RCounter
© 2001 Bendersky Maxim
© 2001 Rusin Alexander

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Alexander Rusin
(amfora@lvs.ru)

The analysis of site audience

(using the data collected with the help of RCounter v1.0)

OR

17 useful conclusions, which will help you to:

evaluate efficiency of your site promotion (as well as your site general efficiency),
plan further promotion steps,

evaluate quality of your site structure, point out its defects,
optimize your site structure,
and give you lots of other simply curious information…

First issue

September 18, 2001

Let’s begin this article with some questions, which we address to people who believe, that the number of site hits is only one thing, which is necessary to know about site audience:

  • Having registered in the catalogs and search systems, are you sure that the registration has passed successfully?
  • If you used the program, which “registers a site in 1000 catalogs worldwide” – are you sure, that if only from such 100 catalogs somebody has gone to you?
  • Having conducted a presentation, delivery or simply having invited friends on your site, do you clear understand effectiveness of this action?
  • Are you sure the pages, which you diligently update, are visited?
  • Are you completely sure in correctness of your site structure? Or the visitors do not go further than the main page?
  • Who is your visitor?
  • In what days does your site have influx of visitors and in what days does not? Are you sure, that in the next time, when you will send your delivery, you will not fall into “dead day”, when practically everyone will ignore your letter, being busy with own problems?
  • After all, do you strongly believe, that this list of similar questions is completely definitive?

 

Contents

1. INTRODUCTION
2. BASIC PARAMETERS OF SITE ATTENDANCE
    Conclusion 1. About how many pages of your site are viewed by the average visitor and as far as it’s good for you
    Conclusion 2. About affection degree, constancy of your site audience
    Conclusion 3. From which it becomes clear, how good your site “has sprouted up” on the Net
    Conclusion 4. Describing “correctness” of your site main page
    Conclusion 5. In which we analyze the actions of your site audience and demonstrate how to evaluate reasons of growth or falling in your site attendance
    Conclusion 6. Assisting to understand, as far as justifies itself your site
3. ANALYSIS OF "REFERRALS"
    Conclusion 7. About what part of your total site audience is the “devoted” one which probably being potential business partners if you have a corporate site
    Conclusion 8. About “finding” your site in search systems
    Conclusion 9. About what effect the registration in the catalogs has given to your site
4. ANALYSIS OF SEPARATE PAGES' ATTENDANCE
    Conclusion 10. Devoted to site pages with abnormal low or high attendance
    Conclusion 11. Assisting to evaluate quality of “key” pages
    Conclusion 12. Sometimes permitting to detect idle (corrupt) links on your site
5. ANALYSIS OF THE CALENDAR STATISTICS
    Conclusion 13. About efficiency of site promotion actions and on what days it is better refrain from such action
    Conclusion 14. In which you will see the qualitative analysis of your site attendance surge as well as evaluation of conducted action
    Conclusion 15. Again devoted to the dynamics of site audience changin
    Conclusion 16. Which from time to time gives simply surprising results, essentially supplementing performances about audience interests of your site as well as about audience actions
    Conclusion 17. Permitting to evaluate all way of visitors inside your site
    Some other conclusions from the calendar statistics.
6. FINAL CONCLUSION
7. OTHER USEFUL DOCUMENTATION, INTERNET-RESOURCES, ADDRESSES

 

1. Introduction

The analysis of site audience and furthermore – making some conclusions on the basis of which is supposed to improve site attendance - rather nontrivial problem. Sometimes even a set of parameters of your site can not give you clear picture of site attendance and sometimes - on the contrary - everything becomes understandable from “several digits”.

In this document I will share my own experience and my colleagues’ one with you about how to make analysis of site audience using RCounter product (www.rcounter.noonet.ru). In the present moment this experience is based to the analysis more than ten sites with the usage of RCounter product (during 4-6 months), and about the same number of sites until as we have developed this product.

I clear understand that many internet-analysts, to whom probably you concern as well, have bigger experience, however I pay your attention: the main purpose of the document is to share the methods of researches with reference to RCounter product with you (although this document may be useful for users of other statistic systems). Accordingly, you will find methods of rating (analysis) of site audience mainly on the basis of the data collected with the help of RCounter in this document. Some parameters of site audience, which temporarily are absent in the RCounter reports, will not be considered in the given version of the document. But, undoubtedly, they will be considered in the future editions, which I will issue a little later, after appearance of the new version of RCounter product (it will be later, because me and my colleagues need enough time to work over and check “new analysis technique”.

And the last one, what is necessary to notice before the beginning of this informative story – what the site audience was chosen as an example to give you counsels and recommendations. I have selected the web site of NooNet Internet-studio (www.noonet.ru) for this purpose. Why have I choose exactly this site? Not just because the audience of this site “is more correct” than other sites have. And promotion/advertising of this site in any way cannot be named model (exemplary-exponential). Simply, this site from the moment of its creation has been analyzed with the help of RCounter and its site audience and structure are good enough for making understandable examples on their base. Just look at this site as an qualitative teaching and methodical manual, not ideal but exponential one.


2. Basic parameters of site attendance

In the beginning of this paragraph I’ll determine some “elementary” parameters:

  • Number of hits (showings of site pages);
  • Number of hosts (visits);
  • Number of unique visitors (IP-addresses);
  • Number of showings of the site main page;
  • Number of addresses-referrals (the length of “referrer list”);

and some “more complex” parameters:

  • Average number of “hits per day ”;
  • Hosts per day;
  • IP-addresses per day.

I have named them as elementary parameters, because “RCounter” simply shows appropriate numbers on one of the accounting pages and they do not need to be calculated – just see them and everything will be understandable. The version 1.0 does not show the more complex parameters “obviously” and they need to be calculated on the basis of other parameters.

The majority of the elementary parameters is visible on the main page of RCounter:


Small preface about the basic parameters

It is not a secret that the more visitors the better for this site owner. However, for sites of the different type, size, regularity of updates (as well as different quality) – different parameters will be good. For one sites - 1000 hits per day is naturally, but for others it is almost inaccessible level.

Therefore, we can not say, for example, 5000 hits per day is good and 1000 hits per day is bad generally.

However we can make rather interesting and universal conclusions on the basis of RCounter basic parameters.


