trust
Facebook is going down – pageviews, average stay, pages per visit – why?
From the Compete charts below, it is clear that Facebook is seeing a decline in pageviews, average stay, and pages per visit. But why?
I know that I have reduced the time I spend on Facebook and I have also reduced the number of messages and other social actions as well. And I have deleted virtually all of my personal and family photos and will not upload any more. These may be the first signs of a waning of Facebook due to a number of factors.
I can’t get my stuff back out
For example, Facebook has stated that it will not participate in OpenSocial because they do not want people to be able to export their content, conversations, photos, etc, out of Facebook and use on another social network. I am concerned that I will not be able to retrieve or back up content which I believe is mine. I like to have control over my family photos, conversations with friends, etc. I am willing to accept as a “cost” of using the Facebook system the fact that they know who my friends are. But I am less willing or unwilling to continue putting my content where I cannot get it back, in its entirety. (Google Docs, for example, just launched a feature where you can back up everything back out of Google Docs into Microsoft Office formats).
Ads in the stream, erosion of trust
A second issue mentioned in a previous post is the increase in advertising on Facebook and also the more unscrupulous practice of injecting ads “into the stream” — ads masquerading as status updates. These are harmful to the overall trust built up in the community and I have un-friended quite a few people whose accounts were clearly used to promote events, products, etc.
Ad-effectiveness sucks
From a prior post – http://bit.ly/EhiW9 – Facebook advertising metric are absolutely abysmal. They keep trying to sell advertisers on the hundreds of billions of pageviews they throw off. But advertisers are getting smarter and more and more of them will buy ads on a cost-per-click basis (instead of CPM, cost per thousand impressions basis). This means that the ad revenues that Facebook enjoyed from gross INefficiencies will be decimated.
Map of IP addresses around the world used to commit Click-Fraud
A recently disbanded click fraud ring in China racked up $3 million worth of clicks in two weeks. $3 million that we’re aware of. Just how detectable is this whole business of racking up fraudulent ad revenue clicks?
That intricate mess of lines above represents a portion of DormRing1, the click fraud bunch that was caught in China. The lines show the relationship of some of the IP addresses involved in the fraud and how they are connected to some fraudulent ad clicks. The whole network actually “involved 200,000 different IP addresses and racked up more than $3 million worth of fraudulent clicks across 2,000 advertisers in a two-week period.” Impressive and scary at the same time.
The trouble is that no one really knows how much ad revenue DormRing1 collected before they were caught. Click-fraud monitoring services such as Anchor Intelligence, the ones behind this catch, are evolving to keep up with the scale on which these rings are operating. It’s still difficult to judge just how well they’re doing as they’re having to infiltrate forums and gain the trust of the perpetrators in a manner reminiscent of drug busts. But as the criminals are getting more elaborate, the investigations are too.
That good news aside, do me a favor: after you read this post, comment, and all that jazz, refresh the page a few times and—Ah…I mean, heh…just kidding. [Tech Crunch]
The generalization that TV ads are more “helpful” than internet ads is simply false and irresponsible
In the following study published by Harris Interactive and Adweek Media, they show a chart which seemingly shows that TV ads are “most helpful” in making a purchase decision. If you were give the following list of choices — TV ads, newspaper ads, search engine ads, radio ads, banner ads, and none — and asked to select which was most helpful to your purchase decision; which would you choose? And would you choose that because it was more familiar to you (e.g. TV), seen more frequently, etc. Or is it that banner ads are generally known to be ignored (eye tracking studies show that most users know not to look at the top and right sides of a web page, knowing that banner ads typcially go there).
Source: http://www.marketingcharts.com/television/tv-ads-most-helpful-web-banners-most-ignored-9645/
More than one-third of Americans (37%) say that TV ads are most helpful to them in making a purchase decision, while nearly half say they ignore internet banner ads, according to (pdf) a poll from AdWeekMedia and Harris Interactive.
In terms of the helpfulness of ads in other media, newspapers rank second behind TV, with 17% reporting that newspaper ads are most helpful, while 14% say the same about internet search-engine ads:
At the other end of the spectrum, Radio ads (3%) and internet banner ads (1%) are not considered helpful by many people. The poll found also that more than one fourth (28%) of Americans say that none of these types of advertisements are helpful to them in the purchase-decision-making process.
Not surprisingly, the types of ads Americans find helpful vary by age and, slightly, by region:
- 50% of people ages 18-34 find TV ads most helpful.
- 31% of those ages 55+ say newspaper ads are most helpful.
- 40% of Southerners find TV ads most helpful, while only one-third (33%) of Midwesterners feel the same.
