Abstract
Lapshina E.V., Anohina I.Yu., Kushnirenko Ye.N. WEBSITE OPTIMIZATION FOR ONLINE STORE
The article raises the problem of information technologies development A model that describes the influence of various factors on the promotion of an online store website has been developed. The necessity of optimization of web sites is well-proven
The development of information technologies and, above all, electronic networks, gave a powerful impetus to a new environment formation, the intensity of which has become an important feature of modern business functioning. This led to the emergence of new forms of business processes with a significant share of the electronic component of business relations [1].
At the moment, the use of Internet technologies allows you to optimize business processes. More than a third of the top 100 US online trading systems provide e-commerce services. The global e-commerce market continues to grow: in 2018 its volume increased by 18%, and the total value of all online orders amounted to $ 2.86 trillion. A further increase in the number of participants in the segment of the e-commerce market and in Russia is predicted[2].
In early 2018, the Association of Internet Trade Companies (AKIT) predicted that the market would grow by 15%. A similar assessment was made in research of Institute for Economic Policy named after E.T. Gaidar, released in March. Nevertheless, according to the results of AKIT research in 2018, the volume of the Russian online trading market grew by 59% compared to the previous year [3].
The main place of interaction between the company on the Internet and Internet users is website. The interaction between users and website can be simulated in order to determine the optimal strategies for both developing and promoting the site, and, consequently, increasing sales, number of customers, etc.
Website development comes at a relatively low cost compared to constant media campaigns. The site can be specifically targeted to the buyer's profile.
A large number of tools for running Internet business is presented on the Internet. However, when choosing them, as a rule, heuristic procedures are used based on the experience, intuition and recommendations of various authors on website promotion. This led to the relevance of the tasks set.
The research objectives are:
- identification of factors influencing the development of the e-commerce system and the promotion of online stores, commercial brands on the network;
- development of models for assessing the impact of various indicators of e-commerce sites on the companies success level in the network;
- creation of a model describing the interaction of the Internet project website and network users.
Developing proposals to improve the efficiency of the use of Web sites for e-commerce.
Rating calculation method
The initial data for modeling were obtained from the rating results [4], which include a hundred largest Russian stores in terms of online sales in 2018.
The rating is based on a comprehensive methodology for constructing the rating and collecting data. By default, the rating is sorted by online sales.
The number of the store in the rating was chosen as a predicted variable. Stores included in the top ten were considered, i.e. having the highest sales volume; shops located in the middle and at the end of the Top.
The following factors were taken into account as the studied parameters:
Usability (denoted as the U variable in the calculations). The Usability Factor includes 10 parameters: the presence of intuitive icons; uniformity of the interface; predictable location of key elements; sitemap; “The principle of non-violence”; instant scrolling; simple structure of the main menu; no clutter of elements; using live search; concise and short texts.
The Menu View factor (hereinafter the VM variable) determines the horizontal, vertical or mixed presentation of the site menu. With its help, each visitor can easily navigate to the necessary sections and understand what information is presented on the pages. The main purpose of the site menu is navigation.
The font size, the RSH variable, is related to the number of fonts types used on the site, their sizes. Suitable font sizes have more visual weight and improve usability. According to research by Payame Noor University and IBM / Google, the larger the font size, the faster the reading speed. Large fonts with recognizable heading and paragraph styles allow the visitor to identify the headings on the page quickly and move faster to the next point [5], and, therefore, increase the comfort of work.
Page load time (VZ variable) is one of the important factors of site usability. Nobody likes to stand in line. Modern consumers will not forgive a page load for more than 2 seconds. Studies have shown that after three seconds of waiting for the download, 57% of visitors will leave the site [6]. Search engines also pay attention to the page load time of the site. Both Yandex and Google prefer fast resources. The reason is simple: the slower sites get to the top of the search engine results, the less often users will use it [7].
Google's PageSpeed Insights tool was used to measure the loading speed.
Personal discountsи (PS variable) are beneficial offers to specific customers. They include discounts for regular customers. Such offers are called “loyalty programs”. They are presented in the form of discount cards offered to the buyer. They accumulate bonuses. This technique works well in the case of high-margin goods, that is, with goods for which the increased demand is constant. [8].
Free shipping (variable BD) is the most favorite by buyers and, at first glance, the most unprofitable option for the seller. According to American marketers, for 59% of online shoppers, the delivery price influences the purchase decision, and 44% refuse to buy something if the delivery price is high. [9].
Return of goods (variable VT). According to ReadyCLOUD research, 80% of customers will not make a purchase if it is known for certain that returning from a given store is troublesome or impossible. Conversely, 92% of customers indicated that they will shop again in the same online store if the return policy is loyal to the customer. [10].
Mobile version of the site (variable MV). In 2019, the availability of website version optimized for mobile platforms became “must have” for commercial sites. This factor has a positive effect on Google promotion.