Conclusion 1. About how many pages of your site are viewed by the average visitor and as far as it’s good for you

Let’s compare such parameters as “number of hits” and “number of hosts”. It will be even better if we will divide the first parameter into the second one. The more result, the better for you. In my case (with NooNet’s site) – the result is 1021/309 = 3.3. It means, that the average visitor views more than three pages of this site. Certainly, this result depends on subjects of a site, number of pages. If your site has only 3 pages – it’s not possible to get this result, and if your site has 100 pages, the given result is most likely bad than good. However, in my case the size of my site is 6 pages, therefore, this result is quite enough (because the average visitor views more than half of site pages).

General rule: this parameter should be not less than 2.2-2.5 for the majority of sites. For some sites - even “3.3” will be bad result.

Be careful with conclusions: this parameter is strongly depends on subjects and size of your site.


Conclusion 2. About affection degree, constancy of your site audience

We compare such parameters as “number of hosts” and “number of IP-addresses”. Again it is not bad to divide one into another. And, again – the more result, the better for you. For my case it is 309/172 = 1.8. It means, that on the average same person came on my site twice for its existence history, besides - not successively, but with the large interval (in different days). In other words – he/she came back to my site. The more percent of returns on your site, the better, because it shows “affection degree” of audience to your site. And such parameter is always lowest on resources, to which the visitors get “casually” (via search engine or banner exchange system).

It is necessary to make reservation that “number of IP-addresses” inaccuracy shows real number of different people coming on your site. Under an one address the different people (for example from one company with proxy) could come, and on the contrary - the same person could come under different addresses (from different computers or with dial-up connection). But, on the whole, such parameter as “number of IP-addresses” can be used in the audience analysis. It will not be a big mistake.

General rule: the given parameter is not bad if it is more, than 1.4 and it is very good at values more, than 1.8. If for your site this parameter is “2” and more - it means, that your site has “especially devoted” audience, that meets rather seldom.

Be careful with conclusions: do not try to analyze this parameter when your site is too young (less than 3 months). At the early stage of site existence it is impossible to say, that its audience is devoted or chance – your site audience has not formed yet.

Not recommended conclusion: After reading conclusions ¹1 and ¹2 you may desire to receive the relation of number of hits to number of IP-addresses. In other words, to find out how many shows one unique visitor has seen on average. I would not recommend considering such parameter and making any conclusions with its help. It is not only difficult, but also is very inaccuracy. You see it is not known from this parameter, when the same visitor “stroll” about your site, and when, with big breaks, came back to the same page. Therefore it is easier to make an incorrect conclusion, than receive any really curious appraisal.

If you disagree with me and see good practical usage for this parameter – I’ll familiarize with your interpretation of this parameter with great pleasure (send your letters to amfora@lvs.ru).


Conclusion 3. From which it becomes clear, how good your site “has sprouted up” on the Net

Let's look at number of addresses-referrals (URL count in Referrer list). This parameter does not need to be divided into anything, simply take away 2 addresses (because two addresses are always your site and “unknown” in this list) from it and estimate obtained result. For me - 19-2 = 17. As a rule, this parameter depends on intensity and breadth of advertising/promotion of your site as well as its lifetime

General rule: Less than 50 referrals for a site living 3 months or longer and past registration in the catalogs/search engines is not enough. By the way, my example - NooNet is a Russian web-site, so it is not lawful to use these criterions for this site. More than 100 referrals is good even for a site “in its heyday” (for one year or older sites). And if you have more than 200 referrals – it is simply excellent parameter. May be you have achieved it not in the usual manner.

Be careful with conclusions: Pay attention that number of referrals has different value for sites of different age, with different intensity of promotion etc. But greater importance is what geographical specialization of your site - international or regional.


Conclusion 4. Describing “correctness” of your site main page

Firstly, count how many percents from total shows (hits) the main page shows makes. In my case (352 / 1021) 100 = 34 %. This number obviously shows what percent of your visitors past further than the main page. Than less this number, the better. When this number is great enough - always it is necessary to think about it: may be something wrong in your site structure or in presentation/registration of the main page?

On the first sight, this parameter is similar to percent of hosts from total hits (If we suppose that a visitor browses through your site - that necessarily one hit belongs to the main page, and others – to the second pages of your site). But such assumption is very inaccurately, because often visitors can load (update) the main page some times or periodically to come back during their browsing through your site. And, on the contrary, a visitor can get on your site and browses through it not enter into the main page. Thus, the percent of the main page shows from total hits is an independent valuable parameter.

General rule: If “the percent of main page” is more than 45 % - it almost always shows that a site has problems. This “percent” should be 30-35 % and less for the majority of sites. If this value is less than 25 % - it is already very good.

Be careful with conclusions: the value of this parameter strongly depends on both the subjects/size of your site and the type of your main page. There are main pages, which have a lot of information (on which a visitor frequently receives everything what he/she wants and goes away) and few-informative ones (which are only “for meeting” a visitor). In the first case “the percent of main page” may be big enough, in the second case – it must be rather small.


Conclusion 5. In which we analyze the actions of your site audience and demonstrate how to evaluate reasons of growth or falling in your site attendance

Firstly, calculate the average number of “hits per day” and “hosts per day”. Compare these parameters with the current daytime attendance of your site (using parameters of one day only is very inaccurately, therefore, you can take the average level of attendance under the “totals” of current or previous month for “current attendance”, see the calendar statistics).

The conclusions by results of such comparison can be made more interesting than it seems on the first sight.

If the “current” number of hits/hosts per day is more than “average for site existence”, besides they have grown approximately proportionally - then the conclusion is simple - the audience of your site grows. If these are proportionally less – your audience reduced. But if there is disproportion (for example, the level of hits grows but the level of hosts does not) it is necessary to make more complex analyses with this information. When the growth of hits overtakes the growth of hosts – we can say that your site audience approximately stays on the same level, but your visitors go to your site with bigger enthusiasm; in the case when the growth of hits are behind – your audience grows, but most likely the real reason of this is some special methods of promotion and the majority of new visitors has low interest to your site. If you see some drop of hits/hosts – it means that the disproportion also has some special feature: when hits fall faster – it means that interest to your site is lost (for example, all information has already read, so visitors simply check your site for some news or upgrades); when hosts fall faster than hits do – it frequently means that one of strong promotion ways which gave you lots of new visitors is getting ineffective but old and devoted part of your audience remains and it creates comparatively high level of hits.

The most ambiguous parameter is growth of hosts at falling hits or there is reverse situation. It’s most likely temporary status meaning intensive changes in your audience, which definitely should be replaced with general growth (both hits and hosts) or (alas!) general falling.

