=Paper=
{{Paper
|id=Vol-2392/paper20
|storemode=property
|title=Online Community Information Model for Use in Marketing Activities
|pdfUrl=https://ceur-ws.org/Vol-2392/paper20.pdf
|volume=Vol-2392
|authors=Natalya Shakhovska,Oksana Peleshchyshyn,Zhanna Myna,Tetiana Bilushchak
|dblpUrl=https://dblp.org/rec/conf/coapsn/ShakhovskaPMB19
}}
==Online Community Information Model for Use in Marketing Activities==
https://ceur-ws.org/Vol-2392/paper20.pdf
Online Community Information Model for Use in
Marketing Activities
Natalya Shakhovska1 [0000-0002-6875-8534] , Oksana Peleshchyshyn 2[0000-0002-1641-7340],
Zhanna Myna 3[0000-0001-7954-5799] and Тetiana Bilushchak4 [0000-0001-5308-1674]
Lviv Polytechnic National University, Ukraine
nataliya.b.shakhovska@lpnu.ua1, oksana.p.peleshchyshyn@lpnu.ua2,
zhanna.shijaniuk@gmail.com3, tetiana.m.bilushchak@lpnu.ua4
Abstract. Some aspects of the use of virtual communities in the marketing ac-
tivity of the enterprise have been considered. Based on a formal description of
characteristics, data on online communities and discussions and their analysis
results, an information model of a community for online marketing has been
built, which serves as the basis for a database structure for accounting of infor-
mation flows in online communities. The problem of determination of indica-
tors of relevance and importance of online communities for marketing, use of
these indicators in solving community selection tasks for participation of repre-
sentatives of the enterprise has been considered. The use of the database provi-
sioning in the process of creating, verifying and distributing marketing messag-
es in virtual communities has been proposed.
Keywords: Online Marketing, Online Community, Information Model.
1 Introduction
The use of virtual communities in the marketing activities of the enterprise requires
all participants in the communication process to make strategic and immediate deci-
sions regarding specific actions and marketing events. The availability of the compo-
nent of decision support demonstrates the technological maturity and completeness of
the project of the enterprise's comprehensive IT penetration.
Among the typical tasks, the key ones with regard to the activities in online communi-
ties are the choice of the strategy for using communities in marketing; selection of
online communities for certain activities; analysis of the effectiveness of marketing
information flows in the virtual environment.
An important aspect of successful online marketing in an information-intensive envi-
ronment of the online communities is the use of the state-of-the-art IT solutions, cus-
tom-made mathematical tools and software in all parts of the process. In particular,
there is a need to process large pools of data in real-time, in the data mining and au-
tomation of some processes and tasks.
Some aspects of the company's activities in the social media of the Internet are the
subject of research on information retrieval and analysis of web space content [1, 3, 9,
11, 12, 20], development of methods for building and managing web communities [7,
13, 14], positioning of websites in the global environment, management of infor-
mation activities of the company in the networks of sites [21, 23, 25, 27], organization
of marketing in online communities [8, 10, 15, 17, 24, 26, 28]. The have investigated
the use of international standards of quality management system in higher educational
institutions. It has been found that the effective work of a university, in order to
provide educational services, depends on the implementation of quality standards ISO
9001 [6].
The concept of relevant and important for marketing online communities and discus-
sions has been introduced in [5], while the basic strategies for using online communi-
ties in marketing, the necessary resources and risks during their implementation have
been defined in [4].
2 Information Model for the Virtual Community for Online
Marketing Needs
2.1 Formal communities’ data model for online marketing
Competent activity of a marketing expert in virtual communities should take into
account the peculiarities of the communication process in online environments, in
particular the availability of certain traditions and rules of interaction between com-
munity members. Formalizing the communication process, analyzing and computer-
based accounting of the characteristics of online communities and marketing infor-
mation flows provide support for the activities of the marketing expert during the
generation of marketing messages and participation in discussions.
The structure of the online community VCi from the array
VC VC i i 1 ,
N VC
(1)
of online communities that are used in marketing is described as follows:
VCi NameVCi , DiscrVCi , TechVCi , RuleVCi , RuleLangVCi ,
StatVCi , RThVCi , AdvVCi , AnRELVCi , AnIMPVCi , TpVCi ,
(2)
where NameVCi – is the name of the i-th online community; DiscrVCi – description
of the i-th community; TechVCi – technical specifications of the i-th online communi-
ty; RuleVCi – the rules of the i-th community; RuleLangVCi – communication lan-
guages in the i-th community; StatVCi – statistical data of the i-th community;
RThVC i – relevance of the topic of the i-th community with marketing topic; AdvVCi
– recommendations for working with the i-th online community; AnRElVC i – results
of the analysis of the relevance of the i-th community; AnIMPVC i – results of the
analysis of the importance of the i-th community for its use in marketing; TpVC i –
discussions of the i-th online community.
The technical specifications needed in the process of using the online community
to solve marketing problems are described as follows:
TechVCi URLVC i , CMSVCi , MLVCi
(3)
where URLVC i – the website address of the i-th community; CMSVCi – community
site management system; MLVCi – markup language (BB Code, HTML, etc.).
