SPSS Statistics is a software package used for statistical analysis. It is now officially named "IBM SPSS Statistics". Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, and collaboration and deployment (batch and automated scoring services).
$99
per month per user
SurveyMonkey
Score 8.2 out of 10
N/A
SurveyMonkey provides free, customizable surveys, and a suite of paid, back-end programs that include data analysis, sample selection, bias elimination, and data representation tools. SurveyMonkey also offers large-scale, enterprise options for companies interested in data analysis, brand management, and consumer focused marketing.
$99
per month
Pricing
IBM SPSS Statistics
SurveyMonkey
Editions & Modules
Base
USD 3,830
one-time fee per user
Standard
USD 8,440
one-time fee per user
Professional
USD 16,900
one-time fee per user
Premium
USD 25,200
one-time fee per user
Monthly subscription
USD 99
per month per user
Annual subscription
USD 1,188.00
per year per user
Team Advantage
$25
per month (billed annually) per user (starting at 3 users)
Team Premier
$75
per month (billed annually) per user (starting at 3 users)
It's probably above Google Surveys and below the other two. I didn't select SurveyMonkey, the company already had it and I made the decision to get an additional license for my work.
I described earlier that the only scenarios where I use SPSS are those where we have legacy projects that were developed in the late 90s or early 2000s using SPSS, and for some reason, the project (data set, scope, etc.) hasn't changed in 24+ years. This counts for 1-2 out of around 80 projects that I run. Whenever possible, I actively have my team move away from SPSS, even when that process is painful.
SurveyMonkey is well suited for external, professional, client-facing forms and complex question types. I've tried generating forms on HubSpot, and it's not nearly as intuitive or clean-looking, and not all question types are supported (e.g. Likert scales). For quick, internal forms that don't need to be as pretty or professional, I find that Google Forms is the quickest and easiest to pull together, especially since it has a single, universal respondent link. If I wanted to embed a link in a mass email, SurveyMonkey doesn't allow multiple respondents to use the same link on my plan.
SPSS has been around for quite a while and has amassed a large suite of functionality. One of its longest-running features is the ability to automate SPSS via scripting, AKA "syntax." There is a very large community of practice on the internet who can help newbies to quickly scale up their automation abilities with SPSS. And SPSS allows users to save syntax scripting directly from GUI wizards and configuration windows, which can be a real life-saver if one is not an experienced coder.
Many statistics package users are doing scientific research with an eye to publish reproducible results. SPSS allows you to save datasets and syntax scripting in a common format, facilitating attempts by peer reviewers and other researchers to quickly and easily attempt to reproduce your results. It's very portable!
SPSS has both legacy and modern visualization suites baked into the base software, giving users an easily mountable learning curve when it comes to outputting charts and graphs. It's very easy to start with a canned look and feel of an exported chart, and then you can tweak a saved copy to change just about everything, from colors, legends, and axis scaling, to orientation, labels, and grid lines. And when you've got a chart or graph set up the way you like, you can export it as an image file, or create a template syntax to apply to new visualizations going forward.
SPSS makes it easy for even beginner-level users to create statistical coding fields to support multidimensional analysis, ensuring that you never need to destructively modify your dataset.
In closing, SPSS's long and successful tenure ensures that just about any question a new user may have about it can be answered with a modicum of Google-fu. There are even several fully-fledged tutorial websites out there for newbie perusal.
Being able to close the survey at a set time without having to remember to do so.
Takes the guess work out of response collecting.
Makes it easy to categorize responses within the same survey. Being able to add tags to open-ended questions makes it easy for us to identify patterns in responses.
An array of survey options and questions.
An all around great product that meets multiple needs.
Can have multiple collectors for the same survey to included manual input.
collaboration - SPSS lacks collaboration features which makes it near impossible to collaborate with my team on analysis. We have to send files back and forth, which is tedious.
integration - I wish SPSS had integration capabilities with some of the other tools that I use (e.g., Airtable, Figma, etc.)
user interface - this could definitely be modernized. In my experience, the UI is clunky and feels dated, which can negatively impact my experience using the tool.
I would like to have more customizable options for branding it to our hospital colors. Some survey options allow you to enter html color codes. SurveyMonkey allows you to change colors and you have to pick from selected options.
Embedding the surveys into a webpage, like WordPress is not as seamless as other services.
Both money and time are essential for success in terms of return on investment for any kind of research based project work. Using a Likert-scale questionnaire is very easy for data entry and analysis using IBM SPSS. With the help of IBM SPSS, I found very fast and reliable data entry and data analysis for my research. Output from SPSS is very easy to interpret for data analysis and findings
Compared to other competitors in the market (including a few I've used internally), if you're looking for a survey application, this one does the job and it's quite inexpensive too. Considering the fact that it comes with a handy mobile application too (on iOS and Android), you also get flexibility thrown in the deal too.
Probably because I have been using it for so long that I have used all of the modules, or at least almost all of the modules, and the way SPSS works is second nature to me, like fish to swimming.
It does everything a survey software should do, and it does it very well. I can't speak for how well it would work for a business that was surveying tens of thousands of people - but for a small business of 50 employees with a couple of thousand clients, it does everything it needs to do.
I have not contacted IBM SPSS for support myself. However, our IT staff has for trying to get SPSS Text Analytics Module to work. The issue was never resolved, but I'm not sure if it was on the IT's end or on SPSS's end
I've never had to contact the SurveyMonkey customer care team directly, but they have a pretty good library of help articles on their website. Everything from designing and executing your survey to account and billing questions. I never had a need for further support from Survey Monkey.
Have a plan for managing the yearly upgrade cycle. Most users work in the desktop version, so there needs to be a mechanism for either pushing out new versions of the software or a key manager to deal with updated licensing keys. If you have a lot of users this needs to be planned for in advance.
I have used R when I didn't have access to SPSS. It takes me longer because I'm terrible at syntax but it is powerful and it can be enjoyable to only have to wrestle with syntax and not a difficult UI.
SurveyMonkey is easier to customize and provides much more in depth analytics. SurveyMonkey also provides better templates providing us with a better presentation to our employees. SurveyMonkey also comes with a more trustworthy platform that ensures confidentiality, which is incredibly important to our employees and means we're getting more reliable results from the surveys.
I found SPSS easier to use than SAS as it's more intuitive to me.
The learning curve to use SPSS is less compared to SAS.
I used SAS, to a much lesser extent than SPSS. However, it seems that SAS may be more suitable for users who understand programming. With SPSS, users can perform many statistical tests without the need to know programming.
The speed at which we can develop, program, execute and generate actual usable results provides significant value, particularly when we need fresh numbers to illustrate a point.
The fact that we can execute a research project so quickly means that new research is always a primary option when we're developing campaigns. That's a huge value proposition.