The mobile application (variable MP) allows the company to increase sales, create another channel for attracting customers and get an effective tool for returning customers. At the moment, a significant percentage of users regularly make purchases via mobile devices. In 2018, mobile traffic of online stores reached 64.5% [11].
According to Smart Insight, more than 95% of online consumers are registered in at least two social networks and use one of them constantly. Every year, social networks are increasingly replacing search engines for the online audience. Solvent young people under 24 prefer to search for information about a product or brand in social networks, and 1/4 of the respondents note that likes, reposts, comments in the store's community can persuade them to buy. In the group under 44, this is 1/5 of the respondents. The From social to sale research shows the relationship between Facebook reposts and likes and sales (both online and offline) – almost a third of users bought a product after reposting (Fig. 1).
Figure 1 – Impact of Facebook activities on online and offline sales (percentage)
Literary Descriptions s (LO variable) are magazines, brochures, useful articles that an online store produces for customers. They are aimed at acquainting the consumer with the ideas, goods, areas of the store activity.
The number of social networks s (variable KS) shows the prevalence of the store on the Internet. Social signals (reposts, likes, tweets), links from social networks have a positive effect on website promotion in search engines. The more subscribers, the higher this indicator is. Due to this, the probability of choosing potential customer of the proposed product increases [12].
According to a Forbes research, 78% of those surveyed said that companies' publications on social networks influence their decision to purchase a product or service [13].
Research
The view of the initial data is shown in Figure 2. All calculation procedures were performed using the Statistica package.
At the first stage, the data was processed using the Factor Analysis module.
The following tasks were set:
- Determine the number of operating factors and indicate their relative intensity.
- Reveal the characteristic structure of factors, i.e. to show what features of the object determine the action of one factor or another and to what relative extent.
- Reveal the factor structure of the studied features of the object, i.e. to show the share of influence of each of the factors on the value of one or another sign of this object.
Figure 2 – Initial data for modeling
The calculated factor loads are shown in Table 1. The share of the total variance (Prp.Totl) is about 70%.
Variables related to the characteristics of the goods return and the availability of a mobile version of the site were excluded from consideration as they take on the same value in almost all analyzed objects.
Studies have shown that the first factor includes: a variable that determines the type of menu (VM), the presence of a mobile application (MP) and the number of social networks (KS) in which the Internet portal is presented. Thus, in general, the first factor is related to the presentation level of the portal on the Internet.
The second factor is determined by the level of "friendliness" of the site (usability U) and the presence of several variants of fonts used when browsing the site, i.e. the second factor characterizes the user experience.
| Factor 1 | Factor 2 | Factor 3 | Factor 4 | |
| U | 0.41 | 0.60 | -0.24 | -0.48 |
| VM | -0.50 | -0.10 | 0.13 | 0.25 |
| RSH | 0.13 | 0.74 | 0.35 | 0.09 |
| VZ | 0.35 | -0.13 | 0.63 | -0.34 |
| PS | -0.01 | -0.51 | 0.43 | -0.61 |
| BD | 0.22 | -0.49 | -0.25 | 0.60 |
| MP | 0.56 | -0.36 | 0.51 | 0.05 |
| LO | 0.55 | 0.19 | 0.56 | -0.05 |
| KS | 0.66 | 0.06 | -0.16 | 0.44 |
| Prp.Totl. | 0.22 | 0.18 | 0.16 | 0.11 |
The third factor was the load time (VZ) and the presence of a literary description (LO), and the LO variable, as further studies showed, has almost half the effect of the load time. The third factor was mainly determined by the speed of work. The availability of personal discounts and free delivery of goods formed the fourth factor.
To assess the degree of influence of factors on the position of the portal in the rating, a regression model was built. The initial data was preliminarily transformed by introducing weight coefficients taking into account their factor loads and the proportion of variance determined by factors. As you can see, the greatest impact is exerted by the presence of a mobile version of the site and the functions that make the process of working, reading the site as comfortable as possible (Fig. 3).
Figure 3 – Results of regression analysis
The conducted cluster analysis made it possible to assess the proximity of the factors. It should be noted that the comfort of working with the site wins
such technical characteristics as download speed.
Figure 4 – Clustering variables
Cluster analysis made it possible to divide groups of Internet portals into 3 clusters. The breakdown was evaluated in the Discriminant Analysis module, which confirmed the breakdown into three clusters (Fig. 5).
Figure 5 – Results of dividing a group of Internet portals into clusters
The average values of the parameters for each cluster are shown in Table 2. The first cluster includes Internet portals that are on the first lines of the rating, i.e. the best. They are highly rated for usability, free shipping, mobile app and literary descriptions. Their feature is their serious representation in a large number of social networks.
