The Effect of Inbound Links

The Effect of Inbound Links

It has already been shown that each additional inbound link for a web page always increases that page's PageRank. Taking a look at the PageRank algorithm, which is given by
PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))
one may assume that an additional inbound link from page X increases the PageRank of page A by
d � PR(X) / C(X)
where PR(X) is the PageRank of page X and C(X) is the total number of its outbound links. But page A usually links to other pages itself. Thus, these pages get a PageRank benefit also. If these pages link back to page A, page A will have an even higher PageRank benefit from its additional inbound link.
The single effects of additional inbound links shall be illustrated by an example.

We regard a website consisting of four pages A, B, C and D which are linked to each other in circle. Without external inbound links to one of these pages, each of them obviously has a PageRank of 1. We now add a page X to our example, for which we presume a constant Pagerank PR(X) of 10. Further, page X links to page A by its only outbound link. Setting the damping factor d to 0.5, we get the following equations for the PageRank values of the single pages of our site:

PR(A) = 0.5 + 0.5 (PR(X) + PR(D)) = 5.5 + 0.5 PR(D)
PR(B) = 0.5 + 0.5 PR(A)
PR(C) = 0.5 + 0.5 PR(B)
PR(D) = 0.5 + 0.5 PR(C)
Since the total number of outbound links for each page is one, the outbound links do not need to be considered in the equations. Solving them gives us the following PageRank values:
PR(A) = 19/3 = 6.33
PR(B) = 11/3 = 3.67
PR(C) = 7/3 = 2.33
PR(D) = 5/3 = 1.67
We see that the initial effect of the additional inbound link of page A, which was given by
d � PR(X) / C(X) = 0,5 � 10 / 1 = 5
is passed on by the links on our site.
The Influence of the Damping Factor
The degree of PageRank propagation from one page to another by a link is primarily determined by the damping factor d. If we set d to 0.75 we get the following equations for our above example:
PR(A) = 0.25 + 0.75 (PR(X) + PR(D)) = 7.75 + 0.75 PR(D)
PR(B) = 0.25 + 0.75 PR(A)
PR(C) = 0.25 + 0.75 PR(B)
PR(D) = 0.25 + 0.75 PR(C)
Solving these equations gives us the following PageRank values:
PR(A) = 419/35 = 11.97
PR(B) = 323/35 = 9.23
PR(C) = 251/35 = 7.17
PR(D) = 197/35 = 5.63
First of all, we see that there is a significantly higher initial effect of additional inbound link for page A which is given by
d � PR(X) / C(X) = 0.75 � 10 / 1 = 7.5
This initial effect is then propagated even stronger by the links on our site. In this way, the PageRank of page A is almost twice as high at a damping factor of 0.75 than it is at a damping factor of 0.5. At a damping factor of 0.5 the PageRank of page A is almost four times superior to the PageRank of page D, while at a damping factor of 0.75 it is only a little more than twice as high. So, the higher the damping factor, the larger is the effect of an additional inbound link for the PageRank of the page that receives the link and the more evenly distributes PageRank over the other pages of a site.
The Actual Effect of Additional Inbound Links
At a damping factor of 0.5, the accumulated PageRank of all pages of our site is given by
PR(A) + PR(B) + PR(C) + PR(D) = 14
Hence, by a page with a PageRank of 10 linking to one page of our example site by its only outbound link, the accumulated PageRank of all pages of the site is increased by 10. (Before adding the link, each page has had a PageRank of 1.) At a damping factor of 0.75 the accumulated PageRank of all pages of the site is given by
PR(A) + PR(B) + PR(C) + PR(D) = 34
This time the accumulated PageRank increases by 30. The accumulated PageRank of all pages of a site always increases by
(d / (1-d)) � (PR(X) / C(X))
where X is a page additionally linking to one page of the site, PR(X) is its PageRank and C(X) its number of outbound links. The formula presented above is only valid, if the additional link points to a page within a closed system of pages, as, for instance, a website without outbound links to other sites. As far as the website has links pointing to external pages, the surplus for the site itself diminishes accordingly, because a part of the additional PageRank is propagated to external pages.
The justification of the above formula is given by Raph Levien and it is based on the Random Surfer Model. The walk length of the random surfer is an exponential distribution with a mean of (d/(1-d)). When the random surfer follows a link to a closed system of web pages, he visits on average (d/(1-d)) pages within that closed system. So, this much more PageRank of the linking page - weighted by the number of its outbound links - is distributed to the closed system.
For the actual PageRank calculations at Google, Lawrence Page und Sergey Brin claim to usually set the damping factor d to 0.85. Thereby, the boost for a closed system of web pages by an additional link from page X is given by
(0.85 / 0.15) � (PR(X) / C(X)) = 5.67 � (PR(X) / C(X))
So, inbound links have a far larger effect than one may assume.
The PageRank-1 Rule
Users of the Google Toolbar often notice that pages with a certain Toolbar PageRank have an inbound link from a page with a Toolbar PageRank which is higher by one. Some take this observation to doubt the validity of the PageRank algorithm presented here for the actual ranking methods of the Google search engine. It shall be shown, however, that the PageRank-1 rule complies with the PageRank algorithm.
Basically, the PageRank-1 rule proves the fundamental principle of PageRank. Web pages are important themselves if other important web pages link to them. It is not necessary for a page to have many inbound links to rank well. A single link from a high ranking page is sufficient.
To show the actual consistance of the PageRank-1 rule with the PageRank algorithm several factors have to be taken into consideration. First of all, the toolbar PageRank is a logarithmically scaled version of real PageRank values. If the PageRank value of one page is one higher than the PageRank value of another page in terms of Toolbar PageRank, than its real PageRank can at least be higher by an amount which equals the logarithmical basis for the scalation of Toolbar PageRank. If the logarithmical basis for the scalation is 6 and the toolbar PageRank of a linking Page is 5, then the real PageRank of the page which receives the link can be at least 6 times smaller to make that page still get a toolbar PageRank of 4.
However, the number of outbound links on the linking page thwarts the effect of the logarithmical basis, because the PageRank propagation from one page to another is devided by the number of outbound links on the linking page. But it has already been shown that the PageRank benefit by a link is higher than PageRank algorithm's term d(PR(Ti)/C(Ti)) pretends. The reason is that the PageRank benefit for one page is further distributed to other pages within the site. If those pages link back as it usualy happens, the PageRank benefit for the page which initially received the link is accordingly higher. If we assume that at a high damping factor the logarithmical basis for PageRank scalation is 6 and a page receives a PageRank benefit which is twice as high as the PageRank of the linking page devided by the number of its outbound links, the linking page could have at least 12 outbound links so that the Toolbar PageRank of the page receiving the link is still at most one lower than the toolbar PageRank of the linking page.
A number of 12 outbound links admittedly seems relatively small. But normally, if a page has an external inbound link, this is not the only one for that page. Most likely other pages link to that page and propagate PageRank to it. And if there are examples where a page receives a single link from another page and the PageRanks of both pages comply the PageRank-1 rule although the linking page has many outbound links, this is first of all an indication for the linking page's toolbar PageRank being at the upper end of its scale. The linking page could be a "high" 5 and the page receiving the link could be a "low" 4. In this way, the linking page could have up to 72 outbound links. This number rises accordingly if we assume a higher logarithmical basis for the scalation of Toolbar PageRank.

