What gadgets are early adopters searching for?

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Later this week I’ll be sharing some insights at the Australian Retail Symposium 2009 on how specific demographic segments search for retail brands and products. I’ve looked at searches by Australian households in our Hitwise Lifestyle segment, ‘Young Ambition’, who are early adopters of technology and are likely to research products over the Internet. Here’s a sample of their leading electronics search terms during March 2009:

EarlyAdopterSearches_AU.png

• ‘mobile phones’ was the leading product-related search term, but ‘Young Ambition’ were much more likely to search for ‘mobile phone reviews’ with an index of 485 compared to the online population average (100).

• ‘iphone accessories’ attracted higher volumes of search than ‘iphone,’ suggesting that ‘Young Ambition’ are seasoned iPhone users and are now looking for the latest accessories.

• ‘Omnia’ and the ‘LG Web Slider’ are providing strong competition to the iPhone amongst ‘Young Ambition’ households, with high search volumes compared to the online population.

• ‘navman’ and ‘tomtom’ searches were over-represented amongst ‘Young Ambition’ during Christmas 2008 but were under-represented during March 2009. This suggests that navigation products are becoming less of a fad amongst early adopters.

• ‘headphones’, ‘cameras’ and ‘laptops’ were other leading product search terms. ‘Sennheiser’ related terms also appeared in the long-tail of ‘Young Ambition’ searches.

Retailers can gain an understanding of the products and brands that resound with specific consumer groups by drilling into their search behaviour. Stay tuned for a similar analysis on high-end shoppers and suburban families.

April 28th 2009 Uncategorized

Budget 2009: paid search tactics

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As you would expect, last week’s budget received a lot of press attention. UK Internet searches for the term ‘budget’ increased 27-fold between the weeks ending April 18th and 25th. However, as the chart below illustrates, searches for the term only reached a similar level to last year and were actually down on two years ago. Following the online reaction to last year’s pre-budget report I was also expecting a spike in searches for the term ‘50p tax’, but surprisingly that didn’t occur.

UK_Internet_searches_for_budget_2009_2008_2007_chart.png

Despite this, ‘budget’ was the third fastest moving term in the in the UK last week (in fact it was really the fastest, as the two that appeared above it – ‘earth day’ and ‘st george’s day’ – were both Google Doodles), and lots of websites were competing to pick up traffic from it. As the table below illustrates, the most successful was DirectGov, which paid for the majority of its clicks. The Telegraph ranked second, also thanks to a significant investment in paid traffic, while BBC News, Google News and the FT all ranked in the top 10. The accountancy firms also did well from the term, with KPMG beating Ernst & Young to the top spot this year, despite paying less for its traffic.

Websiates_receiving_traffic_from_searches_for_budget_tapril_2009_table.png

The Conservative Party also ran a paid search campaign for the budget, and was the 11th biggest recipient of traffic from the term ‘budget’ last week. Over 90% of this traffic came via paid search and, as the table below illustrates, it was the highest placed non-branded term sending traffic to the Tories’ homepage last week. The other terms that that Conservative Party received a significant amount of paid traffic from were ‘budget 2009’, ‘vat threshold’ and ‘2009 budget’.

Conservative_party_top_budget_2009_search_terms_table.png

The combination of more paid search traffic and the general interest in all things budget-related meant that traffic to conservatives.com increased by 71% last week. The official homepages of the Labour Party (up 20%) and the Liberal Democrats (up 33%) also received traffic boosts. Following on from the Daniel Hannan YouTube clip last month, it is starting to look like the next UK election may well be the first in which the Internet will play a significant role.


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April 27th 2009 Uncategorized

Oprah may be America’s Tweet-heart, but she doesn’t make the earth move Downunder!

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My colleague in the US, Heather Hopkins recently covered the blaze of publicity around Oprah Winfrey starting to tweet and its immediate impact on Twitter’s US share of visits. In Australia the influences seem to be broader than America’s new ‘tweetheart’.

