 | 21 | 3.4 |
| 1 - 5 | 168 | 27.2 |
| 6 - 10 | 172 | 27.8 |
| 11 -15 | 140 | 22.7 |
| 16 - 20 | 88 | 14.2 |
| > 20 | 29 | 4.7 |
The industry experience exhibits a bell-shaped curve, but weighted toward greater experience.
Position Level
| LEVEL | RESPONSES | % |
|---|---|---|
| Executive/CEO/President/Owner | 39 | 6.3 |
| Senior Management/VP/Director | 84 | 13.7 |
| Experienced/Senior Level | 293 | 47.6 |
| Experienced/Mid Level | 154 | 25.0 |
| Entry Level/Junior | 36 | 5.9 |
| Intern/Student | 6 | 1.0 |
| Administrative Staff | 3 | 0.5 |
Position level also trends towards greater levels, with only 7.3% considering themselves anything other than “experienced” or more.
Position Tenure
| TENURE | RESPONSES | PERCENTAGE (%) |
|---|---|---|
| < 3 months | 51 | 8.3 |
| 3 – 6 months | 67 | 10.9 |
| 7 – 12 months | 112 | 18.2 |
| 1 – 3 years | 263 | 42.7 |
| 4 – 5 years | 55 | 8.9 |
| > 5 years | 68 | 11.0 |
The time spent in current position reflects volatility, with a clear plurality in the 1 – 3 year range. But this could be due to either changing job/company or promotions given the question.
Organization Size
| NUMBER OF EMPLOYEES | RESPONSES | % |
|---|---|---|
| 1 (self-employed / independent / freelance) | 52 | 8.9 |
| 2 - 25 | 89 | 15.3 |
| 26 - 100 | 89 | 15.3 |
| 101 – 250 | 49 | 8.4 |
| 251 – 500 | 65 | 11.2 |
| 501 – 1000 | 38 | 6.5 |
| 1001 – 3000 | 48 | 8.3 |
| > 3000 | 152 | 26.1 |
Respondents predominately came from larger organizations, with 52.1% from places with more than 250 employees, and the largest bracket was greater than 3000 employees.
Skills Application
Management
| NUMBER MANAGED | RESPONSES | % |
|---|---|---|
| 0 | 318 | 54.2 |
| 1 - 5 | 215 | 36.3 |
| 6 - 10 | 37 | 6.3 |
| 11 – 20 | 11 | 1.9 |
| > 20 | 6 | 1.0 |
Respondents overwhelmingly reported managing 5 or fewer people at 90.8%. Taken with the experience levels and organization sizes reported, this suggests that respondents typically work on smaller teams.
Teaching
The clear majority of respondents do not teach (70.1%). Of those who do, they teach workshops and/or continuing education/certificate classes (26.2%).
| Education Level | Responses | % |
|---|---|---|
| Elementary School | 5 | 0.9 |
| High School | 7 | 1.3 |
| Undergraduate | 29 | 5.2 |
| Graduate | 38 | 6.8 |
| Continuing Ed. / Certificate | 36 | 6.4 |
| Workshop | 111 | 19.8 |
| Don’t Teach | 393 | 70.1 |
Salary Range Analyses
Mean Salary by Location: US Region and City
Note: Line thickness reflects relative number of responses for the variable.
As with prior years, the region with the highest mean salary was Northern California, with San Francisco having the highest mean salary per metropolitan area. New York followed per metro area, with the Northeast region in the fourth position. There were many more responses from the Northeast than the other regions ahead of it, which may have skewed the numbers somewhat.
Mean Salary by Age Range
Note: Line thickness reflects relative number of responses for the variable.
Combined, the 51-60 age ranges had the greatest mean salary, which is likely a reflection of, and related to, years of industry experience and career stage. But the older ranges of 61-65+ had lower mean salaries than might be expected. There were also fewer responses in these ranges.
Mean Salary by Education Level
Note: Line thickness reflects relative number of responses for the variable.
Educational attainment does not correlate greatly with mean salary, with “some college” having greater mean salary than a Bachelor’s degree and “some graduate school” less than a Bachelor’s degree. Doctorate degrees and “other” (which often includes post-graduate level work and professional certifications) had the highest mean salaries, though not much higher than Master’s degrees.
Mean Salary by Years of Industry Experience
Note: Line thickness reflects relative number of responses for the variable.
Years of experience has a correlating salary dividend, with each level having noticeable salary gains, particularly in the early career stages.
Note: Line thickness reflects relative number of responses for the variable.
Position level also reflects a strong correlation to salary, with generally sizeable increases noticeable with each step up. Only the “executive / CEO / President / Owner” category did not follow the trend. This difference may be related to lumping “owner” into the group, which would include freelancers of varying levels.
Salary by Gender and Experience
Comparing gender and years of experience with salary ranges shows similar distribution, with females making slightly more with less experience and males making more with greater years of experience.
Salary by Gender and Education
Comparing gender and education in terms of salary ranges reveals similar distributions, with females tending to have higher educational attainment.
IAI Mean Salary Timeline
Survey Responses and Reported Mean Salary by year
Note: Thickness refers to total survey responses, though in some cases in not all respondents included salary information, it is shown for relative participation each year, which may affect results.
Though collection methods for salary data have varied through the years, in general the mean has gained over time. The gains could be the result of several factors:
Conclusions and Future Considerations
The comparisons and calculations presented in the findings include all available data points. As such, international disparities in wages have an affect and considerations of cost of living expenses should be considered. But even with those differences, the industry is in good health in terms of salary, finally regaining lost ground to the 2008 economic downturn.
Given that data collection methods have varied through the years, it is difficult to make longitudinal comparisons for salary trends in terms of gender, education, and experience. Standardizing methods will allow for more meaningful trend analyses going forward.
Other items to consider for future surveys, include:
Appendix A: Visualization Dashboard
Appendix B: History Graphic of IAI Salary Survey
Previous salary surveys:
This page was last modified on March 19, 2014 08:36 AM.