serp and pagerank tools

What is the worth of my puny blog ? Here’s two snippets (download) to grab estimates from two sites. The first one is business-opportunities.biz, the second webvaluer.org.

According to www.business-opportunities.biz my blog is worth 1700 dollar. Their estimate is derived from the Technorati blog cosmos so it only works for blogs that are registered there.

use

That returns in my case $1,693.62

According to webvaluer.org my website is worth $7,549 US dollar. Their site returns a value for every type of site. In the page source there is a span format tag around the text

I cut it before and after the span tag, and use the php function strip_tags() to remove the span tag, and only the text string remains.

use :

How to make your own php fetch function :

• check the result page html source
• see what tag or phrase comes before the text you want (’Estimated Worth’)
• use explode() or split() to cut the source up in pieces on that phrase
• take the piece after the phrase (arrays are 0-based,use cut1[1] to get the second piece)
• cut that up at the first tag (’< /h1>‘) after the text you want
• use the first piece (cut2[0]) that holds the text you want

It’s easier to use source splitting for this sort of fetching than regular expressions, which is sooner meant to retrieve generic patterns (email addresses and stuff) from lots of pages (preg_match()), or an array of similar string from one page (preg_match_all(), for serp pages or report tables).

note : my php code highlighter refuses to display html tags in functions proper so in the code I added a blank space : $cut2=explode(’< /p>‘,$cut1[1]);
Remove the blanks from the html tag in the function for it to work proper or use the text source.

I want a quick way to check the competitors in a niche, and estimate what can I spend on a search engine marketing campaign to make money in the segment, using the search engines (read: Google).

For a quick test I dive into the money segment, got the top 70 search phrases of October off of 7Search and for each get the top 100 results, resulting in a mysql database with 7.000 url’s on 3500 domains.

Then I try three cross-sections to extract the top 25 domains in the segment :

• (100 - position) / 100 per result
• (100 - position) / 100 per result, +1 for first 10, +1 for first 6, +1 for first three
• AOL experience based percentage of search volume

rating by rank

If I rate the sites’ urls based on (100 - position) / 100 per result.

place 1 = 0.99, place 100 = 0, that yields this table :

That makes Amazon top dog for all phrases containing ‘money’. I know the first pages get most traffic, and that first method doesn’t express that, so I change the routine and do my old trick.

rating by rank, bonus for front page

(100 - pos) / 100, and
for place 1-3 3 points
for place 4-6 2 points
for place 7-10 1 points

That gives this table :

That still does not show what domains actually get the traffic I need for conversion.

It is easy to score in a low traffic niche and anyone can be a winner on long tails, “alabama ski resort”, but long tails only get you a few hits (and wonder if they are serious?). And these results doesn’t give me a clue what I can spend (or what my competition would be willing to spend) on the actual traffic spots.

So I am going to estimate what traffic every site gets. I need search volumes and percentages for the serp ranks. I grabbed the search volumes per phrase from 7Search. For percentages, Aaron Wall quotes an old AOL source on the average click through rate of search engine result pages per spot on the first page :

That was what i was looking for. Given these percentages I can estimate the traffic any spot on the search engine result front page in Google would generate, and that yields a more realistic table of the money segment :

That shows which sites actively target and get the traffic in the segment, a site like amazon doesn’t show in the top of the last table.

One way of testing the validity of the estimates is comparing with alexa rank, doing a quick SeoQuake toolbar check :

That’s roughly correct based on old AOL percentages (well done, Aaron) and Oktober’s search volumes. It does not work for youtube, msn and others that have an alexa rank based on the entire domain. Being a search engine traffic estimate it doesn’t cover your ‘audience’ (returning visitors on bookmarks and referrals off of other sites (which are included in the alexa ranking) or other segments.

Problogger for example, according to that calculation would get about 6K hits through Google but the Alexa rank indicates it has ~~160K hits a month. That indicates high return visits and direct traffic, a high usability and I think they get traffic from other segments (’blog’ ?).

The use of it

Why did I start doing this ? To estimate a budget for niche penetration.

If I were interested in a niche and have a 1% conversion at $100,- per year per conversion, what would I be able to spend to get Bidvertisers’ traffic in the search engines ? With their traffic and my conversion, 730.000/100 = 7300 conversions per month =y 88.000 a year @100/conversion = 8.8 million dollar gross revenue on search engine traffic conversions.

If my marketing budget is 20% of gross sales, for a year project that amounts to 1.7 million dollar. If I already had 300K hits my budget would be a million.

That (roughly) answers my question.

I have my doubts about the use of a tool like this, it could function as quick way to scan a segment, make a ‘heatmap’ and pinpoint the soft spots that are easy to penetrate and get a foothold, but that would require some stiff programming and a lot of switches, as well as processing a lot more segments. Nice project for the winter.

A rather obsolete post. I hacked a quick referrer tracking script together because I wanted to see how Googlebot indexed my serp tool pages. I can use Google analytics or phpMyVisites, but that is not as rewarding as keeping my own logs.

I start with a mysql table LOG to store the traffic data

on every page I track, I start with

The function log_hit() relies on the php $_SERVER array that holds all data the web server collects:

the connect_data() function is standard mysql connection

It is far from perfect, but it works. It helps check the crawl-rate of pages. You can filter out the useragent ‘Googlebot’ and run a query grouping useragent by date and see what times Googlebot comes by.

…or exclude all records if the UserAgent indicates it was a Bot, and get a listing of organic beings visiting the pages :

…that shows ‘organic’ visitors.

other resources
tek-tips.com/ Limit Requests per day by IP

morrowland.com/ HOW TO SHOW CURRENT VIEWERS IN PHP
phpMyVisites open source free referrer and traffic analysis