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Five Things I’ve Learned About redditors (so far)

This is my reddit avatar. All employees get one
About a month ago, I took a gig to design the user experience of reddit. It’s a pretty exciting challenge!  My first projects have been mostly on mobile, and they’ve been a blast.  Check out our recently released AMA app on iTunes and Android and recently acquired Alien Blue iOS app.

The first step towards better user experience is better understanding of the users, so the quest begins with understanding redditors. And, there’s a lot of them: 6% of all online adults! ((Pew Research: 6% of Online Adults are reddit Users)) Understanding so many people requires attacking the problem at multiple angles.

One of the most direct ways to learn about a large user population is through surveys. The benefit of surveys is that they can be deployed broadly and analyzed statistically.  The main drawback is that they skew results towards the users who choose to complete them.

A few weeks ago, I released a test survey the subreddit ((subreddit: a sub-communities within reddit focused on a specific topic)) called /r/samplesize, which is dedicated to posting and taking surveys for other redditors.  I received 226 responses. Bearing in mind the enormous grain of salt that these results are comprised entirely of self-selecting users, here’s what I learned:

1. Twice as many men responded to the survey than women.

While I don’t know how representative this ratio is of reddit as a whole, this is already far more gender-balanced than previous self-selected surveys from three years ago. ((Who in the World is reddit? Results are in…)) ((I made a basic Reddit Demographic Survey. Let’s find out who we are…))

2. Most active users have been redditors for 1-3 years.

This isn’t too surprising considering the survey was given to a subreddit that only longer-term users would be aware of. However, given the site’s high bounce rate, it’s likely that reddit could improve at welcoming and retaining newer users.  After all, if reddit can’t create core users at a rate at or above dropout (churn) rate, its population will gradually decline.

3. Reading favorite subreddits is redditors’ most valued activity.

I asked users to rank their activities on reddit from not very important to extremely important: here are the responses only for extremely important.  As you can see, reading favorite subreddits was by far most commonly marked as extremely important.  User’s front pages was the second most marked as extremely important, which isn’t surprising since 99.2% of survey respondents have accounts which they use to modify their front page.

4. Users primarily want reddit to entertain them. Their secondary expectation is for community.

Here, I asked “what do you expect of reddit?” with a freeform response.  The tallies are per response rather than per user, such that if a user said she expected “community and humor,” I’d give one tally to community and another to humor.

Wanting reddit to be entertaining isn’t surprising: it’s the front page of the internet, after all.  What’s particularly interesting is how often community and communication were cited as expectations.  Discussion, particularly through comments, was the second most frequently cited expectation.  What’s reflected in “free speech,” “openness,” and “local content” were mainly variations on the idea that reddit content is different primarily because of its community.  Of these, about half of the responses mentioned the value of varied perspective – that reddit provided content and stories that users might otherwise not have found (or answers to questions they were afraid to ask).

5. What frustrates redditors most are other redditors.

For this freeform question, I simply asked redditors what frustrates them about reddit. The majority of responses could be summarized by concern that reddit is or is becoming dominated by negative viewpoints. Most common were concerns that homophobia, racism, and/or misogyny were unduly influencing the community. Second most common were concerns that reddit culture was becoming homogenized. Words such as “hivemind,” “groupthink,” and “in-jokes” appeared frequently. The most common frustration not related to the community was that the site itself was ugly and/or poorly designed.

It’s fascinating to get some insight into how these longterm users think about reddit and its future.  The challenge from here will be to learn more about the people who may not self-select to take a survey: newer users, non-users, and the population of reddit overall.  We’re planning user tests now to learn about newer redditors, and in-person interviews can help give more in-depth data on behavior.  But we’ll continue using surveys too: here’s the next if you’d like to take one!

How People Use New Tabs

As the web evolves, so does the way people interact with the web. Firefox’s user experience and research teams have been eager to learn about our users’ browsing habits so that we can better design for our users.  Lately, Mozillians like Lilian Weng and Jono X have been running some fascinating studies using Test Pilot to determine how, when, and why Firefox users open new tabs.  I wanted to note a few key takeaways from their recent study that give us a glimpse into how our users browse (full studies are linked at the bottom of this post).

