Posts Tagged ‘analytics’
More on Web Analytics and Web Advertising
Today we’re going to do some hands-on work with Google Analytics and talk about some key considerations for tracking the success or failure of a web promotion effort.
Google Analytics tour: http://www.google.com/analytics/tour.html. (For more details, head to the Google Analytics IQ Lessons at Conversion University.)
We’re also going to discuss advertising with Google and Facebook. I will show you some examples from an online advertising campaign I ran.
Posted in Uncategorized | 
Tags: analytics, facebook, Google analytics, Google calendar, website promotion | 
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Website Promotion and Analytics
Last week we discussed ways to promote a website. This week we’re going to follow up on that topic and also discuss measuring the effectiveness of website promotion with web analytics.
How do You Find Websites
One way to think about how to promote your web content is to think about how people find new websites. Last week I asked you to list five ways you find out about websites. Here’s a summary of your responses:
| Source | Mentions | Details |
| Other sites | 18 | Links from other websites, blogs, online articles, social media (Facebook, Twitter) |
| Advertising | 10 | Billboards, magazines, TV, public locations (bus, building rooftop, flyers); online ads |
| Word of mouth | 7 | |
| Search engines | 6 | Mostly Google, often serendipitous |
| Friends | 4 | Broadcast links via Facebook, twitter |
| Journalism | 4 | Zines, newspapers, TV news, online articles |
| Web aggregators | 2 | Digg, Reddit |
| Emails | 2 | Including email blasts |
| TV | 2 | |
| Business cards | 1 | |
| Accident | 1 | |
| Text messages | 1 |
By far the most common way to find out about a website is via a link at another website. This makes sense, doesn’t it? The World Wide Web is built around the power of hyperlinks and “surfing” from one website to another.
The next biggest categories are advertising (both online and offline), word of mouth, and search engines.
Web Aggregators
Last week we also tried our hand at using Digg, one of the most popular examples of collaborative filtering via a web aggregator.
Following this link we can see which stories were most popular with our class.
Steven L. Johnson
Susan Jacobson