The rules for online communities are usually presented in a free unstructured text
format, which makes it impossible to directly enter them into a specialized database.
Therefore, it is necessary to analyze the rules manually by certain definite features.
The list of features for formalization and subsequent computer accounting usually
depends on the task. The main characteristics that are subject to accounting are the
following:
─ languages of communication;
─ permission to publish advertising materials;
─ restrictions on the use of graphic images (size, type list, possibility of connecting
external files);
─ restrictions on the use of attached files;
─ restrictions on user names (case, the Roman/Cyrillic characters, aliases, site ad-
dresses);
─ restrictions on user's photos (admissibility and user image size);
─ restrictions on user's signature (number of characters, number of rows, admissibil-
ity of graphic images, admissibility of references);
─ restrictions on links (admissibility of links, admissibility of referral links).
Community rules regarding the languages of communication of their participants
RuleLangVCi are important in the process of communication, preparation of promo-
tional and informational materials. The linguistic characteristics of the target audience
are taken into account when creating an array of marketing terms that are used for
searching for relevant online communities.
To describe the rule for using the language of communication Lang j in the com-
munity VCi , we introduce the function of defining a priority PLangVCi Lang j , the
value of which is: PLangVCi Lang j 0 - if the language is not used in the online
community; otherwise, the function value (integer) indicates the priority of its use
when communicating as compared with other languages. Then the language use rule
in the online community is described as follows:
RuleLangVCi PLangVCi Lang j j 1
N Lang (4)
where Lang j Lang Lang j N Lang
– j-th language of communication from the array of
j 1
communication languages that a company uses in marketing in online communities.
One way to adapt marketing actions to the requirements and traditions of online
communities is to use recommendations when creating messages. These recommen-
dations are obtained as a result of the analysis of rules and community traditions. The
structure of recommendations AdvVCi regarding the work in the community is rec-
orded as follows:
AdvVCi AdvUserVCi , AdvPostVCi
(5)
where AdvUserVCi – recommendations for the optimal version of the user name of the
i-th online community (nick, real name and surname, website address, company or
product name); AdvPostVCi – recommendations for the creation of posts in the i-th
community, which should contain the following information:
─ expediency of using in-depth formatting and a large number of links in one mes-
sage;
─ expediency of using advertising graphic objects;
─ optimal size of the message;
─ additional linguistic characteristics (youth slang, industry slang);
─ admissibility of extended citation of sites.
To link the topics of the online community VCi and identified marketing topics
Th Th N , we introduce the adherence function FRThVCi Th j : FRThVCi Th j 1 - if
Th
i i 1
the topic of discussion relates to the marketing term Th j from the array Th , otherwise
FRThVCi Th j 0 .
Then, we will describe the relevance of the topic of the online community as follows:
RThVCi FRThVC i Th j j 1
N Th
(6)
where Th j Th – j-th marketing term.
For decision-making on the use of the online community in marketing and in the
planning of the communication process, it is important to record and analyze commu-
nity statistical data. The required statistics for the online community VCi will be rec-
orded as:
Tij , CMVC i Tij , CTpVC i Tij , CPVC i Tij , CRVC i Tij ,
N StatVCi
(7)
StatVCi
CVVC i Tij , FrNTpVC i Tij , FrNPVC i Tij , CQVC i T
ij j 1
where T ij – i-th date of collection of statistical data for the j-th online community;
CMVCi Tij – count of members; CTpVC i Tij – count of topics; CPVCi Tij – count of
posts; CRVCi Tij – count of readings; CVVCi Tij – daily attendance of the community
(from Count of Visitors); FrNTpVCi Tij – frequency of new discussions started in the
community (Frequency of New Topics); FrNPVC i Tij – frequency of new comments
(posts) in community discussions (Frequency of New Posts); CQVCi Tij – the number
of external links to the community site from other sites (Count of Quotation).
The results of the analysis of the online community relevance to marketing topics are
as follows:
AnRELVCi AnRELDate j , RELVC ij
N AnRELDate
j 1
(8)
where AnRELDate j – j-th date of the relevance analysis; RELVC ij - relevance of the
i-th online community as on the j-th date of analysis.
Evaluation of the importance of the online community is as follows:
AnIMPVCi AnIMPDate j , IMPVC ij
N AnIMPDate
j 1
(9)
where AnIMPDatej – j-th date of the importance analysis; IMPVCij – importance of
the i-th online community as on the j-th date of analysis.
The importance of the online community in formula (9) depends on the type of the
marketing task set for the company's specialists. The list of types of marketing tasks is
presented in the form:
TaskType TaskTypek k 1
N TaskType
(10)
Then the importance of the community, defined during the j-th analysis, will look
like:
IMPVCij TaskTypek , IMP TaskTypek ,VCi , AnIMPDate j
N TaskType
k 1
(11)
where TaskTypek – the task of the k-th type from the array (10);
IMPTaskTypek , VCi , AnDatej - the function of determining the importance of the
i-th online community for performance of the k-th type task; the date of the analysis
AnIMPDate j determines the relevance of the statistical and analytical data of the
online community needed to calculate marketing importance.