Banner Ads Most Ignored
Almost half of Americans (46%) say they ignore internet banner ads, according to the study. Much further down the list of ignored items are internet search engine ads (17% of people ignore), television ads (13%), radio ads (9%), and newspaper ads (6%):
One in ten Americans (9%) say they do not ignore any of these types of ads.
Age and regional differences:
- 50% of those ages 35-44 and 51% of Midwesterners say they ignore Internet banner ads compared with 43% of 18-34 year olds as well as Easterners and Southerners.
- 20% of Americans 18-34 years old (20%) say they ignore Internet search engine ads while 20% of those ages 55+ ignore TV ads.
Harris Interactive suggestes that these findings are important because, despite online video and the ability to use a DVR to shift live programming, TV ads remain most helpful to consumers. Conversely, while an internet strategy is essential for a comprehensive ad campaign, banner ads are only considered helpful by a few and are ignored the most, the polling fiirm said.
About the survey: The AdweekMedia/The Harris Poll was conducted online in the US from June 4-8, 2009 among 2,521 adults (ages 18+). Figures for age, sex, race/ethnicity, education, region and household income were weighted where necessary to bring them into line with their actual proportions in the population. Propensity score weighting was also used to adjust for respondents’ propensity to be online.
What is Web 3.0? Characteristics of Web 3.0
2009 06 16 What Is Web 3.0 – Presentation Transcript
- What is Web 3.0? Dr. Augustine Fou June 16, 2009. June 16, 2009.
- Evolution of the Internet microprocessor 40 yrs 10 yrs 20 yrs 5 yrs present web internet 2.5 yrs social networks e-commerce 1.5 yrs Web 1.0 Web 2.0 Web 3.0? June 16, 2009.
- Evolution of the “Web” content commerce search social networks social content social search social commerce As each stage reaches critical mass, the next stage is tipped into present June 16, 2009.
- Key Characteristics present web 1.0 web 2.0 web 3.0
- Speedy
- more timely information and more efficient tools to find information
- Collaborative
- actions of users amass, police, and prioritize content
- Trust-worthy
- users establish trust networks and hone trust radars
- Content
- content destination sites and personal portals
- Search
- critical mass of content drives need for search engines
- Commerce
- commerce goes mainstream; digital goods rise
- Ubiquitous
- available at any time, anywhere, through any channel or device
- Individualized
- filtered and shared by friends or trust networks
- Efficient
- relevant and contextual information findable instantly
June 16, 2009.
- Illustrative Examples – retail/shopping present web 1.0 web 2.0 web 3.0
- what friends bought or want to buy
- drag-to-share items which friends know friends are looking for
- item collections
- value in the aggregation
overstock.com amazon.com FB app: MyFaveThings
-
- contextual reviews
- reviews of reviews
- what others bought
- individualized recommendations
June 16, 2009.
- Illustrative Examples – social networks present web 1.0 web 2.0 web 3.0
- aggregates all your online identities
- syndicates all your updates to all social networks
- social actions visible to friends
- trust networks across geography, time, and interests
- collection of personal homepages
geocities.com facebook.com peoplebrowsr.com June 16, 2009.
- Illustrative Examples – restaurant reviews present web 1.0 web 2.0 web 3.0
- Yelp content vetted through a user’s trust network and individual recommendations made based on situation and need, in real-time
- user submitted reviews
- related items based on similarity of user preferences
- infrequent publication
- centralized editorial control
zagat‘s yelp need reco for great Italian + GPS + Yelp 5-star Babbo, been there, love it June 16, 2009.
- Illustrative Examples – photos present web 1.0 web 2.0 web 3.0
- real-time, contextual “do you like this knit shirt?”
- friends give immediate feedback
- share photos with friends and strangers
- enable visitors to tag and comment
- individual albums
kodakgallery.com flickr.com ? June 16, 2009.
- Illustrative Examples – real estate present web 1.0 web 2.0 web 3.0
- information vetted by fellow users, recommended directly an in context
- listings plus relevant information like school zones, comparable sales, alerts
- listings based on parameters
corcoran.com streeteasy.com trulia iphone app June 16, 2009.
- Illustrative Examples – encyclopedia present web 1.0 web 2.0 web 3.0
- content is ubiquitous and available through any channel or device
- trust network proactively forwards relevant info to user who needs it
- created, updated, and edited (policed) by user actions
- digitized version of printed encyclopedia
britannica.com wikipedia.com chacha.com June 16, 2009.
- Illustrative Examples – online coupons present web 1.0 web 2.0 web 3.0
- coupons delivered contextually and proactively when user needs it (without the user even asking for it)
- instant feedback
- community action makes it more accurate and useful for others
- collection of online coupons – value in the aggregation
dealcatcher.com retailmenot.com June 16, 2009.
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