1. INTRODUCTION

Today, we can observe libraries’ migration into digital space following potential users. The rapid growth of network information resources around the world, including library resources (websites, social network accounts, blogs, etc.), necessitated their organization and evaluation. On this ground, there arises webometrics and the need for webometric research. To date, webometrics has received several definitions. First, the use of the term “webometrics” in relation to quantitative indicators has been defined—“web statistics.” Another webometrics definition refers to it as “a field of research using the methods of bibliometrics of network information resources, structures, and technologies” (Björneborn & Ingwersen, 2001).

Libraries today have to compete with the alternative of instant access to information on the web. That is why libraries are now doing a great job of creating, analysing, and managing web resources (Udartseva, 2018). Libraries are aware of the webometric study potential to provide useful information about user behaviours on their web resources and have several aspects for use: service quality improvement, self-presentation of library products and services in virtual space, and use of empirical data for the implementation of various solutions at the level of web resource management (Lowe, 2012; Paul & Erdelez, 2009). Conducting webometric research, libraries, one way or another, need to tackle a number of pressing issues, the answers to which are a key factor in ensuring library competitiveness in the information services market, being, in particular, the basis for their effective activities in the online space:

Especially today, libraries need theoretical justification of existing issues and their practical resolution. Due to constant transformation of the web space, libraries look for new models and mechanisms of website management. Webometric research will help to better understand the user audience and evaluate library performance in web space. The world libraries of different levels and types are engaged in the development of the issues raised.

The aim of this research was to:

In addition, some metrics correlation was found; this feature was taken into account in this study, which allowed us to give an optimal interpretation of current indicators.

2. LITERATURE REVIEW

3. METHODOLOGY

In this study the author used a quantitative approach. This study was conducted based on a sample of websites of the largest scientific libraries in Siberia and the Far East. The obligatory condition for selection was that the library had the status of a coordinating centre for the libraries of the region, territory, and republic in Siberia and the Far East and that it was working in web space through its official website. Based on these criteria, there were selected 22 library websites of the largest scientific libraries of Siberia and the Far East, which are research institutions in the fields of library science, bibliography and book history, and are organizational-methodical and coordinating centres of libraries of the region, territory, and republic. The relevance of the library website URL address was checked manually during direct visits to the website. At the time of the study, all website URL addresses of the Siberian and Far Eastern scientific libraries, presented in Table 1, were relevant. In order to assess the popularity of web-based analytical tools, which are preferred by the Siberian and Far Eastern scientific libraries, the Pr-cy.ru analytical tool was used, as well as the analysis of websites by general browsing (de visu) for the purpose of additional evaluation. Pr-cy.ru is a free website analysis service that offers a variety of indicators and is an affordable online tool. In this study, we used it due to availability. When analysing the website, Pr-cy.ru determines the unique identifier of the counter being used by the counter code, which is located on the website pages. Monitoring was conducted in June 2018.

Table 1.

Web analytics tools for scientific libraries in Siberia and the Far East (June 2018)

Using web analytics tools makes it possible to analyse the library segment in the web space and identify the main competitors in this area. One of such tools is SimilarWeb, a web service of the Israeli group of developers, which collects, analyses, and provides data on user digital behaviors, allowing creation of a prototype of user behavior and assessment of the audience involvement and loyalty on the website and mobile application. The basis of the web service functioning is the big data processing technologies characteristic of such web analytics tools. SimilarWeb is widely used for competitive intelligence and is especially important in a situation where the web-analytical data describing library websites is not accessible. The accuracy of the data obtained, according to the web service users in Russia, is 90-95% (Mamon, 2017). With the use of SimilarWeb service, data on the attendance of scientific libraries in Siberia and the Far East for a six-month period have been collected. The period (six months) was not chosen by chance. First, SimilarWeb service provides data only for the last six months, and second, this period is optimal, allowing predicting data for the other half of the year, which generally gives a good result. Monitoring was conducted 3-27 July 2018 by key traffic metrics (visits, average visit time, average visit depth, bounce rate, and traffic sources) since they are potentially important for explaining the effective development of libraries on the web. Noting the importance and crucial significance of traffic metrics to assess the efficiency/inefficiency of the library website, we will take them as a basis for our research.