A caveat is that these results – as with all Test Pilot studies – are gathered using anonymized data submitted by users who have signed up to participate in Test Pilot. Thus, the Test Pilot users data tends to skew slightly towards the technical and early-adopter crowd.

How are people currently using new tabs?

Each day, the average Firefox user creates 11 new tabs, loads 7 pages from a new tab, and visits 2 unique domains from a new tab.[1] The average new tab loads two pages before the user closes or leaves it.[2]

Once users have a new tab page open, about half of the time (53%) they navigate to a new page using their mouse, and about half of the time (47%) they use the keyboard.[1]

Here’s a breakdown of what actions users take once they’ve opened a new tab:

How People Use New Tabs

As you can see above, the URL bar was the most-used item on a new tab page, with 53% of use actions originating there. The search bar only accounted for 27% of user actions. Even though by default it’s not even enabled in Firefox, 16% of new tab page actions were clicking on a URL in the bookmark bar. History and bookmarks menus were both used less than 5% of the time.

In this study, 17.4% of the domains recorded accounted for 80% of the page views for all participants. You might think that the more active a user is, the number of unique domains they’d visit would follow the same ratio. However, this study found that the more sites a user visited online, they more often they would visit the same 20% of domains. Turns out, the most active internet users are even more loyal to a few choice domains than their less active counterparts.[2]

[1]Quick report on new tab study, by Lilian Weng

[2]Test Pilot New Tab Study Results, by Mozilla Research Team

Firefox Would Love to Read Your Mind

I’d like to highlight the awesome research project that intern Lilian Weng is leading around Firefox’s new tab page.

While our goal is to make users more efficient at their browsing tasks, what makes them more efficient is a question we keep returning to. Most other browsers display links on new tab pages based on frecency. Frecency is a portmanteau which combines frequency and recency. At Mozilla, we use it to refer to sites that users have been to often, recently, or both. It’s how we calculate what should be the first, second, third, etc site that appears when you type a letter into Firefox’s URL bar.

Using frecency to list links on a new tab page seems an obvious design direction, but we want to truly investigate whether another solution would be best for users. So, Lilian is spinning up a brave new study. Once her test is ready, users of Test Pilot, our platform for collecting structured feedback on Firefox, will be asked if they’d like to participate in a new study. If they say yes, they will be randomly assigned one of six new designs on their new, blank Firefox tabs. One of these six designs will be our control group: a blank white tab, just as Firefox users see currently. The other five will look almost identical to each other. They will display a simple 8×8 grid of favicons set on a button which is colored to highlight them based on a color-matching algorithm designed by Margaret Leibovic:

Minimal 8x8 Grid Layout of Site Links

The only variable that will be changing among the five designs is which sites are displayed in this grid. Here’s the five variations we’re testing:

  1. Frecency. A combination of a user’s most frequently and most recently visited sites.
  2. Most recently bookmarked sites. By displaying prominently what a user has recently starred, we effectively turn the new tab page into a read it later list.
  3. Most recently closed sites. This could lead users to treat new tab page as an undo feature, or close tabs in order to temporarily store them in the new tab page as a short-term read it later list.
  4. Sites based on content similarity. Intern Abhinav Sharma is trying out his project, called Predictive Newtabs, which displays sites based on where the user has opened a new tab from. For instance, if the user has been browsing a news site, a new tab would offer other news sites the user has been to.
  5. Sites based on groups of sites frequently visited together. In another part of Abhinav’s Predictive Newtabs experiments, he has designed an algorithm to predict sites to show based on sites users visit in groups. For instance, if every time you get to work you first check the weather and then check stock prices, this new tab would offer you a stock page on a new tab after you checked the weather. If you want to try this experiment out yourself, you can download the Jetpack here.