In Australia the growth of Twitter has been nothing short of phenomenal;
• 49.9% growth in the past month (comparing 21/04/2009 vs. 22/03/2009)
• 1067.3% since the start of the 2009 (comparing 21/04/2009 vs. 01/01/2009)
• 3,220.7% annual growth (comparing 21/04/2009 vs. 22/04/2008).

On Sunday 19 April 2009, Twitter became the 37th most visited website by Australian Internet users, breaking into the top 40 Australian websites for the first time on the back of a 3.9% rise in share, coinciding with Oprah’s first tweet.

aus_share_trenda

The largest single day of growth experienced by Twitter this year was 22 March 2009, when share of visits grew by 89.3% over the previous day. It was a day after the Queensland Election and four days after the second of the Melbourne earth tremors.

In Australia a number of celebrities were included in searches for ‘twitter’, representing 38% of the top 50 ‘twitter’ search variations for week ending 18 April 2009.

Ashton Kutcher and his challenge to be the first Twitterer to have one million followers received considerable news coverage. In the days leading up Kutcher passing the million follower mark, Twitter’s share of daily visits increased by 10.6% (16/4/2009) and 6.22% (17/4/2009). Oprah could only move Twitter’s Australian share by 2.46% (18/4/2009).

Lindsay Lohan however, with her much publicised relationship split, had the strongest association with Twitter compared to other celebrities, with 0.65% of Twitter-related search terms (week ending 18/04/2009), followed by Kutcher (0.51%), Miley Cyrus (0.35%) and Australia’s Hugh Jackman (0.22%).

Twitter a truly global phenomenon

In other markets, Twitter has a growth pattern similar to the US and UK, highlighting that Twitter is a truly global phenomenon.

Twitter increased its share in New Zealand 305.5% since the start of the year (1/01/2009), and on 21 April 2009 ranked at 49 amongst all websites (up from 206).

In Singapore, Twitter moved up 239 positions to a rank of 65 amongst all websites with an increase in share of visits of 333.3% since the 1/01/2009.

Hong Kong is lagging by comparison to the other Asia Pacific markets the US and UK, as can be seen from the chart below, but has moved up 373 places since 1/01/2009 to currently stand at the 198th most visited website in Hong Kong on 21/04/2009 with a share of visits increase of 198.1%.

twitter global_sml.png

Click chart for larger version

It is interesting to note that large jumps in share of visits have been sparked by a variety of events and news items at different times over the past three months. However, Ashton Kutcher and Oprah seem to have had an impact in all countries in mid April.

For statistical comparison the Twitters share of visits in the US and UK, as at 21/4/2009, have grown 570.03% and 621.3% respectively since 1/01/2009 improving its ranking position by 324 spots in the US and 305 spots in the UK.

It is interesting to note that Entertainment / Celebrity brands have embraced Twitter as a communication and connection tool, yet many consumer facing brands have yet to understand the opportunity and accept the challenge of direct interaction with consumers. Props to those businesses that are active and learning.

April 24th 2009 Social Media

Bushfire Searches: 4 week window of peak community interest

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The Victorian bushfires in February 2009 demonstrated how Australians turned to the Internet to get vital information surrounding a crisis. Search data reflected strong community awareness of the Victorian Country Fire Authority, with ‘cfa’ the fastest moving search term driving traffic to all websites in February 2009. Searches that included ‘bushfires’ were three times greater than searches including ‘cfa’ during the height of the crisis, week ending 14 February 2009. The below figure demonstrates the peak of bushfire searches following Black Saturday and how quickly they dropped off.

bushfiresearches.png

· ‘Bushfires’ searches decreased by 76.5% the week ending 21 February 2009 compared to week ending 14 February 2009, and dropped a futher 44.3% a fortnight later.

· There was 4-week window for peak community awareness following the Victorian Bushfire tragedy. 6 weeks after the height of the crisis, search activity on ‘bushfires’ dropped to search levels preceding the crisis.