Data from reports of Pr-cy.ru and SimilarWeb services have been entered into an Excel spreadsheet, sorted and constructed to define the regularities of using web analytical tools and current development of scientific libraries of Siberia and the Far East. Webometric indicators without analysis present formal statistics; of particular value is the interpretation of data collected using analytical systems. Interpretation of webometric indicators was based primarily on:

For ease of analysis, the data collected were compiled into separate tables, and the indicators summarized based on the assessment were reformatted into visual elements to make them easier for researchers to understand.

4. RESULTS

Twenty-two websites of the Siberian and Far Eastern scientific libraries have been monitored for the use of web-based analytical tools and their openness. As a rule, statistics from the web-analytical tools of most libraries are closed to “outsiders”; in particular, 15 of the 22 viewed library websites have closed counters. At the time of the study, the following libraries had open access to the statistics of some web analytics tools: N. N. Muravyov-Amursky Amur Regional Scientific Library (LiveInternet), A. S. Pushkin Magadan Regional Universal Scientific Library (LiveInternet), Novosibirsk State Regional Scientific Library (Yandex.Metrica), N. G. Domozhakov National Library (LiveInternet), S. P. Krasheninnikov Kamchatka Regional Scientific Library (Rating@mail.ru), A. S. Pushkin Zabaikalsky Regional Universal Scientific Library (HotLog), and V. Ya. Shishkov Altay Regional Universal Scientific Library (Rating@mail.ru). This confirms the statement that most libraries close their analytical tool data.

According to Pr-cy.ru, the most commonly used web analytics tools of libraries are Google Analytics, Yandex.Metrica, and LiveInternet. Yandex.Metrica holds the leading position; this analytics system is used by 16 libraries, Google Analytics takes the second place (9 libraries) and, finally, LiveInternet takes the third position; this counter is installed on the websites of five Siberian and Far Eastern scientific libraries (Fig. 1). The data obtained by general browsing on the library website are slightly different, since Pr-cy.ru has not identified such web-analytical tools as Rating@mail.ru, Sputnik, and HotLog. All of these are free Russian-language analytical systems that allow collecting data on website traffic by installing the counter code on the website pages.

Fig. 1.

Popular web analytics tools for scientific libraries in Siberia and the Far East (Russia).

As a result, we can conclude that the Pr-cy.ru marketing tool defines only classical acknowledged web analytical systems (Table 1). Another interesting fact is that using general browsing, no information was found on any websites about the collection of statistical data using Google Analytics.

An important indicator of the success and popularity of the library website in virtual space is the increase in its traffic (attendance). To obtain a correct attendance assessment of a library web resource, it is necessary to constantly monitor a number of the selected key traffic metrics. Webometric attendance characteristics of the Siberian and Far Eastern scientific libraries according to SimilarWeb are presented in Table 2, with the exception of data from the website of Sholem Aleichem Birobidzhan Regional Universal Scientific Library (data not available in SimilarWeb), and data from eight libraries which are only partially presented.

Table 2.

Attendance of scientific libraries in Siberia and the Far East according to SimilarWeb (1 January-31 June 2018)

The high visit rate is shown by the website of the State Universal Scientific Library of the Krasnoyarsk Territory: 55.93 thousand per month. The average time of website visit is 5.17 minutes. It is also the best indicator among the websites of the Siberian and Far Eastern scientific libraries. Only the website of the Novosibirsk State Regional Scientific Library is slightly behind: The average visit time is 5.15 minutes, and the average visit depth has the highest rate among the libraries analysed at 6.93 pages. The average visit depth for the websites of the Siberian and Far Eastern scientific libraries is 3.58 pages; based on the informational component of library websites, this is a pretty good indicator. The lowest bounce rate (45.78%) is for the website of A. S. Pushkin Omsk State Regional Scientific Library, and the highest (78.57%)—is the website of the Ugra State Library.