The Implementation of PageRank in the Google Search Engine

The Implementation of PageRank in the Google Search Engine

Regarding the implementation of PageRank, first of all, it is important how PageRank is integrated into the general ranking of web pages by the Google search engine. The proceedings have been described by Lawrencec Page and Sergey Brin in several publications. Initially, the ranking of web pages by the Google search engine was determined by three factors:
Page specific factors
Anchor text of inbound links
PageRank
Page specific factors are, besides the body text, for instance the content of the title tag or the URL of the document. It is more than likely that since the publications of Page and Brin more factors have joined the ranking methods of the Google search engine. But this shall not be of interest here.
In order to provide search results, Google computes an IR score out of page specific factors and the anchor text of inbound links of a page, which is weighted by position and accentuation of the search term within the document. This way the relevance of a document for a query is determined. The IR-score is then combined with PageRank as an indicator for the general importance of the page. To combine the IR score with PageRank the two values are multiplicated. It is obvious that they cannot be added, since otherwise pages with a very high PageRank would rank high in search results even if the page is not related to the search query.
Especially for queries consisting of two or more search terms, there is a far bigger influence of the content related ranking criteria, whereas the impact of PageRank is mainly visible for unspecific single word queries. If webmasters target search phrases of two or more words it is possible for them to achieve better rankings than pages with high PageRank by means of classical search engine optimisation.
If pages are optimised for highly competitive search terms, it is essential for good rankings to have a high PageRank, even if a page is well optimised in terms of classical search engine optimisation. The reason therefore is that the increase of IR score deminishes the more often the keyword occurs within the document or the anchor texts of inbound links to avoid spam by extensive keyword repetition. Thereby, the potentialities of classical search engine optimisation are limited and PageRank becomes the decisive factor in highly competitive areas.
The PageRank Display of the Google Toolbar
PageRank became widely known by the PageRank display of the Google Toolbar. The Google Toolbar is a browser plug-in for Microsoft Internet Explorer which can be downloaded from the Google web site. The Google Toolbar provides some features for searching Google more comfortably.