The above study is still in preparation, and once it goes live I predict that we’ll learn tons of valuable information about how new tab suggestions can positively impact users. Lilian will be collecting data on many aspects of users’ responses to these designs, such as how they effect the breadth of sites users visit, how likely they are to click on each item in the grid, and how long they spend deciding where to navigate. I can’t wait to start pouring over the data that comes back: it’s very new research in an area that has a profound impact on how we use the web.

User Testing in the Wild: Joe’s First Computer Encounter

This past Friday, I went to Westfield Mall in San Francisco to conduct user tests on how people browse the web, and especially how (or if) they use tabs. This was part of a larger investigation some Mozillians are doing to learn about users’ tab behavior.

The mall is a fantastic place to find user test participants, because the range of technical expertise varies widely. Also, the people I encountered tended to be bored out of their minds, impatiently waiting for their partners to shop or friends to meet them. However, rather than completing all 20 tests I was hoping to, I ended up spending three hours testing a man I’ll call Joe.

I find Joe, a 60-year-old hospital cafeteria employee, in the food court looking suitably bored out of his mind. Joe agrees to do a user test, so I begin by asking my standard demographics questions about his experience with the internet. Joe tells me he’s never used a computer, and my eyes light up. It’s very rare in San Francisco to meet a person who’s not used a computer even once, but such people are amazingly useful. It’s a unique opportunity to see what someone who hasn’t been biased by any prior usage reacts. I ask Joe if I could interview him more extensively, and he agrees.

I decide to first expose Joe to the three major browsers. I begin by pulling up Internet Explorer.

Internet Explorer (as Joe encountered it)

Me: “Joe, let’s pretend you’ve sat down at this computer, and your goal is finding a local restaurant to eat at.”

Joe: “But I don’t know what to do.”

Me: “I know, but I want you to approach this computer like you approach a city you’re not familiar with. I want you to investigate and look around try and figure out how it works. And I want you to talk out loud about what you’re thinking and what you’re trying.”

(I show Joe how to use a mouse. He looks skeptical, but takes it in his hand and stares at the screen.)

Joe: “I don’t know what anything means.”

(Joe reads the text on IE and clicks on “Suggested Sites”)

Me: “Why did you click on that?”

Joe: “I don’t really know what to do, so I thought this would suggest something to me.”

(Joe reads a notification that there are no suggestions because the current site is private)

Joe: “I guess not.”

Joe looks around a bit more, but he’s getting visibly frustrated with IE, so I move on to Firefox.

Firefox (as Joe encountered it)

I give him the same task: find a local restaurant. He stares at the screen for awhile with his hand off the mouse, looking confused. I ask what he’s looking for. “I don’t know, anything that looks like it will help!” he says.  Finally, he reads the Apple context menu at the top of the screen, and his gaze falls on the word Help.

“Help, that’s what I need!” says Joe. He clicks on Help, but looks disappointed at what he sees in the menu.

“None of these can help me,” he says.

Joe is getting frustrated again, so I move on to Chrome and give him the same task.

Chrome (as Joe encountered it)

He proceeds to read all of the words on Chrome’s new tab page, looking for any that may offer guidance. Luckily for Joe, he spies a link to Yelp which is marked San Francisco in Chrome’s new tab page. He clicks it, and, seeing restaurants, declares he’s won.

I want to put Joe through other experiments at this point, but the tests are clearly taxing him. He looks very agitated, and has frequently in the tests declared that he “just doesn’t know,” “should have learned this by now,” and “has no excuse for not taking a class on computers.” No amount of assurance that I was testing software, not him, was calming him down. So, I decide to cut Joe a break. “Alright Joe, you’ve helped me, maybe I can help you.”

Because Joe has mentioned a few times he wants email, I get him a gmail.com email address and show him how to access it at a public computer. We practice logging into Gmail several times, and I end up writing a very explicit list of steps for Joe which includes items like “move mouse cursor to white box.” One of the hardest things to relate to Joe is the idea that you must first click in a text field in order to type.

When I am convinced that Joe understands how to check his email, I want to show him how he can use his new email address. So, I ask him why he had asked for an email address in the first place. I imagine he’ll say he wants to communicate with friends and relatives.

