analytics

Google Analytics tracks 'Time On Site'. How would you do that effectively? Does it actually track when the user closes the browser or navigates away? Thoughts? I can't be 100% certain of course, but I would guess they use javascript and the onload and onunload events and/or setTimer to communicate with a web service via AJAX. This way they could figure out when users go to or leave a page on your site. Once the browser stops "pinging" the web service, it's assumed that they left your site. I'm sure there's some margin of error involved no matter how you do it, but you could get a pretty decent

I am using RJDBC for accessing MySQL from R. Earlier I used to work with RMySQL which is not available for R 2.15. There were so many discussions around SO but still I couldn't able to use RMySQL package in R 2.15 so switched to RJDBC. When I'm using dbWriteTable(..., append = T) command for appending records into MySQL table it is simply overwriting, please see the code below. setting environment variable for MySQL server Sys.setenv(MYSQL_HOME='C:/Program Files (x86)/MySQL/MySQL Server 5.1') library(RJDBC) MySQL connection drv <- JDBC("com.mysql.jdbc.Driver","mysql-connector-java-5.0.5.jar",

So here's my challenge. I have a spreadsheet that looks like this: prod_id | pack | value | durable | feat | ease | grade | # of ratings 1 75 85 99 90 90 88 1 2 90 95 81 86 87 88 9 3 87 86 80 85 82 84 37 4 92 80 68 67 45 70 5 5 93 81 94 93 90 90 4 6 93 70 60 60 70 70 1 Each product has individual grade criteria (packaging - ease of use), an overall average grade, and number of ratings the product received. The entire data set I have places 68% of the products within the 80-89 grade range. I need to have the grades recalculated to take into account the number of ratings for the product, so

I am switching from SegmentIO to their open source version. I used this blog post as a guide but it's not tracking. Anyone see issue with this code: window.analytics || (window.analytics = []); window.analytics.methods = ['identify', 'track', 'trackLink', 'trackForm', 'trackClick', 'trackSubmit', 'page', 'pageview', 'ab', 'alias', 'ready', 'group', 'on', 'once', 'off']; window.analytics.factory = function (method) { return function () { var args = Array.prototype.slice.call(arguments); args.unshift(method); window.analytics.push(args); return window.analytics; }; }; for (var i = 0; i < window

I listened to a talk by Steve Souders a few days ago and he mentioned the new performance spec that newer browsers are implementing and it was pretty intriguing. In his speech he mentioned the following example as a means of measuring perceived page load time: var timing = performance.timing; var loadtime = timing.loadEventEnd - timing.navigationStart; alert("Perceived time:"+loadtime); Clearly this is a basic example, but when trying it on my development environment, I get crazy numbers like -1238981729837 as the answer because loadEventEnd is < 0. Obviously something is amiss and there are

I understand that apple no longer allows me to send "device data" to third-party services. As a result of this, Flurry and presumably every other analytics company no longer collects OS/hardware version data. However, this data is very valuable to anyone trying to target development toward the people who are actually using the apps. I can imagine a few different ways to collect this data. 1) Send a custom event indicating the hardware/os version to Flurry. This, of course, is in direct violation of the agreement with Apple. However, I suspect plenty of people are doing this, and just not