The Google Toolbar displays PageRank on a scale from 0 to 10. First of all, the PageRank of an actually visited page can be estimated by the width of the green bar within the display. If the user holds his mouse over the display, the Toolbar also shows the PageRank value. Caution: The PageRank display is one of the advanced features of the Google Toolbar. And if those advanced features are enabled, Google collects usage data. Additionally, the Toolbar is self-updating and the user is not informed about updates. So, Google has access to the user's hard drive.

If we take into account that PageRank can theoretically have a maximum value of up to dN+(1-d), where N is the total number of web pages and d is usually set to 0.85, PageRank has to be scaled for the display on the Google Toolbar. It is generally assumed that the scalation is not linearly but logarithmically. At a damping factor of 0.85 and, therefore, a minimum PageRank of 0.15 and at an assumed logaritmical basis of 6 we get a scalation as follows:
Toolbar-PR Tats�chlicher PR
0/10 0.15 - 0.9
1/10 0.9 - 5.4
2/10 5.4 - 32.4
3/10 32.4 - 194.4
4/10 194.4 - 1,166.4
5/10 1,166.4 - 6,998.4
6/10 6,998.4 - 41,990.4
7/10 41,990.4 - 251,942.4
8/10 251,942.4 - 1,511,654.4
9/10 1,511,654.4 - 9,069,926.4
10/10 9,069,926.4 - 0.85 � N + 0.15
It is uncertain if in fact a logarithmical scalation in a strictly mathematical sense takes place. There is likely a manual scalation which follows a logarithmical scheme, so that Google has control over the number of pages within the single Toolbar PageRank ranges. The logarithmical basis for this scheme should be between 6 and 7, which can for instance be rudimentary deduced from the number of inbound links of pages with a high Toolbar PageRank from pages with a Toolbar PageRank higher than 4, which are shown by Googe using the link command.
The Toolbar's PageRank Files
Even webmasters who do not want to use the Google Toolbar or the Internet Explorer permanently for security and privacy concerns have the possibility to check the PageRank values of their pages. Google submits PageRank values in simple text files to the Toolbar. In former times, this happened via XML. The switch to text files occured in August 2002.
The PageRank files can be requested directly from the domain www.google.com. Basically, the URLs for those files look like follows (without line breaks):
http://www.google.com/search?client=navclient-auto&
ch=0123456789&features=Rank&q=info:http://www.domain.com/
There is only one line of text in the PageRank files. The last cipher in this line is PageRank.
The parameters incorporated in the above shown URL are inevitable for the display of the PageRank files in a browser. The value "navclient-auto" for the parameter "client" identifies the Toolbar. Via the parameter "q" the URL is submitted. The value "Rank" for the parameter "features" determines that the PageRank files are requested. If it is omitted, Google's servers still transmit XML files. The parameter "ch" transfers a checksum for the URL to Google, whereby this checksum can only change when the Toolbar version is updated by Google.
Thus, it is necessary to install the Toolbar at least once to find out about the checksum of one's URLs. To track the communication between the Toolbar and Google, often the use of packet sniffers, local proxies an similar tools is suggested. But this is not necessarily needed, since the PageRank files are cached by the Internet Explorer. So, the checksums can simply been found out by having a look at the folder Temporary Internet Files. Knowing the checksums of your URLs, you can view the PageRank files in your browser and you do not have to accept Google's 36 years lasting cookies.
Since the PageRank files are kept in the browser cache and, thus, are clearly visible, and as long as requests are not automated, watching the PageRank files in a browser should not be a violation of Google's Terms of Service. However, you should be cautious. The Toolbar submits its own User-Agent to Google. It is:
Mozilla/4.0 (compatible; GoogleToolbar 1.1.60-deleon; OS SE 4.10)
1.1.60-deleon is a Toolbar version which may of course change. OS is the operating system that you have installed. So, Google is able to identify requests by browsers, if they do not go out via a proxy and if the User-Agent is not modified accordingly.
Taking a look at IE's cache, one will normally notice that the PageRank files are not requested from the domain www.google.com but from IP addresses like 216.239.33.102. Additionally, the PageRank files' URLs often contain a parameter "failedip" that is set to values like "216.239.35.102;1111" (Its function is not absolutely clear). The IP addresses are each related to one of Google's seven data centers and the reason for the Toolbar querying IP-addresses is most likely to control the PageRank display in a better way, especially in times of the "Google Dance".
The PageRank Display at the Google Directory
Webmasters who do not want to check the PageRank files that are used by the toolbar have another possibility to receive information about the PageRank of their sites by means of the Google Directory (directory.google.com).