Traffic sources are the channels through which users come to library web resources. A steady flow of users through these channels is the key to the success of any library web resource. Direct traffic is received by entering the website through a targeted search, typing in the search box the address of a particular website or going from previously saved bookmarks. The websites of A. S. Pushkin Omsk State Regional Scientific Library (40.52%), Novosibirsk State Regional Scientific Library (39.00%), and N. G. Domozhakov National Library (35.97%) have the highest rates of this type of traffic, which is an indicator of the positive image of their permanent audience. Referral traffic (Referrals) is the traffic of visitors who have followed links from third-party portals. The highest rate of this traffic is for the website of the National Library of the Republic of Sakha: 12.53%. The average rate of referral traffic for the Siberian and Far Eastern scientific libraries is 4.5%. High rates of transitions from search engines (Search), so-called organic traffic, are the result of well-conducted promotion of a web resource in search services. The websites of S. P. Krasheninnikov Kamchatka Regional Scientific Library (87.00%), D. I. Mendeleev Tyumen Regional Scientific Library (82.66%), and A. S. Pushkin National Library of the Republic of Tyva (81.12%) stand out for the highest rates of this kind of traffic, which is an indicator of the websites’ quality. Traffic from social networks is quite relevant today because users spend a lot of time there, and the task of libraries is to use it correctly. The highest rates of traffic received from social networks are from the websites of A. S. Pushkin Omsk State Regional Scientific Library (6.27%), V. Ya. Shishkov Altay Regional Universal Scientific Library (5.68%), and I. I. Molchanov-Sibirsky Irkutsk Regional State Universal Scientific Library (5.67%). The websites of A. S. Pushkin Omsk State Regional Scientific Library and V. Ya. Shishkov Altay Regional Universal Scientific Library receive the most traffic from VKontakte social network, along with the website of I. I. Molchanov-Sibirsky Irkutsk Regional State Universal Scientific Library—from Facebook. The average traffic rate from social networks for the Siberia and Far Eastern scientific libraries is only 2.9%, which is the result of the lack of effective library work on social networks. It is obvious that in terms of promoting their own resources and services, some libraries do not work with social networks and do not even have accounts, which affects the overall traffic. Knowledge of traffic sources will allow libraries to conduct marketing activities in virtual space most effectively.

The analysis of traffic metrics allowed ranking the library websites in Siberia and the Far East by attendance, comparing the key attendance indicators and highlighting the most effective websites (Fig. 2).

Fig. 2.

Ranking of scientific libraries in Siberia and the Far East (Russia) according to SimilarWeb (1 January-31 June 2018).

As on several library websites, some of the traffic metrics were absent in SimilarWeb, and only 13 websites of the Siberian and Far Eastern scientific libraries are presented for ranking, the traffic metrics of which are presented in full. A checklist of libraries is provided in Appendix. Each website selected for the study was carefully evaluated based on the checklist and data table. A high position in the rating of the websites’ attendance of the Siberian and Far Eastern libraries is an indicator of competitive advantage among the analysed libraries’ websites.

5. DISCUSSION

6. RECOMMENDATIONS

Library website performance depends largely on the improvement of its webometric indicators, which reproduce the current situation of each website individually. From the discussion above, it is clear that libraries need to review the current strategy of their own websites’ development. For this reason, we provide the following recommendations to help libraries achieve greater efficiency. This study showed that the presented attendance key metrics most fully recreate the picture of the current development of library websites. Based on the data obtained, it is recommended to libraries with low visit rates (A. M. Gorky Primorsky Regional Public Library, N. N. Muravyov-Amursky Amur Regional Scientific Library, Sakhalin Regional Scientific Universal Library, N. G. Domozhakov National Library) to increase website productivity by reconstructing the whole website or its individual pages. In addition, a clear way to attract more users is placing interesting content and links to other popular resources on the pages of the library website, which in turn will contribute to the increase of another no less important indicator—average time spent on the website. Another recommendation is that the content should be up-to-date and constantly updated, which will increase the response rate of users to the published content. While high depth with low bounce rate indicates audience interest in the library website, low depth with high bounce rate indicates problems. As recommendations to libraries whose websites demonstrate such indicators (Ugra State Library, A. S. Pushkin Tomsk Regional Universal Scientific Library, D. I. Mendeleev Tyumen Regional Scientific Library), it is offered to carry out optimization to eliminate the arising problems when users interact with them. Library websites with high bounce rates (Table 2) should pay attention to the website navigation system to facilitate the search for necessary information.

