The latest TestPilot analysis shows the predominance of the back button in browser control usage, garnering 2/3 of clicks by user in the browser chrome. The observation that the back button is the most used browser control is longstanding, here’s a view from a ‘06 post excerpting the ACM WWW ‘06 best student paper from Weinrach, et al.:
Table 1: Comparison chart of three long-term studies
|
|
Catledge & Pitkow3 |
Tauscher & Greenberg3 |
This Study |
|
Time of study
|
1994 |
1995-1996 |
2004-2005 |
|
No. of users
|
107 |
23 |
25 |
|
Length (days)
|
21 |
35-42 |
52-195, ø=105 |
|
No. of visits
|
31,134 |
84,841 |
137,272 |
|
Recurrence rate
|
61% |
58% |
45.6% |
|
Link
|
45.7% |
43.4% |
43.5% |
|
Back
|
35.7% |
31.7% |
14.3% |
|
Submit
|
- |
4.4% |
15.3% |
|
New window
|
0.2% |
0.8% |
10.5% |
|
Direct access
|
12.6% |
13.2% |
9.4% |
|
Reload
|
4.3% |
3.3% |
1.7% |
|
Forward
|
1.5% |
0.8% |
0.6% |
|
Other
|
- |
2.3% |
4.8% |
The replication of the finding is welcome, and the lack of novelty didn’t prevent Techmeme buzz from sprouting up, probably helped significantly by the excellent visual heatmap. Nice work Mozilla peeps! Here’s a zoom on the back button findings by clicks per user and % of users:
There’s been supposition that the growing use of tabbed browsing is reducing the importance of the back button. Certainly, opening search results into new tabs reduces the need to go back to get to search results as do parallel scenarios in non-search browsing. My recent analysis of tab usage from SRP and non-SRP pages shows that open in new tab is common but still a minority use case for search result browsing.
The TestPilot analysis doesn’t specifically address the relative prominence of back button versus tab switches or links inside pages because it only includes browser chrome — defined as the area surrounding the tabbed browser. I’d love to see a replication of this study which counted clicks on tabs as well as interior to the browsed page UI.
The latest Mozilla TestPilot study to publish data is the Tab Switch Study evolving the logging stream from the Tab Open Close study. Less robust tab usage data is also available in the first week in the life data drop.
In addition to improvements to logging to allow individual tabs to be tracked accurately as users open and close tabs around them, the latest study includes tagging of search result pages (SRPs). This is particularly interesting to me as clickstream patterns around search results are highly useful for evaluating search quality and even generating data for machine learning, but tabbed browsing (and new window strategies) may seriously affect how a server side log appears and complicate accurately reconstructing the user sequence.
How is tabbed browsing used in search?
I found that 96% of the users in the 2000 user data set had a URL loaded from an SRP. 86% of these users also opened a new tab from an SRP, suggesting that at least in this audience, opening links in tabs from an SRP is a very well known strategy available to over 90% of users.
The denominator for the following stats are *either* tab focus changes or page loads in a tab. For those SRPs, 40% of changes were page loads in the same tab and 20% were open in new tabs. Thus, open in new tab doesn’t seem to be the predominant strategy. However, I would expect navigational queries, estimated by research at 30% of web search engine usage, not to invoke a open in new tab strategy.
General behavior following a page load
Looking at successive events from a load event to specifically to understand search and tabs, we see users are only about 8.5% more likely to open a page following an SRP in a new tab than for any other page load.
|
|
|
|
|
|
|
|
.
|
Is SRP? |
Close |
Load |
Open Tab |
Open Window |
Switch |
|
.
|
0 |
8.49% |
62.4% |
12.91% |
0.01% |
16.2% |
|
.
|
1 |
4.75% |
69.92% |
14.08% |
0.01% |
11.24% |
|
.
|
Grand Total |
8.21% |
62.97% |
13% |
0.01% |
15.82% |
|
My SQL for creating a MySQL table, importing the data, and creating a derived sequence table is available on github:
For my analysis of previous tab usage TestPilot datasets, see this post and my visualization galllery.
Back to tracking SRP behavior, it looks like tabbed browsing is only barely more of an issue for pathing in search behavior than in general web activity. Anybody know of an analytics solution that tackles this? Creative use of window.name would likely maintain pathing integrity even when tabs are opened in the background.
A couple of themes emerged in the Jetpack for Learning finalists:
- Language Learning
- Game-based Learning
- Annotation
- Trails
I’m personally especially excited to see the Trails implementations as I’ve long regarded that as a missing piece of the Web 2.0+ world.
A couple projects break the mold here: Cohere is superset of annotation in the knowledge construction & management space and part of a larger .edu project. Rubrick facilitates assessment in a collegiate environment.
We’re having great fun at the Design Camp leading into SXSWi, track it via #jet4learning. Looking forward to spending more time on the future of JetPack today and the final presentations.
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