The Google Directory is a dump of the Open Directory Project (dmoz.org), which shows the PageRank for listed documents similarly to the Google Toolbar display scaled and by means of a green bar. In contrast to the Toolbar, the scale is from 1 to 7. The exact value is not displayed, but it can be determined by the divided bar respectively the width of the single graphics in the source code of the page if one is not sure by looking at the bar.

By comparing the Toolbar PageRank of a document with its Directory PageRank, a more exact estimation of a pages PageRank can be deduced, if the page is listed with the ODP. This connection was mentioned first by Chris Raimondi (www.searchnerd.com/pagerank).

Especially for pages with a Toolbar PageRank of 5 or 6, one can appraise if the page is on the upper or the lower end of its Toolbar scale. It shall be noted that for the comparison the Toolbar PageRank of 0 was not taken into account. It can easily be verified that this is appropriate by looking at pages with a Toolbar PageRank of 3. However, it has to be considered that for a verification pages of the Google Directory respectively the ODP with a Toolbar PageRank of 4 or lower have to be chosen, since otherwise no pages linked from there with a Toolbar PageRank of 3 will be found.

What is The PageRank Algorithm?

The PageRank Algorithm

The original PageRank algorithm was described by Lawrence Page and Sergey Brin in several publications. It is given by
PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))
where
PR(A) is the PageRank of page A,
PR(Ti) is the PageRank of pages Ti which link to page A,
C(Ti) is the number of outbound links on page Ti and
d is a damping factor which can be set between 0 and 1.
So, first of all, we see that PageRank does not rank web sites as a whole, but is determined for each page individually. Further, the PageRank of page A is recursively defined by the PageRanks of those pages which link to page A.
The PageRank of pages Ti which link to page A does not influence the PageRank of page A uniformly. Within the PageRank algorithm, the PageRank of a page T is always weighted by the number of outbound links C(T) on page T. This means that the more outbound links a page T has, the less will page A benefit from a link to it on page T.
The weighted PageRank of pages Ti is then added up. The outcome of this is that an additional inbound link for page A will always increase page A's PageRank.
Finally, the sum of the weighted PageRanks of all pages Ti is multiplied with a damping factor d which can be set between 0 and 1. Thereby, the extend of PageRank benefit for a page by another page linking to it is reduced.
The Random Surfer Model
In their publications, Lawrence Page and Sergey Brin give a very simple intuitive justification for the PageRank algorithm. They consider PageRank as a model of user behaviour, where a surfer clicks on links at random with no regard towards content.
The random surfer visits a web page with a certain probability which derives from the page's PageRank. The probability that the random surfer clicks on one link is solely given by the number of links on that page. This is why one page's PageRank is not completely passed on to a page it links to, but is devided by the number of links on the page.
So, the probability for the random surfer reaching one page is the sum of probabilities for the random surfer following links to this page. Now, this probability is reduced by the damping factor d. The justification within the Random Surfer Model, therefore, is that the surfer does not click on an infinite number of links, but gets bored sometimes and jumps to another page at random.
The probability for the random surfer not stopping to click on links is given by the damping factor d, which is, depending on the degree of probability therefore, set between 0 and 1. The higher d is, the more likely will the random surfer keep clicking links. Since the surfer jumps to another page at random after he stopped clicking links, the probability therefore is implemented as a constant (1-d) into the algorithm. Regardless of inbound links, the probability for the random surfer jumping to a page is always (1-d), so a page has always a minimum PageRank.
A Different Notation of the PageRank Algorithm
Lawrence Page and Sergey Brin have published two different versions of their PageRank algorithm in different papers. In the second version of the algorithm, the PageRank of page A is given as
PR(A) = (1-d) / N + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))
where N is the total number of all pages on the web. The second version of the algorithm, indeed, does not differ fundamentally from the first one. Regarding the Random Surfer Model, the second version's PageRank of a page is the actual probability for a surfer reaching that page after clicking on many links. The PageRanks then form a probability distribution over web pages, so the sum of all pages' PageRanks will be one.
Contrary, in the first version of the algorithm the probability for the random surfer reaching a page is weighted by the total number of web pages. So, in this version PageRank is an expected value for the random surfer visiting a page, when he restarts this procedure as often as the web has pages. If the web had 100 pages and a page had a PageRank value of 2, the random surfer would reach that page in an average twice if he restarts 100 times.
As mentioned above, the two versions of the algorithm do not differ fundamentally from each other. A PageRank which has been calculated by using the second version of the algorithm has to be multiplied by the total number of web pages to get the according PageRank that would have been caculated by using the first version. Even Page and Brin mixed up the two algorithm versions in their most popular paper "The Anatomy of a Large-Scale Hypertextual Web Search Engine", where they claim the first version of the algorithm to form a probability distribution over web pages with the sum of all pages' PageRanks being one.
In the following, we will use the first version of the algorithm. The reason is that PageRank calculations by means of this algorithm are easier to compute, because we can disregard the total number of web pages.
The Characteristics of PageRank
The characteristics of PageRank shall be illustrated by a small example.