Joe: “I want discounts at Boudin Bakery.”

Me: “Sorry, what?”

Joe: “I want Boudin discounts, but they keep telling me I need email.”

(Joe takes his Boudin Bakery customer appreciation card out of his wallet and shows it to me)

I’m a little confused, but go ahead and register Joe’s Boudin Bakery card with his new email address. I show him the web summary of all the bread he’s bought lately. “Woah!” says Joe.

So, what did I learn from Joe?

  • There is little modern applications do to guide people who have never used a computer. Even when focusing on new users, designers tend to take for granted that users understand basic concepts such as cursors, text boxes, and buttons. And, perhaps, rightfully so – if all software could accommodate people like Joe, it would be little but instructions on how to do each new task. But, Joe was looking for a single point of help in an unfamiliar environment, and he never truly got it – not even in a Help menu
  • No matter their skill level, users will try to make sense of a new situation by leveraging what they know about previous situations. Joe knew nothing about computers, so he focused on the only item he recognized: text.  Icons, buttons, and interface elements Joe ignored completely
  • We shouldn’t assume that new users will inquisitively try and discover how new software works by clicking buttons and trying things out. Joe found using software for the first time to be frightening and only continued at my reassurance and (sometimes) insistence. If he was on his own in an internet cafe, I think he would have given up and left after a minute or so.  Giving visual feedback and help if someone is lost may help people like Joe feel they’re getting somewhere
  • Don’t make too many assumptions about how users will benefit from your technology – they may surprise you!

Herdict and its Tasty, Anonymized, Aggregated Data

Nothing sucks on the web like not being able to go to the site you want. Page not found and 404 errors are an inconvenience that entirely halt your workflow. What’s worse than not being able to access a site is not being given relevant information to fix the problem. When users are presented with an error message, they tend to do whatever will make the error go away to get back to their task. Page not found errors can’t be dismissed, because they’re shown instead of the content wanted.

What creates an added level of frustration is not being given information on what the problem is. When users get a Page not found error, they likely have two questions in mind:

  1. Is this problem on my end, or not?
  2. If the problem is on my end, how can I fix it?

These are questions that have been hard for browsers to answer. Currently, Firefox’s network error pages aren’t incredibly useful. They’re certainly not as useful as Chrome’s, which use Google Link Doctor to find possible matches both for subdirectories and domains. That won’t necessarily tell the user if the problem is on their end or not, but it will help if the problem is a typo.

So how could a browser tell users if the problem is on their end or not, without infringing on their privacy? One project that currently takes a stab at this is Herdict, which Johnathan Zittrain’s been working on at Harvard University’s Berkman Center for Internet and Society. What Herdict does is let computer users tell the “herd” – via a Firefox extension – what sites are accessible. The aggregated data can tell if a site is down (because no one can access it), or blocked by a firewall (because only some people can access it), or likely on the user’s end (because everyone else can access it). Not only does that answer the question of “is this problem on my end,” but it may start to answer questions like “is this problem only experienced by my country, network provider, or device?”

Useful stuff! Does it have a place in the browser, and specifically in Firefox? I think that getting and submitting anonymized data should have an increased role in the browser, and especially where it promotes transparency and information to the user. Mitchell Baker has been writing about data, and how Mozilla could be treating aggregated, anonymized data as a public asset that should be freely available. Especially in situations where sites are being blocked and censored, giving users knowledge of the situation seems to align with Mozilla’s goals of transparency and viewing the web as global public resource that must remain open and accessible.

One way something like Herdict could be incorporated is through those Page not found errors. If there were an option on these to submit anonymized data, we could build a pretty accurate view of accessibility information for a website and share it. Allowing users to submit data when there’s a problem is something many programs do already – especially for crashes. This is good design; it makes users feel better by registering the annoyance they feel as a useful data point to developers. Here’s some sketches of what it could look like to incorporate Herdict’s aggregated accessibility data with these error messages:

1. No available information on a site:

2. Site is blocked due to local firewall:

3. Site is down for a country:

4. Site is down for everyone: