trust
A sure sign Facebook’s already in trouble – meteoric rise and meteoric fall coming
Facebook Suicide is on the rise (people leaving Facebook and not coming back)
According to SAI sources, the following exchange is between a 19-year-old Mark Zuckerberg and a friend shortly after Mark launched The Facebook in his dorm room:
Zuck: Yeah so if you ever need info about anyone at Harvard
Zuck: Just ask.
Zuck: I have over 4,000 emails, pictures, addresses, SNS
[Redacted Friend's Name]: What? How’d you manage that one?
Zuck: People just submitted it.
Zuck: I don’t know why.
Zuck: They “trust me”
Zuck: Dumb fucks.
Source: http://gizmodo.com/5537408/the-devolution-of-facebook-privacy
Google Suggest — top searches starting with “how do i… “
Ecosystem of Apps for Facebook is already overtaken by iPad Apps as evidenced by search volume around the 3 terms.
NYTimes: chart of Facebook Privacy Options – too complex for most people to figure out and use appropriately.
Charlie O’Donnell: “By the time of this post is done, Diaspora, the web decentralization play from four NYU/Courant students in New York, will undoubtedly have $100,000 raised on Kickstarter. Over and above that, it seems like they’re on a clear path towards a million dollars. Think I’m poking the bear? I’m dead serious. You watch. A week from now, they get to seven digits. Why? Because the ire over Facebook’s privacy issues, platform aggression, etc. is real. If you’re concerned about Facebook, these guys are your heroes.”
AdAge Poll from May 19, 2010.
My Previous article: Facebook is going down in unique users, visits, and time spent
How low can you go? Poll of what percentage of people trust advertising
Source: http://www.marketingcharts.com/topics/behavioral-marketing/distateful-ads-hurt-brand-appeal-12414
34% of respondents 18 and up said soft drink advertising was the most trustworthy,
22% said fast food advertisements rated most trustworthy
18% pharmaceutical companies
14% auto companies
13% financial services companies
If 1 in 3 or as low as 1 in 10 trust ads, even if they saw the ads, they are likely to ignore them or NOT base their purchase decisions on them. Imagine if you had spent a ton of money making the ad, and another ton of money to air or place the ad, how low the ROI would be, if any.
Advertising Can Prevent Purchases
More than one-third of Americans will not purchase a brand because of distasteful advertising,according to a new Adweek Media/Harris Poll.
Advertising Can Prevent Purchases
Thirty-five percent of respondents said they have chosen not to purchase a certain brand because they found the advertisements distasteful. Another 22% said they have not done so but have thought about doing it, and 43% said they have never done so.
Gender, Age Make Varying Differences
The gender and age of a consumer can have a varying impact on whether they will choose not to buy a brand due to distaste for some part of its promotional strategy. Slightly more women (36%) have chosen not to purchase a brand due to its advertising than men (35%). However, more men have chosen not to purchase due to its spokesperson (32%) than women (25%). More men have also chosen not to purchase a product due to a program or event sponsored by it (29%) than women (22%).
College Grads, Wealthy More Easily Offended
College graduates and respondents earning more than $75,000 a year had the highest levels of choosing not to purchase a brand due to some part of its promotional strategy. Forty-three percent of college graduates have chosen not to purchase a brand due to distasteful advertising, compared to 37% of respondents with some college and 29% with a high school degree or less.
In addition, 33% of college graduates have chosen not to purchase a brand because of the spokesperson, compared to 31% of respondents with some college and 23% of respondents with a high school degree or less. And 33% of college graduates have chosen not to purchase a brand because of a sponsorship issue, compared to 27% of respondents with some college and 24% of respondents with a high school degree or less.
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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