We regard a small web consisting of three pages A, B and C, whereby page A links to the pages B and C, page B links to page C and page C links to page A. According to Page and Brin, the damping factor d is usually set to 0.85, but to keep the calculation simple we set it to 0.5. The exact value of the damping factor d admittedly has effects on PageRank, but it does not influence the fundamental principles of PageRank. So, we get the following equations for the PageRank calculation:


PR(A) = 0.5 + 0.5 PR(C)
PR(B) = 0.5 + 0.5 (PR(A) / 2)
PR(C) = 0.5 + 0.5 (PR(A) / 2 + PR(B))
These equations can easily be solved. We get the following PageRank values for the single pages:
PR(A) = 14/13 = 1.07692308
PR(B) = 10/13 = 0.76923077
PR(C) = 15/13 = 1.15384615
It is obvious that the sum of all pages' PageRanks is 3 and thus equals the total number of web pages. As shown above this is not a specific result for our simple example.
For our simple three-page example it is easy to solve the according equation system to determine PageRank values. In practice, the web consists of billions of documents and it is not possible to find a solution by inspection.
The Iterative Computation of PageRank
Because of the size of the actual web, the Google search engine uses an approximative, iterative computation of PageRank values. This means that each page is assigned an initial starting value and the PageRanks of all pages are then calculated in several computation circles based on the equations determined by the PageRank algorithm. The iterative calculation shall again be illustrated by our three-page example, whereby each page is assigned a starting PageRank value of 1.
Iteration PR(A) PR(B) PR(C)
0 1 1 1
1 1 0.75 1.125
2 1.0625 0.765625 1.1484375
3 1.07421875 0.76855469 1.15283203
4 1.07641602 0.76910400 1.15365601
5 1.07682800 0.76920700 1.15381050
6 1.07690525 0.76922631 1.15383947
7 1.07691973 0.76922993 1.15384490
8 1.07692245 0.76923061 1.15384592
9 1.07692296 0.76923074 1.15384611
10 1.07692305 0.76923076 1.15384615
11 1.07692307 0.76923077 1.15384615
12 1.07692308 0.76923077 1.15384615
We see that we get a good approximation of the real PageRank values after only a few iterations. According to publications of Lawrence Page and Sergey Brin, about 100 iterations are necessary to get a good approximation of the PageRank values of the whole web.
Also, by means of the iterative calculation, the sum of all pages' PageRanks still converges to the total number of web pages. So the average PageRank of a web page is 1. The minimum PageRank of a page is given by (1-d). Therefore, there is a maximum PageRank for a page which is given by dN+(1-d), where N is total number of web pages. This maximum can theoretically occur, if all web pages solely link to one page, and this page also solely links to itself.

How Do Search Engines Work?

To many people, Google IS the internet. It’s the default homepage and the first port of call before accessing any site. It’s arguably the most important invention since the Internet itself. Without search engines, content would all be hand picked – just like newspapers and magazines. And while search engines have changed a lot since those first humble beginnings – and Google certainly isn’t the only search engine out there –  the underlying principles are the same as they always were.

Do you know how search engines work? There are three basic stages for a search engine: crawling – where content is discovered; indexing, where it is analysed and stored in huge databases; and retrieval, where a user query fetches a list of relevant pages.

Crawling

Crawling is where it all begins – the acquisition of data about a website. This involves scanning the site and getting a complete list of everything on there – the page title, images, keywords it contains, and any other pages it links to – at a bare minimum. Modern crawlers may cache a copy of the whole page, as well as look for some additional information such as the page layout, where the advertising units are, where the links are on the page (featured prominently in the article text, or hidden in the footer?).

How is a website crawled exactly? An automated bot – a spider – visits each page, just like you or I would, only very quickly. Even in the earliest days, Google reported that they were reading a few hundred pages a second. If you’d like to learn how to make your own basic web crawler in PHP – it was one of the first articles I wrote here and well worth having a go at (just don’t expect to make the next Google).

The crawler then adds all the new links it found to a list of places to crawl next – in addition to re-crawling sites again to see if anything has changed. It’s a never-ending process, really.


Any site that is linked to from another site already indexed, or any site that manually asked to be indexed, will eventually be crawled – some sites more frequently than others and some to a greater depth. If the site is huge and content hidden many clicks away from the homepage, the crawler bots may actually give up. There are ways to ask search engines NOT to index a site, though this is rarely used to block an entire website.

There was even a time when large parts of the Internet were essentially invisible to search engines – the so-called “deep web” – but this is rare now. TOR-hosted websites (What is Onion Routing?) for example, remain unindexed by Google, and are only accessible by connecting to the TOR network and knowing the address.

how do search engines work

Indexing

You’d be forgiven for thinking this is an easy step – indexing is the process of taking all of that data you have from a crawl, and placing it in a big database. Imagine trying to a make a list of all the books you own, their author and the number of pages. Going through each book is the crawl and writing the list is the index. But now imagine it’s not just a room full of books, but every library in the world. That’s pretty much a small-scale version of what Google does.

All of this data is stored in vast data-centres with thousands of petabytes worth of drives.

Ranking & Retrieval

The last step is what you see – you type in a search query, and the search engine attempts to display the most relevant documents it finds that match your query. This is the most complicated step, but also the most relevant to you or I, as web developers and users. It is also the area in which search engines differentiate themselves (though, there was some evidence that Bing was actually copying some Google results). Some work with keywords, some allow you to ask a question, and some include advanced features like keyword proximity or filtering by age of content.

The ranking algorithm checks your search query against billions of pages to determine how relevant each one is. This operation is so complex that companies closely guard their own ranking algorithms as patented industry secrets. Why? Competitive advantage for a start – so long as they are giving you the best search results, they can stay on top of the market. Secondly, to prevent gaming of the system and giving an unfair advantage to one site over another.

Once the internal methodology of any system is fully understood, there will always be those who try to “hack” it – discover the ranking factors and exploit them for monetary gain.

Exploiting the ranking algorithm has in fact been commonplace since search engines began, but in the last 3 years or so Google has really made that difficult. Originally, sites were ranked based on how many times a particular keyword was mentioned. This led to “keyword stuffing”, where pages are filled with mostly nonsense so long as it includes the keyword everywhere.

Then the concept of importance based on linking was introduced  – more popular sites would be more linked to, obviously – but this led to a proliferation of spammed links all over the web. Now each link is determined to have a different value, depending on the “authority” of the site in question. If a high level government agency links to you, it’s worth far more than a link found in a free-for-all “link directory”.


search engine explanation

Today, the understanding of the exact algorithm is even more shrouded in mystery than ever, and the dark art of “Search Engine Optimization” has largely been crippled – the advice now is to focus on providing the best content, with a great user experience (how crazy, right?!). Considering that almost 60% of all searches end up clicking the first result, it’s easy to see why ranking your page well is so important.

12 Components of a Digital Marketing Strategy

As we’ve been watching the trends in the medical device industry, we see that it is currently valued at a staggering $100 billion dollars. Investment in this industry has more than doubled in the past two decades and is expected to grow to $133 billion in 2016. Many companies are entering this market, but due to the high level of competition, they aren’t capable of making an impact. One of the mistakes that many of these companies are making is not investing in their digital marketing efforts to support the overall marketing objective. Whether you’re a medical device company or not, not having a digital marketing strategy leaves potential revenue on the table by not reaching the target consumers through all digital channels. A digital marketing strategy is essential to every company’s existence.

1. Website:

Your website is a vital part of the digital marketing mix, and if designed correctly, can make all your marketing efforts more effective. It is crucial to build a website strategy that aligns with the brand platform of your company. Everything is done with purpose towards a specific goal, making it easy to communicate your value. In today’s online landscape, your website must:

In today’s online landscape, your website must:

Be responsive and mobile friendly
Communicate your company’s values up front
Use relevant and up-to-date content
Have product-specific landing pages that can generate leads
Integrate with customer relationship management and marketing automation tools
2. Email:

A solid digital marketing strategy requires a strong email strategy. Email marketing is one of the most effective ways to educate large audiences about your product or service.

A successful email marketing strategy will:

Drive traffic to specific points
Educate and inform prospective buyers with new content
Help you stay top of mind
Build credibility
Establish thought leadership
If you want to generate leads, convert leads, and develop a relationship with your customers, you must use email marketing effectively.

3. Content:

Today’s consumers are empowered to seek out high-quality digital resources and experiences that lead to better, independent decision-making. Without good content, there’s no reason to visit a company’s website, read their tweets, open their emails, or care about anything they say. Most importantly, there’s no reason to interact with a company or build a relationship with them. Your company can capture the attention of a potential buyer who wants to know more, but unless your website provides the right content, you won’t be able to convert them. Today’s buyers want companies to facilitate the buying process by providing the right information needed to make a decision without any effort on their part.

