In Februrary, Shareable conducted its first reader survey. About 170 of you responded — thank you for your time and contribution!
The reader survey is the first step in a website redesign that Shareable is undertaking this year and Shareable is in the running for a $300,000 grant to redo our site using an open design process.
Below are the results:
Here are some of my observations:
- 22% of respondents heard of Shareable by word of mouth.
- 32% of respondents access Shareable on a smartphone and 14% on a tablet device.
- 93% of respondents have talked with others about sharing in the past month.
- Respondents have used a wide variety of sharing services. The most popular are redistribution sites like Craigslist and eBay. Over half have used cooperative stores and bartering or swapping. Close to half have used crowdfunding and a credit union or mutual savings bank, and over a third have used carsharing, coworking, social travel, and ridesharing services.
- 71% of respondents live in cities, 72% of respondents are age 18-40, and 34% of respondents have an annual household income of under $25,000.
The survey was circulated on this website, on Twitter at @ShareableDesign and Shareable's Facebook page, and by email. This was the easiest way for us to reach our readers, but it also means that the survey was not a random sample. Therefore, we don't know how well respondents' answers would match those of the entire Shareable readership. Despite this, I believe these results are useful for the website redesign process. If you have any thoughts on whether we should — and how we could — use a random (aka probability) sample in future surveys, please weigh in.
I'd like to do a cross-tab analysis of the data by the different types of users — especially those who use the site often, frequently share articles, or talk with many other people about sharing. I'd also like to categorize or analyze the three open-response questions in the survey (questions #5, #10 and #19), but haven't figured out the best way to do that. If you have any suggestions for how to do cross-tabulation or text analysis of this data, or — even better — you might be able to help, please speak up in the comments. I've made the raw data from the survey available in this Google spreadsheet. You can view all the responses in your browser, or download them as a CSV, Excel, or Open Office file if you'd like to play with the data yourself.
If any of the survey results stand out or surprise you, or if you have suggestions of how we might improve future reader surveys, please add your comments. Again, thank you to all of you who took the survey!