Bushfire Searches became more specific during and after crisis

A detailed study into the bushfire searches provide insight into what types of information requirements emerge at key periods during a crisis. Hitwise found that bushfire searches fell into the following 5 types:

1. ‘Appeal’ searches around fundraising efforts e.g. ‘redcross bushfire appeal’
2. ‘Education’ searches around historical knowledge and future planning e.g. ‘bushfire survival’
3. ‘General’ searches e.g. ‘victorian bushfires’
4. ‘Informational’ searches around news and geographical updates e.g. ‘bushfire map’
5. ‘Services’ searches around government and commercial agencies e.g. ‘cfa bushfires’

BushfireSearchTypes2.png

· ‘Informational’ searches were strong throughout, with timeliness the key in providing community updates. The top 5 websites to receive ‘Informational’ searches during the height of the crisis (week ending 14 February 2009) were the Victoria Country Fire Authority, ABC News Online, Google News Australia, Victorian Department of Sustainability and Environment, and The Age.

·The community were willing to provide support immediately with ‘Appeal’ searches prevalent during the week ending 14 February 2009. ‘Appeal’ searches however dropped off significantly 5 weeks after the crisis.

· News and Media websites attracted the most traffic from all types of bushfire searches apart from ‘Services’ following the crisis. However News and Media websites received a smaller allocation of paid traffic on ‘bushfire’ Searches (5.8%) than Government websites (8.7%) during the week ending 14 March 2009, suggesting that organic traffic was a more important driver of traffic.

·The proportion of ‘Education’ searches peaked 5 weeks following the crisis, suggesting ongoing demand for information to avoid a repeat of the disaster. Wikipedia was the top website to receive ‘Educational’ during the crisis (week ending 14 March 2009). While Government websites received a significant portion of search traffic with 8.9%, it is clear agencies need to compete with a range of sources in providing reliable and authoritative information to the public.

Making sure government websites are optimised for searches on key issues

Government agencies can use online behaviour surrounding the Victorian bushfire case study to understand the needs of the community, when information is crucial for saving lives. By investing in best practice Search Engine Optimisation, such as using keyword research to determine the language of the community, government agencies can ensure they are a key source of information. Government agencies can also work with leading online news outlets for information dissemination.

We will be releasing an Online Government report very soon that includes the bushfire case study so stay tuned. Hitwise Research Director, Alan Long and Product Director for Search Marketing Services, Stuart McKeown will also be speaking at this AMI event on 30 April: Best practices for government, community organisations and consumer marketing.

April 23rd 2009 Uncategorized

Online retailers receiving less traffic from paid search, but more from social networks

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The amount of traffic that online retailers receive from paid search – i.e. from sponsored or paid for links on search engines such as Google, Yahoo!, Live and Ask – has fallen over the last 12 months. During March 2009, 8.9% of all UK Internet visits to online retailers came from a paid search listing, down from 10.1% in March 2008.

Search engines are the primary source of traffic for almost all online retailers, and a typical ecommerce site in the UK receives 2 in every 5 visits from a search engine. However, the proportion of search traffic that comes from paid listings fell from 27.8% in March 2008 to 22.5% in March 2009. Retailers are amongst the biggest users of paid search in the UK, so – as the chart below illustrates – this has also contributed to an overall decline in paid search rates. In March 2009, 9.4% of all search engine traffic in the UK was from paid listings, down from 12.1% in March 2008.

UK_paid_search_rates_retail_2009_2008_chart.png

Following yesterday’s post illustrating that social networks now receive more UK Internet visits that online retailers, it is perhaps no surprise to see that the amount of traffic our Shopping and Classifies category receive from social networking websites increased from 5.2% in March 2008 to 7.1% in March 2009. A year ago online retailers received a similar amount of traffic from both social networks and webmail services (such as Hotmail, Yahoo! Mail and GoogleMail), but social networks now account for 58.3% more traffic than webmail providers.