General rule: Practically we cannot say that for example “so-and-so level of hits/hosts growth” is normal but “so-and-so one” is too small. It depends on how active you advertise (promote) your site. For a site with no updating/promotion even “zero balance” is a good parameter. On the contrary, for an actively promoted site - the monthly audience growth in 10 % most likely is a negative result. However, from my experience I can say that the monthly growth of hits/hosts should be 2-3% for a typical “live” site with stable audience anyway. It happens due to: a) general Internet growth; b) dying of competing sites. “Zero balance” speaks most likely about neglect than stability of your site. Though, it’s only my observations of some cases and I do not want to say that it works definitely in all cases and situations.

Be careful with conclusions: When you evaluate the level of hits/hosts growth or fall always remember that this parameter has a significance only against a background of that advertising (marketing) campaign, which you conduct on the Net as well as against a background of campaigns of competing sites. Because it may be that everything is O’K with your site but your competitor began very actively “to gather” additional audience, well … in any sense this situation can be considered as a negative parameter, which shows your gap from this rival. And don’t forget that there are seasonal fluctuations in the Net attendance as a whole and your site personally, for example, corporate sites, as a rule, are visited a little in summer as well as entertaining ones during student session.

Be careful with young and small! Do not try seriously to make ratings of growth or fall for hit/host level for young sites, which did not have constant audience yet. If your site lives less than 3 months – all conclusions most likely will be very doubtful - less 6 month age is also questionable. This method of analysis works well for sites living more half a year or greater. But it is not the last limitation! Also, pay attention when you use the described method for sites with low level of attendance. Just remember that 10, 15, 20 are not statistical parameters. For qualitative statistics - it is good to have not less than 100 hits and 30 hosts per day then the analysis will have real sense. By the way, because of low level of attendance I did not begin to describe this method using NooNet site. If I exampled on my “5-6 hosts and 10-20 hits” - any skilled analyst completely fairly would say that I am not right, gently speaking.


Conclusion 6. Assisting to understand, as far as justifies itself your site

Firstly, calculate the average number of unique IP-addresses per day. In my case it is 175/101 = 1.7. This parameter should be considered as: daily 1.7 new visitors on average find out your site – someone simply learns and goes away, others see your site in detail. If you have a corporate site – just image – that new potential clients visit your office. If you have a site of other type - conduct any suitable analogies. This parameter should force you to think about your site profitability and necessary to strengthen its advertising/promotion.

General rule: For a good corporate site, which has not intensively promotion on the Net, about 20 new unique visitors per day can be considered normal. But it also depends on site subject (company specialization). For informational, entertaining sites it is difficult to give universal ratings (for one it’s good to have 50, for others even 200 is not enough).

Be careful with conclusions: First of all, look at this parameter extremely against a background of expenses on your site development/tech.support/promotion. For a site, which “lives without big expenses” sometimes 10 ip/days can be considered as an acceptable level. But for a serious Internet-project, which constantly needs separate employee and some finance for promotion, 100 ip/days cannot be considered as a satisfactory parameter.


3. Analysis of “referrals”"

I think it is necessary to devote the separate chapter to analysis of the "where from" statistics or - “referrals”. “RCounter” shows this kind of statistics on the separate report page. It looks in the following way:

One conclusion, which can be received, looking at the number of addresses in this list, was already described above (see conclusion ¹3). However, we can receive more interesting conclusions from the "where from" statistics.

But, firstly, I should say about:

Problem of frames in the statistics of referrals. If your site is built with the help of the frame technology, the statistics of referrals will be very inaccurate and may be incorrect at all.

It occurs for the following reasons - when a visitor comes on a usual site (without any frames), at the first transition the address of the site from where he/she came is taken into account as a referral. When the visitor “wanders” inside the site – the site address is taken into account as a referral. Thus, all addresses of referrals, distinct from site addresses, are addresses of other resources from which the transition is carried out to your site. But when a site is built with the help of frames every time “primary source site” address is taken into account as a referral at the first transition and during "wander" inside a site quality referral is set off. But it is not correct.

I'll explain it using an example: If I have found a site "X" with the help of “AltaVista” search system, passed on it and thumbed through 4 pages of this site, then if the site is built without frames – 1 transition with “AltaVista” and 3 transitions with “X” will be registered (total – 4). It is correct. If the site is built with frames - then all 4 transitions with “AltaVista” will be registered - that is completely incorrect.

“Frames” is another reason why I have taken “NooNet” site as an example for our analysis. It is built without frames and consequently its statistics of referrals is good enough and correct. Let's see it.


Conclusion 7. About what part of your total site audience is the “devoted” one which probably being potential business partners if you have a corporate site

First of all count, how many percents from all transitions the transitions in the “unknown” line make. In my case it is (276/381)100 = 72 % (381 is the sum of all lines except for the first, because the transitions with “NOONET.RU” are transitions inside the site. They are not interesting to us). The higher obtained percent - the better for you. You see that the “unknown” transitions generally are references to the site either with the help of the link from a letter/document or directly inputting the site name in the address bar of a browser. But, in any case - the visitors who have come on your site “from nowhere” usually are very loyal members of your audience, who come on your site not by chance and probably it is not for the first time. So, the main thing for corporate sites is that high percent of “unknown” means high percent of business partners (even potential), whom your web-site attracts.

I say honestly that “unknown-visitors” are sometimes registered and by virtue of technical reasons (when it is impossible to determine the referral address) but it is not so often case and we can consider this factor as slight error of gathered statistics.

General rule: It is good to have this parameter greater than 50% for any site. However, really good result is 70-75 % and above. If this parameter is 40 % and less - your site is visited mainly thanks to good links from catalogs, good place in search systems, banner exchange systems and so on.

Be careful with conclusions: Above I said that “unknown” sometimes can be take into account from “technical reasons”. Again I say honestly – the nature of these reasons is comparatively difficult and I am not sure that it absolutely always is a “non-significant” factor. Be careful - if the “unknown” level is improbably high on your site – it is good to clear up reasons of it, for example, by practical way (independently coming on your site from “anywhere” and from search systems look at correctness of your statistics), or with the help of scientific methods (ask experts about it).


Conclusion 8. About “finding” your site in search systems

At first, count how many percents from all transitions the transitions in lines with the names of leading search systems (AltaVista, Google, HotBot) make. In my case the considerable results are gotten only from AltaVista system: (22/381) 100 = 5.8 %. If your site has considerable percent of transitions from either one or another search system – it means that your site is “well prepared” for that search system robots. If this percent is insignificant or there are no transitions at all – your site is badly prepared for the given search system.