A good content strategy involves the following:

Create content that represents your brand’s values and vision
Share relevant content across all social media channels to present your company to a wider audience
Be original and offer a variety of content types
Utilize your current and past successes to compile presentable case studies on your website. This type of content presents your company’s credibility and impact on the industry to all website visitors
Ensure that all your content messaging is aligned with the overall brand platform
Use the right content for your target audience
4. Search (SEO):

Did you know that “77% of online health seekers say they begin their session at a search engine” (Pew Research Center)? An essential part of your digital marketing strategy, whether you’re a medical device company or not, is to search for keywords and phrases that individuals might use to find your medical device. If your company does not appear in the search results, you should invest in SEO measures and online advertising to start increasing your brand exposure. These keywords are the gateway to reaching your potential customers from all around the world.

5. Social:

The most effective form of word of mouth is happening online. Now with social media, consumers utilize these channels to express their opinions, learn about new products, and engage with brands and key influencers. As a medical device company, you must ensure that you are also active on these channels and use social listening tools to be aware of what consumers are talking about in order to address their needs directly and keep track of your brand image. In addition, your social media presence can be targeted towards building relationships with key industry influencers in order to reach a wider audience and generate leads. Overall, “54% of B2B marketers said they have generated leads from social media” (CMO).

6. Paid Ads:

A digital marketing strategy is incomplete without the investment in paid ads. In today’s competitive landscape, visibility is key. You cannot expect customers to flock to your website as soon as your product is released. Organic search is very valuable but paid advertisements, such as Google Adwords and display ads, is crucial in gaining exposure in search results.

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Webcast, January 12th: Leveraging Urgency and Scarcity for Increased Sales
Here are 5 reasons why you should invest in paid ads:

You can choose to pay only when the interested individual clicks on the ad
You can control your spending budget
You can reach targeted consumers through the right channels
Success results are immediate
It can be used as an SEO testing tool
7. Lead Management:

The overall objective of all your digital marketing efforts is to generate leads. It is your responsibility to be able to effectively manage these leads, nurture them with the appropriate content, and eventually turn them into customers. “79% of marketing leads never convert into sales. Lack of lead nurturing is the common cause of this poor performance” (Marketing Sherpa). Do you have a lead nurturing strategy in place? Are you sending marketing qualified leads to your sales teams?

8. Marketing Automation:

“80% of marketing automation users saw their number of leads increase, and 77% saw the number of conversions increase” VB Insight. Generating leads has no value if your company is not following up on them and nurturing them properly. One of the key advantages of utilizing a marketing automation system is the fact that it is customizable based on your various targets, sales cycles, promotions, or any other strategic plan. This process makes it much easier to monitor leads as they move through the sales cycle. Therefore, you can maximize the potential of every active lead that enters that cycle.

9. Webinars:

Integrating webinars in your digital marketing strategy is key to positioning your company as a thought leader in your industry. Especially in the ever-changing medical device market, it is crucial to continually educate consumers and individuals in the industry to build trust, increase web traffic and brand awareness, and generate leads. Webinars can also be repurposed for multiple campaigns.

10. Videos:

By implementing video in your digital marketing strategy, you create engaging content that consumers can easily view and share. Based on recent research, “64% of website visitors are more likely to buy a product after watching a video”(VideoBrewery). Therefore, every medical device company should take advantage of this video marketing trend and create original video campaigns that present the company’s values, product features, and the lucrative benefits to the consumer.

11. Analytics:

One of the most valuable elements of having a digital marketing strategy is the fact that you can continually monitor the outcomes and be able to optimize your strategy with each campaign iteration. There are several analytics tools that will assist you in tracking the progress of your marketing efforts in order to be able to analyze and adapt over time. This availability of data is key to maximizing your return on investment.

12. Sales Tools:

Every company, especially one in the medical device industry, requires an active sales force. However, this sales force is ineffective without the right set of sales tools. Your salespeople are your army and you must be able to provide them with the proper ammunition in order to increase your chances of winning in this competitive landscape. As part of your digital marketing strategy, it is essential to invest in a robust set of sales tools, such as brochures, sales presentations, mobile sales app, and a sales deck, in order to empower your sales force and increase the success rate of your campaigns.

We are now living in the digital age. Traditional marketing alone won’t result in the profits you’re looking for. Marketing in digital channels is a requirement. There is no way around it. Just like you devoted a lot of your time and energy into developing your product, it is essential to invest in a comprehensive digital strategy to introduce your product to your targeted markets and continually manage your brand presence. Ensure that you measure your actions so you understand your digital footprint and whether you are maximizing the potential of your marketing campaign. When done effectively, this can set you apart from your competitors and lead to sustainable success for your medical device product.

The 4 C's and 4 P's of Marketing | What's the Diffrence?