Online_retailers_upstream_traffic_from_social_networks_email_webmail_UK_2009_2008_chart.png

The retail categories that received most traffic from social networks during March 2009 were Auctions, Fashion and Department Stores. Together they accounted for over half of all downstream visits from social networks to an online retailer.

Top 10 online retail websites receiving traffic from social networks, March 2009
:

1. eBay UK (1.94% of all downstream visits from social networks)
2. Amazon UK (0.40%)
3. Play.com (0.19%)
4. ASOS (0.13%)
5. eBay (0.10%)
6. Argos (0.09%)
7. Gumtree.com (0.09%)
8. Amazon.com (0.08%)
9. TopShop.com (0.08%)
10. HotUKDeals (0.08%)

Social networks are a relatively small but fast growing source of traffic for online retailers. At present, only a minority of retailers pick up a significant amount of traffic from social networks, but many of those that do have seen a positive impact on traffic. For example, fashion retailer ASOS has a strong presence on Facebook and in March received 13.3% of its traffic from the social network. Another example – in a very different market – is online bookseller Abebooks, which currently receives a quarter of all its UK Internet traffic from social networks, more than it gets from search engines. These and other examples illustrate that a retailer’s success on a social network has less to do with products or demographics than it does with effectively engaging with an online community.


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April 22nd 2009 Uncategorized

Advanced White Hat SEO Exists Damn It! – Dynamic SEO

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Hello again!
I’ve been restless and wanting to write this post for a very long time and I’m not going to be happy until its out. So get out your reading glasses, and I have it on good authority that every reader of this blog happens to be the kind of dirty old men that hang out and harass high school chicks at gas stations so don’t tell me you don’t have a pair. Get ‘em out and let’s begin….

Fuck, how do I intro-rant this post without getting all industry political? Basically, this post is an answer to a question asked a long time ago at some IM conference to a bunch of gurus. They asked them does advanced White Hat SEO exist? If I remember right, and this was a long time ago and probably buzzed up so forgive me, every guru said something along the lines of there is no such thing as advanced White Hat SEO. Now I’m sympathetic to the whole self promotion thing to a small degree. If your job is to build buzz around yourself you have to say things that are buzz worthy. You can’t say the obvious answer, YOU BET IT DOES AND YOU’RE RETARDED FOR ASKING! You gotta say something controversial that gets people thinking, but not something so controversial that anyone of your popularity level is going to contradict in a sensible way making your popularity appear more overrated than a cotton candy vendor at the Special Olympics. In short, yes advanced white hat exists and there’s tons of examples of it; but you already knew that and I’m going to give you such an example now. That example is called Dynamic SEO. I’ve briefly mentioned it in several posts in the past and it is by every definition simple good ol’ fashion on-site keyword/page/traffic optimizing White Hat SEO. It also happens to be very simple to execute but not so simple to understand. So I’ll start with the basics and we’ll work into building something truly badhatass.

What Is Dynamic SEO?
Dynamic SEO is simply the automated no-guessing self changing way of SEOing your site over time. It is the way to get your site as close to 100% perfectly optimized as needed without ever knowing the final result AND automatically changing those results as they’re required. It’s easier done than said.

What Problems Does Dynamic SEO Address?
If you’re good enough at it you can address EVERY SEO related problem with it. I am well aware that I defined it above as on-site SEO, but the reality is you can use it for every scenario; even off-site SEO. Hell SQUIRT is technically dynamic off-site SEO. Log Link Matching is even an example of advanced off-site Dynamic SEO. The problems we’re facing with this post specifically includes keyword optimization which is inclusive of keyword order, keyword selection, and even keyword pluralization.