The increase in quantitative indicators of traffic contributes not only to the growth of the visitors’ numbers, but also to the increase of awareness in general, along with conversion of traffic into targeted actions on the website: subscription to a newsletter, seeking advice, ordering literature from electronic catalogues, application for any services, etc. Libraries are recommended to work not only with the most efficient traffic sources (“direct traffic” and “search traffic”) to increase their efficiency and promote their own web resources, but also pay attention to the insufficiently productive traffic sources (“social traffic”) to conduct a detailed analysis and improve current performance. Based on the study results, we can give several recommendations for further research. In order to study library website convenience, we recommend usability testing. In combination with the results of the work made, it will allow taking into account the website user preferences. Another way is to make a detailed analysis of the website using the advanced functionality of analytical systems (Google Analytics, Yandex. Metrica) that will expand the results of this study regarding the attendance key metrics.

7. CONCLUSION

The experience of Russian libraries in the field of webometrics should be expanded by studying and transforming the existing foreign practice. The literature review showed that the current state of Russian libraries significantly differs from their foreign competitors. Libraries are just beginning to gain experience in this area, are engaged in the selection of web analytical tools, realize the need to use key metrics, and are building the necessary technology to assess the performance of their own web resources, while facing various analytical difficulties.

The study results show that the Siberian and Far Eastern scientific libraries use the analytical systems Yandex.Metrica, Google Analytics, and LiveInternet to collect statistics, which also confirms the hypothesis that scientific organizations are interested in assessing their own resources.

Metrics tracking with web analytics tools is a great way to manage library websites. For successful functioning of a web resource, it is important to conduct a webometric study: to analyse webometric indicators, conduct competitive intelligence, determine one’s own target audience, study the factors affecting the implementation of targeted actions on the website, and so on. Literature review (Chepushtanova, 2016; Fagan, 2014; Guskov et al., 2015; Jansen, 2009; Kann, 2017; Udartseva & Rykhtorova, 2018; Vecchione et al., 2016) showed that key traffic metrics are the foundation for evaluation of library websites’ performance. By choosing attendance indicators for monitoring, libraries will be able to usefully conduct webometric studies of their own websites.

Using data from web-based marketing tools to collect and analyse data, such as SimilarWeb, Alexa, Pr-Cy.ru, and others, will allow libraries to provide an analytical overview of competitors in the web environment. Use of SimilarWeb service can be recommended as an alternative source for collecting key traffic metrics: visits, traffic source (direct traffic, referral traffic, search traffic, and social traffic), average visit duration, pages per visit, and bounce rate. Based on the received data, the most effective websites of the Siberian and Far Eastern scientific libraries have been revealed. The important webometric attendance indicators are considered separately, and the interpretation based on the study objectives is given. Analysis of webometric indicators allowed assessing the current state of scientific libraries in Siberia and the Far East. The three leaders are the websites of the Novosibirsk State Regional Scientific Library, State Universal Scientific Library of the Krasnoyarsk Territory, and V. D. Fyodorov Kemerovo Regional Scientific Library. Any library is able to improve its own position by collecting and analysing key indicators of their website traffic.

Analysis has shown that two types of traffic are the most effective for libraries: direct and search. The same conclusion was reached by scientists (Guskov et al., 2015) who studied the websites of universities of the Siberian Branch of the Russian Academy of Sciences (10 websites), which may reflect a certain regularity for the websites of scientific organizations. Further research will confirm or refute the hypotheses previously put forward in this study.

Analysis of traffic metrics showed how effective/inefficient the activity of scientific libraries in Siberia and the Far East is. Based on the traffic indicators, the rating of libraries in Siberia and the Far East was built, thus clearly presenting the current status of website attendance (traffic). This study results indicate the libraries’ potential to improve their web resources. The study will give impetus to libraries with insufficient attendance to take the necessary measures to improve current performance and change their own development strategy.

As a result, we note that the generalized statistics of website traffic using SimilarWeb service does not give specifics on the existing problems of the website. Nevertheless, it is interesting, allowing us to assess the current development of the websites of the Siberian and Far Eastern scientific libraries. Projecting the positive experience of a competitive library towards oneself is one of the important reasons to conduct such research.