Please, pay attention that this conclusion shows only the level of “finding” for your site in search systems. If you are interested in good efficiency from Google/AltaVista/HotBot or other search systems – this parameter is of great value for analyses of your statistics as well as it will allow you to optimize your site for search robots better. But not always site “finding” in search systems is really valuable characteristic. In my case this described parameter will have only informative meaning.

By the way, the case when the site “is searched” well in one search system (for example, AltaVista) and bad in other one is not rare and not surprising. The fact is that the various search robots process search and ranking of sites, being based on different criteria (one - on contents of page, others - on keywords, header or use a combination from those and other parameters of a site). Therefore good “finding” in AltaVista and the absence of such result in Google show that part of a site, on which Google is oriented, is not worked.

General rule: For sites of different subjects “normal percent of search system” also will be various. In any case, less than 1 % of transitions is an unsatisfactory result. More than 6-8 % is good anyway (Here I mean a percent of each search system, not their sum!). However there are cases when more than 15 % of transitions on your site is given by any search system, moreover, there are sites, which in general “gather” their audience mainly with the help of search systems. For such sites, certainly, this percent should be 15-25 %.

It is necessary also to notice that, as a rule, AltaVista gives more visitors than some other system – only therefore that AltaVista is more popular and often used system. So, do not wait that a percent of transitions from all systems will be equal. However, sometimes it happens that by virtue of specificity (or subject) the site is visited from Google or HotBot more often.

Be careful with conclusions: For young sites the absence of any result from either one or another search system can mean that the robot of this system simply had not time to check up and index your site. As a rule, the period of search and indexation of new sites for search systems is about one month.


Conclusion 9. About what effect the registration in the catalogs has given to your site

Firstly, determine for yourself the list of Internet-catalogs (key sites etc.), which you wish to see as large sources of your visitors. Probably, you sent the applications for site registration to administrators of all these resources. Now, check up from what resources the visitors came and from what ones do not. Count the percent of calls for resources from which the visitors have already came as it was made with search systems.

The conclusions concerning successes of registration in the catalogs (key resources) are made similarly to “finding” rating in search systems. But the conclusions will be a little bit different. If for a search system is mainly important qualitative construction of keywords and text of page header, for the catalogs it is important qualitative description of your resource and placing the link on it in a “correct” rubric.

If you see very small percent of calls from any catalogs - it is possible to assume that the link to your site stands not in “correct” rubric, on an improper place or the description of your site has appeared unsuccessful and it does not convince a visitor to go on your page. If you see no visits from a catalog, probably, the link to your site was not added at all. The reason can be an incorrect filling of catalog registration form or moderator’s decision (a manager of the catalog) about lack of correspondence of your site. Anyway, you should think about the correctness of your site registration again, most likely, you have to repeat the procedure of registration in the catalog (make a re-registration).

Pay attention! Be careful when you consider that this catalog gives you “enough” or “few” visitors. Do not forget that various catalogs themselves have very different attendance. So, it not surprise when, for instance, such large catalog as “Yahoo” can give you more visitors than “AltaVista”, but any modest narrow-thematic catalog simply can not do it. Nevertheless the visitors coming from that narrow-thematic catalog, probably, are more valuable for you than visitors from “AltaVista” or “Yahoo”.

By the way, it is very important for attraction more visitors with the help of a catalog to have a good place of the link to your site and its decoration. Some catalogs have paid services for placing links on an attractive place (for example, in the beginning of the list, outside of an alphabetic sequence) or some service in highlight of the links by the font/color/frame. Probably, it would be better for you to "experiment” with such service for a short time to evaluate how many additional visitors from this catalog you got using this service. After that you can decide for yourselves whether it is necessary to spend finance such “favorable presence in this catalog” or it does not justify itself (may be you can spend this financial resources on other kinds of promotion on the Net better).

General rule: relatively large Internet-catalogs (Yahoo and some others) – in some cases can give you more visitors than search systems - that is the percent of transitions from them can make 5-10 %, sometimes – even more. For specialized resources (including branch, corporate) large percent can be given by an advanced branch, regional catalogs (5-10 % and more) it occurs because, that it is often users look for specialized resources not in search systems but in thematic catalogs (for example, a resource about programming is very convenient to look for in the appropriate section of “Yahoo”, where necessary subsections are created and you can find qualitative descriptions instead of rummaging in the mammoth list of found documents, which "AltaVista" gave on the word “programming”).

Be careful with conclusions: Once again it is necessary to remind that low level of your visitors from either one or another catalog can be not only unsuccessful registration (unsuccessful description) but also simply low attendance of a catalog or (more often) - low attendance of a concrete rubric of either one or another catalog.

And do not forget that registration in a catalog is not necessarily made in the same day then you fill in the application. All the more, it is impossible to wait for new visitors from this catalog in the same day. However, catalogs give faster effect than search systems – you will get new visitors within 1-2 weeks after successful registration. If a catalog makes deliveries of news about the new added resources – in this case, you can have a big surge of attendance even within several days after registration.


4. Analysis of separate pages’ attendance

It has been already mentioned about the analysis of the main page's attendance before (conclusion ¹4). But the attendance level of other pages also can be very important for understanding how good your site (its structure and contents) satisfies visitors' expectations, what exactly is interesting for them on your site, and what pages are abandoned by visitors.

The RCounter program shows the attendance statistics of separate pages in the following way:

Now we are ready to make conclusions, which can be made, looking on this statistics.


Conclusion 10. Devoted to site pages with abnormal low or high attendance

When this list is sorted out by number of shows of pages, as in my example (the sorting mode is adjusted in the program) - the order how pages follow in the list corresponds to the level of their readership - though to be precise – perhaps not the level of readership but number of shows for all page history. Thus a very popular but young page can appear in the bottom of the list and poorly readable but old can appear above. However you, as an owner or editor of your site, certainly, know everything and, looking at the list, can easily evaluate whether there are no “anomalies” in it.

To my mind it is the most useful conclusion, which can be made looking at this statistics. I'll explain how I understand “anomalies” slightly more in detail. When a site page, which has a very modest role and which, probably formed without a special technology, appears too highly in this list with a big separation from others, more “important” pages - it is an anomaly. On the contrary, when a very important page, for which you (or your colleagues) spent a lot of time for its construction, design, checking and you hoped that its contents will reach many visitors, but it appears in the bottom of the list (or even in the middle but with the large backlog from “leaders”) - it is also an anomaly. There is another anomaly - for instance, when a press release, an announcement or simply a new publication, which you widely “advertise”, starts slowly instead of “big jump upward”. It begins, like a “simple” page, to creep in the list.