Many people who have taken a marketing course have learned about the "4 P's" of marketing. Are Product, Price, Place and Promotion elements of this marketing formula something from the past?
Bob Lauterborn, professor of advertising at the University of North Carolina has tracked the success of new products introduced into the U.S. According to Bob, 80 percent of new products fail each year. With such a high failure rate, Bob notes that something isn't working with our "mindset". He wants to replace the Four P's with his Four C's.
Brand Strategy Marketing

Consumer wants and needs (vs. Products)
You can't develop products and then try to sell them to a mass market. You have to study consumer wants and needs and then attract consumers one by one with something each one wants. Author of the movie Field of Dreams, J.P. Cancilla may have exclusive rights to the phrase "build it and they will come". In most cases, you have to find out what people want and then "build" it for them, their way.
Cost to satisfy (vs. Price)
You have to realize that price - measured in dollars - is one part of the cost to satisfy. If you sell hamburgers, for example, you have to consider the cost of driving to your restaurant, the cost of conscience of eating meat, etc. One of the most difficult places to be in the business world is the retailer selling at the lowest price. If you rely strictly on price to compete you are vulnerable to competition - in the long term.
Convenience to buy (vs. Place)
You must think of convenience to buy instead of place. You have to know how each subset of the market prefers to buy - on the Internet, from a catalogue, on the phone, using credit cards, etc. Lands End clothing, Amazon Books and Dell Computers are just a few businesses who do very well over the Internet.
Communication (vs. Promotion)
You have to consider the communication instead of promotion. Promotion is manipulative (ouch!) - it's from the seller. Communication requires a give and take between the buyer and seller (that's nicer). Be creative and you can make any advertising "interactive". Use phone numbers, your web site address, etc. to help here. And listen to your customers when they are "with" you.
Developing a brand takes into account these considerations. Developing a brand is developing a promise. When you take into consideration the "4 C's" noted above you begin the process of developing a brand! Custom Fit Online follows the "4 C's" approach when developing strategy for our clients. These principals can also be applied online.

INBOUND MARKETING VS. OUTBOUND MARKETING: WHAT’S THE DIFFERENCE?

If you run a business, then you know how important marketing is in spreading the word about your company’s products and services. If you don’t market your company, then you won’t get any customers. This means that your company’s success relies heavily on your marketing campaign. While traditionally, the use of outbound marketing was the most common strategy, this has quickly changed in the last few years. These days, many companies have turned towards inbound marketing strategies for their marketing tactics. If you are unsure of what the differences are between outbound vs inbound marketing, read on. Understanding the pros and cons of both will allow you to create a better marketing strategy to fit the needs of your company.

Outbound Marketing
Outbound marketing is a strategy in which a business advertises its products and services by presenting information to consumers even if they are not looking for those products or services. Because of this, outbound marketing has been commonly referred to as “interruptive marketing”. Companies do this via the use of television, print ads, direct mailers, radio and more. This is how traditional advertising worked, but unfortunately, such methods are not only interruptive and poorly timed, they can be quite expensive. If you are a small business owner, then you could be paying an arm and a leg for one of these forms of advertising without any promise of success. However, larger companies that can afford such marketing will benefit, as this strategy can help to bring awareness about one’s product and services to a national audience.

Inbound Marketing
Inbound marketing is a more affordable marketing strategy, which is a reason why so many small business owners make use of it. The idea of inbound marketing is that you target a core audience by providing useful and quality content to entice them into finding out more about your products or services. So, in essence, you give them something in order to get them to come to you.

This is an effective strategy for a number of reasons. First of all, you’ll be targeting consumers who are actually looking for products and services that you provide, instead of trying to advertise to every consumer out there, no matter what their needs are. There are several ways to conduct a successful inbound marketing strategy, all of which require an online presence.

Creating Content – Using social networks such as Facebook, Twitter and LinkedIn, you can post helpful articles and videos that are related to your products or services. This content should not be advertising your company, but instead it should be providing useful content to consumers. Create original content using SEO (search engine optimization) and post it to your social network pages. Not only are you enticing consumers to stick with you, you are giving them the chance to share your content, which will eventually lead back to your webpage.
Offering Incentives – Give followers incentives for following you, such as by providing free eBooks or special deals on your products or services. One strategy is to create a landing page that you link to using your social network pages. On this landing page, you can offer consumers free goods or content in exchange for signing up to your newsletter.
Communication – Unlike outbound marketing, inbound marketing allows you to have direct communication with the consumer. Using your social media presence, you can ask your followers for their input regarding your products and services. This shows them that you care for your customers, and gives you the chance to improve your business.
Deciding between outbound vs inbound marketing will depend a lot on the resources of your company. All companies, no matter how big or small, should use inbound marketing techniques. However, companies with larger resources shouldn’t ignore the benefits of reaching a wider audience using outbound marketing. If you still need some advice on what the best tactics are for your company, give us a call! We’d love to help you with your options. For further information, be sure to check out our previous post that included our inbound marketing infographic.