See the problem is you. When it comes to subpages of your site you can’t possibly pick the exact best keywords for all of them and perfectly optimize the page for them. First of all keyword research tools often get the keyword order mixed up. For instance they may say “Myspace Template” is the high traffic keyword. When really it could be “Templates For Myspace”. They just excluded the common word “for” and got the order wrong because “Template Myspace” isn’t popular enough. They also removed the plural to “broad” the count. By that logic Myspace Templates may be the real keyword. Naturally if you have the intuition this is a problem you can work around manually. The problem is not only will you never be perfect on every single page but your intuition as a more advanced Internet user is often way off, especially when it comes to searching for things. Common users tend to search for what they want in a broad sense. Hell the keyword Internet gets MILLIONS of searches. Who the fuck searches for a single common word such as Internet? Your audience is who. Whereas you tend to think more linear with your queries because you have a higher understanding of how Ask Jeeves isn’t really a butler that answers questions. You just list all the keywords you think the desired results will have. For instance, “laptop battery hp7100″ instead of “batteries for a hp7100 laptop.” Dynamic SEO is a plug n play way of solving that problem automatically. Here’s how you do it.

Create A Dynamic SEO Module
The next site you hand code is a great opportunity to get this built and in play. You’ll want to create a single module file such as dynkeywords.pl or dynkeywords.php that you can use across all your sites and easily plug into all your future pages. If you have a dedicated server you can even setup the module file to be included (or required) on a common path that all the sites on your server can access. With it you’ll want to give the script its own sql database. That single database can hold the data for every page of all your sites. You can always continue to revise the module and add more cool features but while starting out it’s best to start simple. Create a table that has a field structure similar to ID,URL,KEYWORD,COUNT. I put ID just because I like to always have some sort of primary key to auto increment. I’m a fan of large numbers what can I say? :)

Page Structure & Variables To Pass To Your Module
Before we get deep into the nitty gritty functions of the module we’ll first explore what basic data it requires and how the site pages will pass and return that data. In most coded pages, at least on my sites, I usually have the title tag in some sort of variable. This is typically passed to the template for obvious reasons. The important thing is it’s there so we’ll start with that. Let’s say you have a site on home theater equipment and the subpage you’re working on is on LCD televisions. Your title tag may be something like “MyTVDomain.com: LCD Televisions – LCD TVs”.

Side Note/
BTW sorry I realize that may bother some people how in certain cases I’ll put the period outside of the quotes. I realize it’s wrong and the punctuation must always go inside the quotes when ending a sentence. I do it that way so I don’t imply that I put punctuation inside my keywords or title tags etc etc.
/Side Note

You know your keywords will be similar to LCD Televisions, but you don’t know whether LCD TVs would be a better keyword. ie. It could either be a higher traffic keyword or even a more feasible keyword for that subpage to rank for. You also don’t know if the plurals would be better or worse for that particular subpage so you’ll have to keep that in your mind while you pass the module the new title variable. So before you declare your title tag create a quick scalar for it (hashref array). In this scalar you’ll want to put in the estimated best keywords for the page:
[
Keyword1 -> ‘LCD Television’,
Keyword2 -> ‘LCD TV’,
]
Then put in the plurals of all your keywords. It’s important not to try to over automate this because A) you don’t want your script to just tag the end of every word with “s” because of grammatical reasons (skies, pieces, moose, geese) and B) you don’t want your module slowing down all the pages of your site by consulting a dictionary DB on every load.
[
Keyword1 -> ‘LCD Television’,
Keyword2 -> ‘LCD TV’,
Keyword3 -> ‘LCD Televisions’,
Keyword4 -> ‘LCD TVs’,
]
Now for you “what about this awesome way better than your solution” mutha fuckas that exist in the comment section of every blog, this is where you get your option. You didn’t have to use a scalar array above you could of just have used a regular array and passed the rest of the data in their own variables, or you could of put them at the beginning of the standard array and assigned the trailing slots to the keywords OR you could use a multidimensional array. I really don’t give a shit how you manage the technical details. You just need to pass some more variables to the modules starting function and I happen to prefer tagging them onto the scalar I already have.
[
Keyword1 -> ‘LCD Television’,
Keyword2 -> ‘LCD TV’,
Keyword3 -> ‘LCD Televisions’,
Keyword4 -> ‘LCD TVs’,
URL -> ‘$url’,
REFERRER -> ‘$referrer’,
Separator -> ‘-’
]
In this case the $url will be a string that holds the current url that the user is on. This may vary depending on the structure of the site. For most pages you can just pull the environmental variable of the document url or if your site has a more dynamic structure you can grab it plus the query_string. It doesn’t matter if you’re still reading this long fuckin’ post you probably are at the point in your coding abilities where you can easily figure this out. Same deal with the referrer. Both of these variables are very important and inside the module you should make a check for empty data. You need to know what page the pageview is being made on and you’ll need to know if they came from a search engine and if so what keywords did they search for. The Separator is simply just the character you want to separate the keywords out by once its outputted. In this example I put a hyphen so it’ll be “Keyword 1 – Keyword 2 – Keyword 3″ Once you got this all you have to do is include the module in your code before the template output, have the module return the $title variable and have your template output that variable in the title tag. Easy peasey beautiful single line of code. :)