In my case, there is only one anomaly (I see it as an editor of this site) – it is very low “rating” of the page “Horizont”, where my article is located. I have spent a lot of time for article writing and expected that it will be rather interesting and useful to this site audience. It does not happen - and this fact gives me a cause to think about it.

What does the presence of anomalies for a creator (editor), owner of a site mean? The reasons of anomalies can be various. Below, I located the main ones:

  • A link to an “abnormal unpopular” page, its description (comment) is not clear for your visitors. It does not give correct information about its contents. I believe that this is the source of my anomaly.
  • A link to an "abnormal unpopular" page is located in an unsuccessful place or gets lost among other links (for example, at the image resolution 800x600 – it falls outside the screen etc.).
  • You know badly interests and passions of your audience. For example, if students visit your site - they actively will look for free resources and articles and such pages, as price-lists will be interested seldom by them. If your visitors - businessmen, they will be interested in business offers, prices, analytical articles, and only afterwards scientific publications.
  • An “abnormal readable page” is popular due to good, attractive description, successful keywords (which people often use in search systems). May be its description (keywords) is not correspond to contents. So, visitors go with the expectations of receiving something on this page but they definitely see another thing - and it is too poorly (despite of its high attendance).
  • Also a page may be “abnormal popular” because of special placing of its link. Do not forget that when a visitor has some difficulties to select interested page he/she does not leave from your site immediately – a visitor presses most likely the first link in the list or the most observable and so on.
  • When a new and “promoted” page (a press release or a special business offer) very languidly attracts visits – the reason, probably, is its misplace of the link to this page or simply inertness of potential visitors. For instance, if you have delivered a letter "please, get acquainted with the special offer, which is valid to the end of this month" to all partners – it stands to reasons that not everyone will look for this offer on your site. It would be a great idea if you put the link to this page directly in the letter as well as highlight the appropriate link on your site (font, color, frame and so).
  • Also “slackness” of a new and promoted page may be from your inexact insight of interests of your site audience. May be they do not interest “news” or “offer” at all.

But this list of possible reasons of “anomalies”, certainly, is partial as well as not so concrete. At detection of “anomalies” your experience, common sense, and, probably, consultation of the experts will be play the key role.

I would recommend to ask some people, who are not involved in your project at all, why this page attracts redundant interest or, on the contrary, is not popular to their mind. Often such kind of people can easily find defects of your site, which you don't see or miss accidentally.

General rule: Generally speaking, the above list was composed on the basis of my experience, but, as usual, I'll say some words in this rubric as well. Most often, owners and editors of sites are worrying about abnormal low parameters either one or another pages. In the overwhelming majority of cases the reason is bad structure of a site, unsuccessfully formulated links, unsuccessful location of links. Much less often (from my experience), but also you can meet - a mismatch of a page contents with needs of visitors, in other words – page creators simply inaccurate know the audience interests.

Be careful with conclusions: It is necessary again to remind you that total of page shows is displayed in this kind of statistics. Naturally, old pages will be above young ones, even if they are more popular. The current attendance of pages you can see in the section “calendar statistics”. In the future RCounter version it is planned, specially, to show their average popularity in the report about attendance of pages.


Conclusion 11. Assisting to evaluate quality of “key” pages

Now, special attention should be paid on attendance of the separate type of pages - “key” pages, from which there are links to other pages. The special attention should be given them for the reason that the popularity of pages to which they refer strongly depends on them. Unfortunately, in my example (NooNet) there are no such pages except the main. But for many sites such pages are pages with the list of articles/publications or they are production catalogs from which it is possible to get on pages of separate goods or something similar.

What special conclusions can be made, considering their attendance?

Firstly, the attendance of key pages should be high enough. As a rule, a site should have the best attendance on the main page, further - on all “key” ones, and only after that on separate informative pages. Though, there are exceptions in this rule. But if the attendance of a “key” page is lower than for some “simple” one – it is a good reason to think about it. You see, a “key” page is, conditionally speaking, a “crossroad” from which there is a set of roads and which should differ by rather high popularity. Moreover, sometimes, it is a good idea to register especially “key” pages in catalogs and make special decoration of it for search systems – they can have mammoth independent value.

Secondly, you should compare the “key” page attendance with the attendance of pages on which it leads. If the attendance of “wards” pages in the sum is too exceeds (thrice as large and more) the "key" page attendance that it almost means that “final” pages get visitors basically with the help of search systems, instead of the “key” page of your site. Sometimes it works. But, sometimes, it testifies that your “key” page is visited too little or there are unsuccessfully indicated and commented links to other pages on it – in this case, visitors simply leave your site without trying to clear up with your site contents.

By the way, the main page of your site can also be considered as a “key” page and you can apply all above judgements as well.

General rule: I should say that the conclusions, described above, are not invention at all and their advantage is quite real. I repeatedly meet cases, when “key” pages and even the main pages of sites badly distribute visitors on “sponsored” pages. Moreover, there are “key” pages, which even now do not work on the high-powered level on some sites, where I am an editor – but I am going to spend a lot of time, thinking about the reasons of it, experimenting, and optimizing structure of these sites. This, I advise you too.

Be careful with conclusions: do not forget, sometimes, it happens that some “final” page is visited more than the “key” page or even the main one. It happens when there is a very popular resource (an article, downloading file) on such page and there are a lot of users from catalogs and search systems who get directly to it. It is an exclusive case and it should be considered as exclusive one, do not try that the “key” page attendance, certainly, overlaps the attendance of this “star” page. There are also other cases, when the discourse logic, described in this conclusion, should be applied with the certain clauses. Follow by your common sense, analyze statistics, and make experiments!


Conclusion 12. Sometimes permitting to detect idle (corrupt) links on your site

This conclusion is rather simple, but sometimes extremely useful. Look at the date of last visit of pages. Even better – choose the mode which sorts the list of pages by date/time of their last visit from the RCounter program, then you'll see pages with the longest time without visits in the bottom of the list. Now, ask yourself: "Are there such pages, which nobody visited too long ago?". Such a long absence of visitors on a page can mean that its link “has broken”. May be you or your colleague casually have broken, editing the site, or deleted the link to this page. May be something else.

When you see such kind of pages - simply go on the site and check up their accessibility.

General rule: You may think that this conclusion practically never is useful. However for relatively short time of RCounter usage I have already found out twice such “dead” pages. Once – a link was casually corrupted by web-master, in other time - I noticed at once some “unvisited” pages and remembered that their links never placed on the site. Because, a long time ago, I was going to create a separate rubric for this purpose, but for my shame, I forgot.

