Write Great Articles

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Write Great Articles

How well is your article marketing campaign going?

Recently, I decided to see how much of what I wrote online – to support my marketing efforts – was read and / or syndicated on other websites. Basically, if I find evidence that my work has been syndicated elsewhere, I think that is a more reliable indication of how good I am than seeing how many times each of my articles has been viewed. In my opinion, the number of views recorded per article (“number of views”) probably indicates the effectiveness of the article title, more than the actual impression each visitor had of the content of the entire article. In other words, I think it’s possible that some articles are “viewed” more often than others, NOT because their content is more useful, but because their titles are better crafted than others that have the same “age” as theirs.

I always try to imagine what the one who has posted my articles on his website thought. For the most part, I expect that he / she actually took the time to read each one, to the point that it would be useful for him / her to syndicate content to attract visitors = “traffic.” I also prefer syndicating my articles because I know that a person can click on an article that looks interesting (increasing the number of views) to read the full description, and only to exit (click) -away ) after reading one or two paragraphs, because he / she realized that it did not seem to offer the information that he / she expected. In this case, the number of views for the article would have increased, but little was achieved in terms of the qualitative advertising impact for the author.

Take a different perspective. The number of views for a relatively new article compared to an older or earlier published tends not to give an accurate picture of how each article behaves in relation to the other. Consider this example. An article published 100 days ago and reviewed that afternoon was displayed 100 times, while an article published 30 days ago has been viewed 90 times at the same time. If you look at the “number of views”, without considering how long each article was available for the ad, you would get the impression that the former performs better, ie. H. More reader interest than the latter. A closer look at these numbers shows that exactly the opposite is the case! (See below explanation why this is so).

Why an article with a lower “number of views” does better

You must be able to rate all your articles based on the same standard or benchmark. All articles have in common that they have a release date. Another reason is the fact that at any time the AGE can be accurately determined after publication of an article by calculating the difference between the first publication date and the current date.

It’s a pretty simple logic – but it’s not immediately obvious. Instead of using the recorded “total views”, could we get additional information by, for example, measuring the total views per number of days (or weeks? Months?) Since the article was published. The result would be a value – an index – measured in views per day (or week? Month?). In the example presented in the previous section, dividing the “number of views” for each article by its “age” (ie days after publication) shows that the “younger” article has indeed aroused more reader interest – at 3 views a day – since Appear as the “older” – which scored an average of 1 view per day. Very often, deriving a weighted average index based on an absolute measure such as “total views” provides a more representative and useful / reliable indication of performance.

Based on the above information, you can see why I say no. “Views” of an article, however useful it may be, can sometimes be insufficient to accurately gauge the readers’ true interest in your articles (or the value they place on them), and measure the performance of most article directories It seems that only a handful of visitors who click on articles to read them will ever take the time to “rate” one of them with the simple assessment tool provided at the end of each article. This may indicate this that they prefer to download articles that they click to view offline, or that they are often in too much of a hurry to spend the few seconds to give this feedback. and make more sense of the “No.” Of Views “recorded for my articles, which I’ve developed for RII (TM) table analysis.

Set up a table to calculate the Article Readers’ Interest Index (RII) (TM)

For my purposes, I have created a custom automated spreadsheet application that calculates a weighted average or Cumulative Views Per Day (CVPD) value called the Readers’ Interest Index (RII) (TM) for EVERY article I’ve published. The RII (TM) analysis helps to measure more accurately how well individual articles perform in terms of “getting” the reader’s interest.

The following steps will allow you to create a simple table to derive the RII (TM) for your individual articles. Note that the format used for the data below is month / day / year (ie MM / DD / YY).

1. Open a blank table on your PC.

on. In cell A1, enter the field / column heading “Date of publication”.

b. In cell B1, enter “Views download date” (ie The date on which the “number of views” recorded on the website for the item was checked).

c. Then enter the heading “Days Post Publication” (DPP) in cell C1.

d. In cell D1, enter “Total Views”

e. AND Enter the heading “Article RII” in cell E1.

2. Enter the data for the RII (TM) calculation of the selected article as follows:

on. In cell A2, enter the actual release date for the item to review, for example: 15.03.06, that is March 15th, 2006

b. In cell B2, enter the date (July 9, 2006, ie, 07/09/06) where the actual “total views” value (for example, 120) that you want to use for your calculation is was downloaded. This is important because during a two-day download and using today’s date in the “Download Date for Views” column, MORE views may have been recorded since the last download and you could stop the RII (TM) value. Up Computing May Be Wrong , Therefore, it is usually better to use the date on which you downloaded the Total Views value for the articles.

c. In cell C2, enter a formula “= b2-a2,” which basically means subtracting the earlier date in cell A2 from the younger date into cell B2 to get the approximate number of days since the release of the Article have passed. In our example, this is about 116 days.

d. In cell D2, enter the value “total number of views” (we use “120 views” as stated above), which you will use on the date you entered as the “download date for calls” for the calculation of the web page for have downloaded this article

e. In cell E1, enter the formula “= d2 / c2”, which gives the total views for this article at the time of download by the number of days (that have passed) after the article was published.

The formula you receive should be about 1.03 cumulative views per day (CVPD) – and that value is what I call the item’s Readers’ Interest Index (RII) (TM).

The above index, in my opinion, provides a more reliable basis for measuring performance, especially in terms of the tests I’ve done so far, because over time you could see exactly how each article behaves for itself. After you have done these calculations for your articles, or even better, by doing them for other articles published by other authors (for example, in your writing area), you can actually derive some kind of general objective index to which you want to aim.

If you subsequently notice an article that meets or exceeds this target index value or threshold, you may want to focus on writing more qualitative articles on a similar topic / area, as visitors are likely to do so interested in reading them. And for items that you find they are not reaching the cut-off mark, this may indicate that you need to improve the spelling of your titles / content in a particular topic, or it may be a sign that you should not write on the subject at all! 🙂

This solution is very adaptive, so you can not lose it when you take it over

Although I’ve created the specific solution described in this article based on my work at EzineArticles.com, I can easily customize the Excel VB application I’m currently using to accommodate future changes that can occur at EzineArticles.com. or to get them to work with other article marketing sites / directories as needed. You would only need to make minor changes to relevant parts of the formulas – and possibly rebuild the custom data entry interfaces for workbook automation.

You can also develop a similar solution using the spreadsheet application installed on your PC. If necessary, ask a spreadsheet developer to automate them to save time and effort on use.

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