Basic Module Functions
Inside the module you can do a wide assortment of things with the data and the SQL and we’ll get to a few ideas in a bit. For now just grab the data and check the referrer for a search engine using regex. I’ll give you a start on this but trust it less the older this post gets:
Google: ^http://www.google.[^/]+/search?.*q=.*$
[?&]q= *([^& ][^&]*[^& +])[ +]*(&.*)?$
Yahoo: ^http://(w*.)*search.yahoo.[^/]+/.*$
[?&]p= *([^& ][^&]*[^& +])[ +]*(&.*)?$
MSN: ^http://search.(msn.[^/]+|live.com)/.*$
[?&]q= *([^& ][^&]*[^& +])[ +]*(&.*)?$

Once you’ve isolated the search engines and the keywords used to find the subpage you can check to see if it exists in the database. If it doesn’t exist insert a new row with the page, the keyword, and a count of 1. Then select where the page is equal to the $url from the database order by the highest count. If the count is less than a predefined delimiter (ie 1 SE referrer) than output the $title tag with the keywords in order (may want to put a limit on it). For instance if they all have a count of 1 than output from the first result to the last with the Separator imbetween. Once you get your first visitor from a SE it’ll rearrange itself automatically. For instance if LCD TV has a count of 3 and LCD Televisions has a count of 2 and the rest have a count of 1 you can put a limit of 3 on your results and you’ll output a title tag with something like “LCD TV – LCD Televisions – LCD Television” LCD Television being simply the next result not necessarily the best result. If you prefer to put your domain name in your title tag like “MYTVSITE.COM: LCD TV – LCD Televisions – LCD Television” you can always create an entry in your scalar for that and have your module just check for it and if its there put it at the beginning or end or whatever you prefer (another neat customization!).

Becoming MR. Fancy Pants
Once you have the basics of the script down you can custom automate and SEO every aspect of your site. You can do the same technique you did with your title tag with your heading tags. As an example you can even create priority headings *wink*. You can go as far as do dynamic keyword insertion by putting in placeholders into your text such as %keyword% or even a long nonsense string that’ll never get used in the actual text such as 557365204c534920772f205468697320546563686e6971756520546f20446f6d696e617465. With that you can create perfect keyword density. If you haven’t read my super old post on manipulating page freshness factors you definitely should because this module can automate perfect timings on content updates for each page. Once you have it built you can get as advanced and dialed in as you’d like.