Be careful with conclusions: Generally you can be careless with this conclusion. No problems, if you once again suspect “link breakage” and at checking it will appear that everything is OK - the page has simply low popularity. It would be another reason to think again - why popularity of a page is so low.


5. Analysis of the calendar statistics

The calendar statistics is the information about distribution of visits of all site and pages by days. I can say that it is almost the most informative and useful part of the RCounter reports. Probably, it should be considered in earlier chapters, but if you're reading the document here – it means that you are really seriously interested in the attendance analysis of your site. Well, forthcoming conclusions from the analysis of the calendar reports, about which I'll tell you, now, will be an excellent dessert to all aforesaid…

As usual, I give you an example of the RCounter statistical report:

again I return to conclusions:


Conclusion 13. About efficiency of site promotion actions and on what days it is better refrain from such action

Look at the lines “Total” and “Hosts”, selected in the report by a light-blue background. There is the information about all site attendance, by calendar days in them. First of all, we interest in surges and collapses in attendance. For my example – there are one strong surge (9th, 16 hosts/48 hits) and one obvious collapse (7th, no visits at all).

Surges practically are always concerned with some site promotion actions on the Net or promotion actions on the offline (presentations, exhibitions, conferences) and also - that someone, independently from you, could publish the information about your site (in a journal or Internet-review). Furthermore, for example, an Internet-catalog could independently find your resource and add it in the rubric “new Net resources” or mention about your site in deliveries.

When you note any surges, it is always necessary to ask yourself – what is the reason? And, on the contrary, making some advertising actions (on the Network or offline) - it is always necessary to look at whether the attendance surge is after several days and how big it is. Finding out natural surges (after your actions) it is necessary to evaluate how well such actions hereinafter; observing surges which are independent from you - it is necessary to understand their reason (if it is possible) and think about how you can initiate them in the future.

The separate subject is collapses in attendance. As a rule, they are called by week or seasonal attendance fluctuations, concerned with “outside the Net” activity of your visitors. For corporate sites - collapses are natural on weekends, for sites with abstracts - during student vacations and so on. But, it is necessary not only to predict collapses, followed by common sense, but also to see what occurs with attendance in the reality. If you see that there is an attendance collapse each Monday on your site, it probably means that the majority of your visitors comes at office and have a lot of businesses "outside the Net" on Monday. They simply do not have time and need to go to your site on Monday. The same is true about the analysis of “surges”. You can make especially practical conclusions (namely, about possibility and expediency of repeated initiation of such surges). The similar practical conclusions are possible for the analysis of collapses as well. More concretely, the analysis of collapses allows you to plan the promotion actions of your resource (advertising, presentations, deliveries) better. You can avoid making such actions during the periods of natural-low activity of your audience, when those visitors, who you expect, will poorly remark these actions.

General rule: the overwhelming majority of attendance surges can be detected easily. As a rule, they are concerned with promotion actions of your site collective or offline actions. Even simple listing and classification of these reasons/actions deserve separate articles and books devoted to promotion of resources on the Net. As to collapses in site attendance, as a rule, it is easy to select their reasons and almost always it is concerned with week or seasonal periods of visitor activity.

It is difficult to overestimate the real practical value of observation for attendance surges and collapses. These observations have a great value for correct planning, which allow you to intensify effect from these actions and, simultaneously, reduce the costs – simply refuse from small-efficient actions or reduce their size.

Be careful with conclusions: Analyzing surges and collapses in site attendance, sometimes, it is possible to make incorrect conclusions. Comparatively surges – it is can happen when some actions (offline presentation and delivery on the Net) are simultaneously used. And it is difficult to understand what action gives observable effect. Comparatively collapses – do not forget that they can be spontaneous, especially if your site attendance has a low level (less than 100 hits per day). Both in that case and the other one the insurance from errors should be the common sense, recommendations and advises of experts, and regular practical confirmation of your observations as well.


Conclusion 14. In which you will see the qualitative analysis of your site attendance surge as well as evaluation of conducted action

Let's finish the subject of analysis of attendance surges. The separate conclusion can be made not in the area of searching surges and analysis of their nature, but researching their characteristics. A surge is characterized: by number of hits/hosts, duration and schedule of fading (how intensive your site is visited in following days) and what pages have visit surge. The analysis of these parameters allows you to understand what visitor has gone on your site – the same, as earlier, or a little other one. This conclusion is the additional help in the evaluation of conducted action and in determination what effect you achieved and what you can get from this effect (increasing devoted audience or even new commercial partners; but they may be simply temporary visitors).

Now, I’ll give you an example. In my case - in the peak it is registered 48 hits and 16 hosts. In other words, the relation of hits/hosts is 3. It is approximately equal to similar parameter for all site pages. So, I can say that the degree of the interested audience, which has come on my site during this surge, is similar to common parameters. If hits were less – it means that less interested audience has come than usual site audience during the surge. If hits were more - more interested audience (so, the promotion action can be considered useful not only in a quantitative increase of audience, but also in qualitative one).

As to duration of surge - for me, it has a strong expressed view for one day, though, there were 3 days when attendance was hardly above the average level after this day. Here, it is impossible to make unambiguous conclusions, but there is an impression that it is also concerned with surge. So, the conducted action had an effect on the site attendance about 4 days. It is longer than the effect from usual “Spam deliveries”. It is approximately equal to the effect duration from one offline-presentation, but, obviously, it does not correspond to the effect received from some day exhibition. Besides, this surge does not correspond to the effect which can be achieved at registration in Internet-catalogs, as the surge is either more shortly (1-2 days, when registration passes in small-sized catalogs) or it is more mark (not 16 hosts, but at least 30, when there is a registration in large catalogs).

Making the analysis on what pages visitors came during surge, I find that as a whole “distribution by pages” is standard for my site audience, though, on the pages “Horizont” and “Addresses” the percent of visits was hardly above usual. Most likely the reason is that the site has been gotten new visitors. And many of these visitors browsed different pages for better understanding of the site.

General rule: Repeatedly having observed results of either one or other advertising measures and promotion of sites I strongly believe that considering the characteristics of surge, it is possible to understand a lots relatively the quality of new visitors, and consequently – relatively the efficiency of the conducted action both in quantitative and in qualitative aspect. Often you can see a peak for surges per the first day and then there is more or less sharp recession to the average level attendance. Sometimes it happens differently. Generally speaking, discourses about for what types of measures, what kind of attendance surges are typical – are a separate subject and, now, my experience in this area is not so great to enter any classification, find regularities and give "big" advises. Probably, I'll be able to supplement considerably this section or even create a separate document about this subject with the help of your remarks and comments.