The second sector is the middle tier portals. They are characterized by a lower assessment of the convenience of working with the site, although at the same time, the site loading speed is quite high, the number of social networks is on average about 4, while the number of portals of the highest rating reaches 8
Worst
portals, i.e. those at the bottom of the Top, nevertheless, have a fairly high rating of the site’s usability and high loading speed, which can be explained by the smaller number of auxiliary functions. They are distinguished by the lack of free delivery and literary descriptions, as well as low prevalence in social networks, on average about 2 social platforms.
| № cluster | Rating | Usability | Loading speed,sc | Free shipping | Mobile app | Literary descriptions | Social media |
| 1 | 14 | 8,5 | 2,4 | 0,5 | 0,5 | 0,4 | 6,2 |
| 2 | 36,7 | 7,3 | 1,7 | 0,3 | 0,3 | 0,2 | 4,0 |
| 3 | 71,2 | 8,1 | 1,5 | 0,0 | 0,4 | 0,0 | 1,4 |
A multiple regression model was developed, Figure 6. The marker type was determined by the number of the cluster, which included the object. On the basis of the proposed model, it is possible to determine the most essential characteristics of a website for promoting an Internet portal in the ranking.
Figure 6 – Results of forecasting using multiple regression model
– cluster 1
– cluster 2
– cluster 3
Checking the adequacy and accuracy of the model (error less than 9%) allows us to consider the model as corresponding to the real process.
Conclusion.
In conclusion it should be said that during the work on the model, various Internet resources were investigated, their strengths and weaknesses were studied. Based on the simulation, recommendations were developed:
- one of the main conditions for website promotion should be considered the portal representation level in the network, i.e. the number of social networks used;
- sites equipped with a large number of services will have a high loading speed, while it should not exceed three seconds[6];
- the portal should be user-friendly, intuitive, have a sitemap, i.e. follow the principles of usability, since only a small proportion of users are IT professionals;
- the site should take into account the peculiarities of different age groups, in particular, for the younger generation, an indisputable advantage is the availability of mobile versions, applications, etc., while older people prefer sites whose information is convenient to read (various options for people with peculiarities of vision), with detailed description of the advertised goods and services.
References
1. Поеров А.С. Совершенствование системы электронной коммерции в России: автореф. дис. канд. эконом. наук. ВПО «Московская академия предпринимательства при Правительстве Москвы», Москва, 2011.
2. Десять трендов онлайн-ритейла на 2019–2020 годы – vc.ru – Режим доступа: https://vc.ru/trade/59300-desyat-trendov-onlayn-riteyla-na-2019-2020-gody
3. Интернет-торговля рынок России – Tadviser.ru Государство, бизнес, IT. – Режим доступа: http://www.tadviser.ru/index.php/Статья:Интернет-торговля_(рынок_России)
4. Рейтинг ТОП-100 крупнейших интернет-магазинов России – Data Insight 2015-2019 – Режим доступа: https://www.top100.datainsight.ru
5. Как размер шрифта влияет на UX и конверсию? – LPgenerator.ru – Режим доступа: https://lpgenerator.ru/blog/2017/06/26/kak-razmer-shrifta-vliyaet-na-ux-i-konversiyu/
6. Как ускорить загрузку сайта? – TexTerra.ru – Режим доступа: https://texterra.ru/blog/kak-uvelichit-skorost-zagruzki-sayta.html
7. Как ускорить время загрузки сайта и почему это важно – Seo-akademiya.com – Режим доступа: https://seo-akademiya.com/baza-znanij/vnutrennyaya-optimizacziya/vremya-zagruzki-sajta/
8. Повторные покупки: как сделать так, чтобы к вам возвращались? – Lemarbet.com, Seo, PPC & Usability agency – Режим доступа: https://lemarbet.com/razvitie-internet-magazina/povtornye-pokupki-kak-sdelat-tak-chtoby-k-vam-vozvrashhalis/
9. Бесплатная доставка для интернет-магазинов – за и против – Callibri.ru Сервисы прокачки маркетинга – Режим доступа: https://blog.callibri.ru/besplatnaya-dostavka-dlya-internet-magazinov-za-i-protiv
10. Три правила работы интернет-магазина с возвратом товара – Evo.business – Режим доступа: https://evo.business/3-pravila-raboty-internet-magazina-s-vozvratom-tovara/
11. Зачем создавать мобильное приложения для онлайн магазина и сколько это стоит? – Dinarys.com – Режим доступа: https://dinarys.com/ru/blog/how-much-does-it-cost-to-build-a-mobile-app-for-commerce
12. Как социальные сети влияют на бизнес – Techno-effective.com – Режим доступа: https://techno-effective.com/kak-socialnye-seti-vlijajut-na-biznes/
13. Исследование товарного рынка России: какие товары, кому и как продаются в соцсетях – vc.ru – Режим доступа: https://vc.ru/marketing/61479-issledovanie-tovarnogo-rynka-rossii-kakie-tovary-komu-i-kak-prodayutsya-v-socsetyah