How This Works For Your Benefit
Here’s the science behind the technique. It’s all about creating better odds for each of your subpages hitting those perfect keywords with the optimal traffic that page with its current link building can accomplish. In all honesty, manually done, your odds are slim to none and I’ll explain why. A great example of these odds in play are the ranges in competitiveness and volume by niche. For instance you build a site around a homes for sale database you do a bit of keyword research and figure out that “Homes For Sale In California” is an awesome keyword with tons of traffic and low competition. So you optimize all your pages for “Homes For Sale In $state” without knowing it you may have just missed out on a big opportunity because while “Homes For Sale In California” may be a great keyword for that subpage “New York Homes” may be a better one for another subpage or maybe “Homes For Sale In Texas” is too competitive and “Homes In Texas” may have less search volume but your subpage is capable of ranking for it and not the former. You just missed out on all that easy traffic like a chump. Don’t feel bad more than likely your competitors did as well. :)

Another large advantage this brings is in the assumption that short tail terms tend to have more search volume than long tail terms. So you have a page with the keywords “Used Car Lots” and “Used Car”. As your site gets some age and you get more links to it that page will more likely rank for Used Car Lots sooner than Used Car. Along that same token once it’s ranked for Used Car Lots for awhile and you get more and more links and authority since Used Car is part of Used Car Lots you’ll become more likely to start ranking for Used Car and here’s the important part. Initially since you have your first ranking keyword it will get a lot of counts for that keyword. However once you start ranking for the even higher volume keyword even if it is a lower rank (eg you rank #2 for Used Car Lot and only #9 for Used Car) than the count will start evening out. Once the better keyword outcounts the not as good than your site will automatically change to be more optimized for the higher traffic one while still being optimized for the lesser. So while you may drop to #5 or so for Used Car Lot your page will be better optimized to push up to say #7 for Used Car. Which will result in that subpage getting the absolute most traffic it can possibly get at any single time frame in the site’s lifespan. This is a hell of a lot better than making a future guestimate on how much authority that subpage will have a year down the road and its ability to achieve rankings WHILE your building the fucking thing; because even if you’re right and call it perfectly and that page does indeed start to rank for Used Car in the meantime you missed out on all the potential traffic Used Car Lot could have gotten you. Also keep in mind by rankings I don’t necessarily always mean the top 10. Sometimes rankings that result in traffic can even go as low as the 3rd page, and hell if that page 3 ranking gives you more traffic than the #1 slot for another keyword fuck that other keyword! Go for the gold at all times.

What About Prerankings?
See this is what the delimiter is for! If your page hasn’t achieved any rankings yet than it isn’t getting any new entry traffic you care about. So the page should be optimized for ALL or at least 3-6 of your keywords (whatever limit you set). This gives the subpage at least a chance at ranking for any one of the keywords while at the same time giving it the MOST keywords pushing its relevancy up. What I mean by that is, your LCD page hasn’t achieved rankings yet therefore it isn’t pushing its content towards either TV or Televisions. Since it has both essentially equaled out on the page than the page is more relevant to both keywords instead of only a single dominate one. So when it links to your Plasma Television subpage it still has the specific keyword Television instead of just TV thus upping the relevancy of your internal linking. Which brings up the final advanced tip I’ll leave you with.

Use the module to create optimal internal linking. You already have the pages and the keywords, its a very easy to do and short revision. Pass the page text or the navigation to your module. Have it parse for all links. If it finds a link that matches the domain of the current page (useful variable) then have it grab the top keyword count for that other page and replace the anchor text. Boom! You just got perfectly optimized internal linking that will only get better over time. :)

There ya go naysayers. Now you can say you’ve learned a SEO technique that’s both pure white hat and no matter how simple you explain it very much advanced.

April 22nd 2009 News

Oprah Effect on Twitter

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Oprah Winfrey, the icon that can turn any book or product into a best seller, posted her first Tweet on Friday on her show. There’s been much debate among loyal Twitter users about whether this spells the end for Twitter’s coolness, as soccer moms sign up in droves.

So what was the Oprah-Effect on Twitter? The following chart shows daily visits to Twitter from 1st January to 18th April (Oprah’s first Tweet was on the 17th).
Oprah Twitter.png

Share of US Internet visits to Twitter increased 24% on Friday, April 17, the day of Oprah’s first Tweet. Comparing visits with the previous Friday, visits were up 43%.