Be careful with conclusions: the value of surge is an important parameter for the analysis of action effectiveness. As I also work with statistics here, so values should be at least statistical. Making conclusions relatively my 16 hosts, 48 hits, and 9 visitors of any page, I am not quite right. But, I tried to show a principle. Furthermore, when number of hits/hosts in the peak exceeds thrice as large the average site attendance level - it is already sufficient parameter for some conclusions. But, of cause, we should try to make serious conclusions on the basis of serious parameters - hundred hits/hosts, tens shows of different pages. Do not forget that you can try to make either one or other conclusions always, but not always they can be made with an adequate accuracy and have a high degree of reliability.


Conclusion 15. Again devoted to the dynamics of site audience changing

It is possible to receive good enough parameters of site attendance growth or falling from the calendar statistics. For this purpose, compare values in the cells Total/Average and Hosts/Average (the average number of hits and hosts per day, accordingly) with the appropriate indications for the last month. A one remark – this comparing can be made not earlier the fist decade of a month, because the statistics for some days may be very incorrect.

If the average number of hits/hosts has grown in comparison with the previous month – it means that the attendance grows and on the contrary. In my case – 12.39 hits/day and 4.17 hosts/day are fixed for the current month. For the previous month - 9.07 hits and 3.1 hosts per day. You can see that the attendance has grown well (approximately 1.36 times as many). Thus, the percentage ratio of hits/hosts remained approximately the same as for the last month. It means that the qualitative changes in the audience have not taken place only the simple quantitative have taken place.

See the conclusion ¹5 for detail information observing growth/falling of hits/hosts. But there is the comparison of the current number of hits/hosts with the average parameters for all site pages existence in the conclusion ¹5. It is possible to make a comparison of current month with previous or any other one (for instance, with the same month of the last year) with the help of the calendar statistics. Thus, it is possible to make considerably more complete performance about the site audience actions.

General rule: Just see the appropriate section of the conclusion ¹ 5.

Be careful with conclusions: It is necessary to warn against hasty conclusions about growth or reduction of site audience under the observation of the calendar statistics. If there is a comparison of current parameters with the average ones for all site existence in the conclusion ¹ 5, here – I use month parameters only. It can give incorrect result, when the last month had a period of natural recession of activity, and the current one has a period of natural growth (for example, the last month - August, and the current one - September). And, on the contrary, when the last month had a period of growth, and the current one has a period of recession – using this conclusion is not quite right, as the fall of hits/hosts level does not show that the site audience is reduced in this case.

I recommend using the discourses described in this conclusion, together with discourses of the conclusion ¹ 5. Together they will give clearer performance about the actions of your site audience.


Conclusion 16. Which from time to time gives simply surprising results, essentially supplementing performances about audience interests of your site as well as about audience actions

After you have evaluated growth or falling attendance of your site – it is time to use unique possibilities of the calendar statistics - to find out what pages people visit or on what pages visitors have stopped to visit.

For this purpose there is the column “Average”, indicating the average number of hits per day for each page. The same column is in the report for the last month. It allows you to compare these parameters for each page, so you can definitely give the answer to the delivered question.

In my case, the following parameters of pages are fixed: Addresses = 0.89, Development = 2.33, Horizont = 0.61, Info_n_News = 2.22, Main = 5.11, Participants = 1.22 for current month.

For the last month the similar parameters have values: 0.70, 2.03, 0.40, 1.07, 3.40, 1.43 (accordingly).

Now, it is necessary to compare these numbers, paying attention for the general parameter of site attendance growth/falling. I remind you that the general site attendance in comparison with the previous month has grown approximately 1.35 times as much. I think it is not a problem looking at the attendance growth of pages and understand that it is almost on all pages, but first of all – on the pages “Horizont” (an article), “Info_n_News” (some information and news) and “Main” (the main). For the article and the main page – the growth is 1.5 times as much (that is above the average level) and for the page with information and news - the growth is approximately 2 times as much (!). But also you can see that one of pages (“Participants”, participants of studio) - not only does not have growth but even the attendance falling is fixed.

About what does the obtained statistics speak? To make a conclusion - it is necessary to know what information is placed on a site pages. And seriously to think about the meaning of increase or falling of visitor interests to either one or other pages.

About my site: seriously having considered the obtained parameters, I have made the following conclusion: visitors who repeatedly visit the site form more and more percent of people. Thus, many of them visit just to find out news and new information about NooNet. On other pages there is located mainly seldom-updated information, which visitors do not want to re-read every time when they visit the site. As to significant growth of the article visits - most likely the overwhelming majority of visitors, who have ignored it for the first time being on the site, but they have decided to fill this blank in the following visits.

Conclusions, which allow you to make the described method of the analysis of the RCounter, are one of the most important. They allow simultaneously receiving the advanced performances both about interests of your audience and about its actions. But, pay attention that it requires very attentive analysis, in comparison with results obtained from conclusions ¹5, 15.

General rule: It is not always (not each month and not for each site), using the described method of judgements, to receive so correct and useful conclusions. But from time to time this technique gives very important results, confirming, or considerably correcting the usual performances about site audience, its interests, and actions. The experience shows that this conclusion gives more interesting results, when the general growth or the site attendance falling exceeds 30 %. And the more degree of growth/falling - the above probability that the analysis of attendance growth/falling for separate pages will give an interesting result.

Be careful with conclusions: In this rubric it is necessary again to say already many times said caution that the above the analysis reliability, the more “statistical” parameters. And one more caution – about the conclusion ¹15 - it is not necessary to use this analysis earlier 10-th of current month, because it has not enough time yet to get qualitative statistics for this time.


Conclusion 17. Permitting to evaluate all way of visitors inside your site

Probably, it is the most difficult and ambiguous conclusion, which can be made from the reports of RCounter (first version) - about all way of visitors inside your site (from what to what pages visitors go). Nevertheless all difficulties and polysemantic interpretations, this conclusion is of great value and it has a sense to tell about it below.

To find out from what pages to what ones and how often transitions happen – first of all it is necessary to know very well your site structure and secondly, attentively, look on calendar statistics (better for some months).

The principle of this conclusion - if it is known that there are links to pages “B”, “C”, “D” only on the page “A” then, observing the following distribution of hits: A = 10, B = 1, C = 1, D = 4, it is possible to make the conclusion: each tenth visitor goes from “A” to “B”, similarly from “A” to “C” and from “A” to “D” – here almost each second visitor goes. So, it means that the link to the page “D” has the greatest popularity. On the other hand, almost each second visitor from the page “A” does not go anywhere – simply he/she leaves the site.

