AdWords Customer Match lets you target customers based on an initial list of e-mail addresses. Upload your list and you do things like serving different ads or bidding a different amount based on a shopper’s lifecycle stage. Serve one ad to an existing customer. Serve another to a subscriber. And so on. Facebook offers a similar tool, but AdWords was the first appearance of e-mail-driven customer matching in pay per click search.
This has demonstrated that, by poor linking, it is quite easy to waste PageRank and by good linking, we can achieve a site’s full potential. But we don’t particularly want all the site’s pages to have an equal share. We want one or more pages to have a larger share at the expense of others. The kinds of pages that we might want to have the larger shares are the index page, hub pages and pages that are optimized for certain search terms. We have only 3 pages, so we’ll channel the PageRank to the index page – page A. It will serve to show the idea of channeling.
There are two primary models for determining pay-per-click: flat-rate and bid-based. In both cases, the advertiser must consider the potential value of a click from a given source. This value is based on the type of individual the advertiser is expecting to receive as a visitor to his or her website, and what the advertiser can gain from that visit, usually revenue, both in the short term as well as in the long term. As with other forms of advertising targeting is key, and factors that often play into PPC campaigns include the target's interest (often defined by a search term they have entered into a search engine, or the content of a page that they are browsing), intent (e.g., to purchase or not), location (for geo targeting), and the day and time that they are browsing.

But PPC advertising can run up costs extremely quickly. It’s easy to get caught up in a bidding war over a particular keyword and end up spending far more than your potential return. ‘Ego-based’ bidding, where a CEO/marketer/someone else decides they Must Be Number One no matter what, can cost thousands upon thousands of dollars. Also, bid inflation consistently raises the per-click cost for highly-searched phrases.


So, the good news is that there are powerful reasons for creating a digital strategy and transforming your marketing which you can use to persuade your colleagues and clients. There is also now a lot of experience from how other businesses have successfully integrated digital marketing into their activities as explained in the example digital plans, templates and best practices in our digital marketing strategy toolkit.
Size: (green) The size of the text portion of the web page. It is omitted for sites not yet indexed. In the screen shot, “5k” means that the text portion of the web page is 5 kilobytes. One kilobyte is 1,024 (210) bytes. One byte typically holds one character. In general, the average size of a word is six characters. So each 1k of text is about 170 words. A page containing 5K characters thus is about 850 words long.
Search engine optimization (SEO) is often about making small modifications to parts of your website. When viewed individually, these changes might seem like incremental improvements, but when combined with other optimizations, they could have a noticeable impact on your site's user experience and performance in organic search results. You're likely already familiar with many of the topics in this guide, because they're essential ingredients for any web page, but you may not be making the most out of them.
Webmasters and content providers began optimizing websites for search engines in the mid-1990s, as the first search engines were cataloging the early Web. Initially, all webmasters needed only to submit the address of a page, or URL, to the various engines which would send a "spider" to "crawl" that page, extract links to other pages from it, and return information found on the page to be indexed.[5] The process involves a search engine spider downloading a page and storing it on the search engine's own server. A second program, known as an indexer, extracts information about the page, such as the words it contains, where they are located, and any weight for specific words, as well as all links the page contains. All of this information is then placed into a scheduler for crawling at a later date.
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