Hitwise clickstream data reveals that on April 17, 37% of visits to Twitter.com were new visitors (as opposed to returning). The service typically has a high ratio of new visitors as it is still very much in a growth phase. However, the percentage of new visitors was 5% higher on Friday than the previous day and the average for March. To give a benchmark, Facebook’s ratio of new visitors was 8% in March.

The search term “oprah twitter” was the #35 highest search term with the word “twitter” last week and the #7 with “oprah”. Considering that our search data is weekly and that the show only aired on Friday, this is impressive.

April 22nd 2009 Uncategorized

UK Internet users spending more time on social networks than shopping online

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UK Internet users are spending less of their online time shopping and more time browsing online media. During March 2009, 8.6% of all UK Internet visits went to online retail websites and 9.8% to social networking websites. A year ago, in March 2008, the figures were reversed: online retailers accounted for 9.7% of all UK Internet visits, and social networks 8.2%. Over the same time period, the share of UK Internet visits attributed to Entertainment websites (11.4% in March 2008, 11.6% in March 2009) and News and Media websites (5.0% in March 2008, 5.6% in March 2009) has also increased.

UK_Internet_traffic_to_social_networks_online_reteailers_2009_2008_chart.png

The growth of social networking, online video and the continuing popularity of news websites has meant that an increasing proportion of consumer’s online time in the UK has been devoted to online media. Historically this has gone hand in hand with the growth of online retail, but over the last 3 months online retailers seem to be really suffering from the economic downturn for the first time. Traffic to online retailers always peaks over the Christmas period, then declines during January and February, but picks up in March. Last year UK Internet traffic to online retailers increased by 0.8% between February and March, but this year it fell by 0.1%. The decline between December and February was also greater this year.

Electronics retailers and department stores have experienced the most significant declines in traffic since Christmas, although the recent Spring sales acted as a temporary boost for the latter category. However, despite the post-Christmas decline in online retail, there are a number of categories that continue to outperform the general market Online fashion was the fastest growing online retail category during 2009 and continues to perform well, despite growth slowing. Sports retailers are also doing well, helped in part by the demand for the new England football kit.

The good weather over the last few weeks has led to an increase in searches for garden furniture and tools, with a corresponding increase in traffic to House and Garden retailers. Finally, Classifieds websites have seen their UK Internet traffic increase by 15% over the last 12 months as people look to buy and sell second hand goods online.

Follow Hitwise UK on Twitter.

April 21st 2009 Uncategorized

Best Practices for Feeling Sorry for Yourself

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Over at Outspoken, the place where I secretly wish I worked (if I was 15 years younger and had any youthful hotness remaining), there was a firestorm over Lisa Barone’s post It’s Not the Recession, You Just SuckSome loved it, some didn’t, some seemed offended. I read it with detached bemusement, which is professionally my favorite emotional state. Being an elder statesman has it’s perks and

April 21st 2009 News

Top Searches on Hulu.com

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YouTube has unveiled several partnerships with studios to expand the selection of TV shows and movies available on the website. With YouTube adding premium content onto their website, this move starts to make them compete more directly with websites like Hulu. The wide variety and quick availability of content on Hulu has made the website become very popular, so we thought it would be interesting to see what people are searching for on Hulu.com to gain a sense of demand for particular shows. The top search taking place on Hulu.com during the week of March 21, 2009 was for the TV show Family Guy. 3 specific episodes of the Family Guy also made the top 500 internal site searches on Hulu.com – ‘Road to Germany’, ‘Chicken Fight’, and ‘Baby Not on Board’.

Top Internal Site Seaches on Hulu.com – Week of March 21, 2009
1. family guy
2. transformers cartoon
3. lie to me
4. the office
5. keeping up with the kardashians
6. 24
7. battlestar galactica
8. bones
9. damages
10. the simpsons

Not surprisingly, TV shows dominated the top 100 search terms for the week on Hulu.com with 83 search terms with 8 referring to various versions of Law & Order. The majority of the search terms were for specific titles of TV shows and movies, and in some cases, specific episodes, with very few searches for actors.

April 18th 2009 Uncategorized