But, I say it again - this conclusion is ambiguous. The fact is that: 1- it is always possible to fall into pages “B”, “C”, “D” without visiting “A”, if you use search systems; 2 - it is possible to call at once all three pages “B”, “C”, “D” from the page “A” if you “open links in a new window”. Besides, it is very often to get on the same site page by different ways.

Exactly, this is the advantage of calendar statistics, which allows you to minimize ambiguity observing the attendance for different days. So, if there are no visits on the page “A” someday and but there are visits on “B”, “C”, “D” – it means that visitors, really, go to them using alternative ways. So, we can approximately evaluate their level of attendance “passing A”. On the other hand, if there is a link from the page “G” on the page “D”, then it is possible separately to conduct observations for the pair “G-D”, it will allow you approximately to get the popularity of this transition.

It is necessary once again to say: this method of argumentations does not allow you to determine the popularity of any transition. It also does not allow you unambiguously to research the visitor traffic of your site. But, sometimes, when you know the site structure and 5-10 minutes of close observation for the calendar statistics, it is possible to receive an interesting conclusion. Or, in the worse case, you can understand that it is impossible to make such conclusion.

General rule: the described method often is useful for learning such sections of sites as “publications”, “picture galleries”, “catalog of products ”. There is often the “main” page in similar sections, from which (only from it) it is possible to get on other pages of the section. So, you should only to evaluate “background of search systems” and the conclusion is ready.

Be careful with conclusions: I just repeat the remark that this conclusion gives ambiguous results and it is impossible to give the strict recipe, when they are authentic or not. It is recommended to use the conclusions obtained on the basis of the argumentations, extremely as a “information for reflection ”, but not as a “guide to action”.


Some other conclusions from the calendar statistics

Generally speaking, looking at the calendar statistics, it is possible to make some other conclusions, reasoning analogically, as with the analysis procedure of some other kinds of statistics considered in the previous chapters. In some cases the calendar statistics is more convenient and evident than other kinds of the reports of the RCounter system, in others - simply supplements them. I, without long explanations, can specify on these possibilities and you, I hope, can independently evaluate their value and convenience in your own case.

  1. It is possible to analyze the attendance actions of a separate page, to consider its peaks and recessions of attendance. If this page itself extremely visited, it can be possible to make quite reasonable conclusions on the basis of this statistics;
  2. Observing “empty” lines (the data lines by pages which nobody visited for this month, remain empty, without numbers) you can ask yourself: “Is this page accessible or may be the link to this page is broken?”;
  3. Comparing the data in columns “Max” and “Average”, it is possible to evaluate easily “steepness” of attendance peaks. When the data in these columns differ no more than in 1.5 times – it means that there were no big peaks for this month, the attendance was equal enough. When the difference is 3 times and more – it means that there were significant surges of the attendance;
  4. Considering a parameter in the column “Total” concerning each page, you can ask yourself: How rationally does updating of either one or another site section make? It will be logical to suppose that it is useless to spend lots of forces for updating poorly visited pages - it is better to waste your time on development of those pages, which are popularly. On the other hand, it is possible to think about how to improve those poorly popular pages to make them better. With the help of the calendar statistics such argumentations is easy to create more correctly than considering the general level of the page attendance for all time of site existence. In particular, any page could recently have a lot of visits and it was a sense to work with it and for last months the interest to this page has disappeared and it is possible that there is no sense to improve it further..

6. Final conclusion

Dear reader, after finishing this document, you probably have noticed two things: firstly, disadvantages of the “RCounter” system, when some valuable information simply does not suffice in the reports and some information you should get with the help of a calculator. Secondly, a set of “but”, “probably”, “as a rule” and other similar turns of speech forcing to doubt in reliability of many conclusions, which I have described.

I’ll willingly be explained about each of these defects.

As to defects and limitation of the “RCounter” system – only the version 1.0 of Rcounter had been used for preparation of this document. But already in that time I had the version 1.1, which new possibilities permanently forced me to think “Does it make a sense to write this document now or it is better to wait for the new version issue in which many conclusions will be possible to make without a calculator and additional thoughts?” But I always responded myself: “It’s worthy of it!”. Because, I can responsibly declare that users could not see the version 1.1 …… because the version 2.0 will be issued. For last months, as well as during preparation of this paper, we have collected so many ideas, wishes and lots of improvements (some part from which, by the way, has already realized) that the following version of the RCounter system will represent as a conceptually new product. And I am completely sure that the majority of pretensions to the contents of the statistical accounts, which can appear during reading this document, will be removed once and for all.

As for numerous “but”, “probably” and “as a rule” meeting in my document. Partly, they are also from imperfection of the RCounter reports and lack of the information into them. But there are also other reasons. Among them the main is my desire to save you from too hasty conclusions, my attempt to push you to independent argumentations, in which you can get more high-quality results, better than those which can be introduced by simple usage of a calculator and my ready-used advices, which I could give you instead of my numerous “but”, “probably” and “as a rule” turns of speech. But there is another reason - I am not sure completely as far as it is lawful to transfer the experience of my researches to other sites in some argumentations. In spite of the fact I have used Rcounter in different situations and for different sites with assorted levels of attendance, I think it is not enough. So, it would be a great idea to get from you any comments, remarks, additions as well as your criticism.

Here, I am going to finish this paper. Let me take leave and if you have any comments, please write at amfora@lvs.ru.

Good luck on the Net!


7. Other useful documentation, Internet-resources, addresses

Please, visit www.rcounter.noonet.ru to find out other documentation and articles about the RCounter product, new product versions, add-ons, and plug-ins as well as free version of the product and some examples of its usage.

Some Internet-resources:

    1. www.rcounter.noonet.ru - Internet-site of the RCounter product;
    2. www.noonet.ru & www.noonet.ru/eng/ - NooNet Internet-studio (our web-hosting provider, thank them for a lot of help and useful consulting).

Electronic addresses:

Maxim Bendersky – remlo@noonet.ru.
Alexander Rusin - amfora@lvs.ru;
NooNet studio - noonet@noonet.ru

RCounter v1.0 multiplatform. FREE
Count your visitors!
THE ANALYSIS OF SITE AUDIENCE OR 17 USEFUL CONCLUSIONS
By Alexander Rusin, English translation by Dmitry Sheremet.
September 18, 2001