In addition to accounting of online communities in general, separate discussions, the
topic of which relates to the object of marketing promotion, should also be subject to
mathematical formalization, computer accounting and analysis. Given the complex
nature of the tasks of marketing, both technical information and the semantics of dis-
cussions conducted around the object of marketing promotion, should also be subject
to accounting.
2.2 Using The Content of a Database of Online Communities to Carry Out
Marketing Tasks
The given information model forms the basis of the database of online communities
relevant to the marketing subject of the company. Data arrays are created based on
expert analysis of each community that is being added to the online marketing data-
base. Sample community discussions, its general numerical values (usually these are
available on the community statistics page) and the texts of its rules are used for ex-
pert review
Data relating to the semantic characteristics of the online community are used when
creating and verifying marketing posts and choosing task performers. In particular,
the size of the post; the presence and number of references in the post; the presence of
referral links can be checked in the automated mode.
Data related to the technical characteristics of online communities is used, in particu-
lar, to determine the priority of actions and forecast work volumes, planning of work
schedules, software adaptation and hypertext markup of information and advertising
materials.
However, for solving some tasks, in particular, planning of the participation of the
company representatives in discussions, numerical expressions are required for these
characteristics.
The methodology for determining these indicators depends on the available infor-
mation on the characteristics of online communities and discussions. In any case, the
specifics of the tasks of prioritizing the actions of a marketing expert implies a quick-
er relative assessment of importance and relevance than the conditionally precise one.
This, to some extent, makes up for the incomplete information about the community.
There is no general rule for determining the importance and relevance of communi-
ties, because these rules reflect the essence and peculiarities of marketing strategies in
online communities.
We will assume that the topical characteristics of the search results for a particular
community determine the topical preferences the new visitors of the site (because
they get there by the topic queries) and active members of the community (since they
have created virtually all content of the online community).
Consequently, we may use the results of the search engines to determine the degree of
relevance of the online community, limiting ourselves to publicly available infor-
mation that does not require significant computing resources.
In this case, we will define the marketing relevance of the online community of the
marketing object as a part:
SERPVC *,Th
Rel VC * (12)
SERPVC *
where SERPVC * – the total number of pages in the online community in the search
results SERPVC * (from English Search Engines Result Page); SERPVC*,Th - the
number of pages of the online community found by the terms of marketing topics Th .
The array of marketing terms determines the width of further search that is reflected
in the number of communities found and their thematic orientation. Therefore, the
keyword selection procedure depends on which strategy of using the online communi-
ties in marketing has been chosen.
The value SERPVC*,Th only in trivial cases can be calculated in one step. In prac-
tice, multiple searches by exact match for each marketing term is required, with the
exclusion of other marketing terms.
According to the analysis, there are typical classes of communities in certain thematic
areas, which are presented in Table1. It is understandable that the values of limits
given in the table may vary substantially depending on the subject area.
Table 1. Classes of online communities by measure of marketing relevance.
Communities Relevance Comment
Only about one or a group of
Restricted professional 0.1–1
products
About some product group,
Professional 0.02–0.1 which includes the marketing
object
About some subject area, to
Topical 0.001–0.02 which the object of marketing
belongs
With uncertain or very broad
General 0.0001–0.001
subject matter
With topics not related to the
No topical 0
subject of marketing
For exclusive products, the specified limits for a class of restricted professional com-
munities are expanding, and for the rest - narrowing. This is caused by the fact that
the very fact of mentioning the exclusive, used only in special cases, products, already
gives grounds to attribute the community to a class of restricted professional. Such
products include industrial and medical equipment, professional artistic tools, highly
specialized software, corporate services, and the like.
For the products of a wider class, on the contrary, the limits of relevance for restricted
professional and professional communities are narrowing, for the rest - they are ex-
panding.
However, regardless of the specifics of products and the exact limits of class rele-
vance, their overall list remains unchanged.
The selection of online communities for solving certain marketing tasks is appropriate
to begin with identifying a set of online communities relevant to marketing object.
From the sample obtained, guided by the chosen selection strategy for a particular
task, one must allocate the resulting array of important communities. If you start with
identifying important communities, you can often get a great deal of important but
irrelevant online communities.
Since the array of online communities relevant to the subject matter may be quite
large and the resources for marketing in online communities are limited enough, then,
of course, there is the question of the need to limit the array of relevant communities
with which the marketing expert should continue working. This restriction can be
achieved by defining the relevance threshold rule and applying it to the selection: an
online community with a relevance indicator that is relevant to the relevance thresh-
old rule relevant to a given marketing topic; otherwise, we will consider this commu-
nity irrelevant (non-topical). The rule of the relevance threshold application is deter-
mined by the expert method and can be formulated in different ways, for example:
─ the first 100 relevant communities are considered;
─ communities with relevance indicator greater than some fixed value are relevant to
the topic;
─ selection of relevant communities is carried out in an iterative manner until the
required number of important ones is obtained.
Regarding the discussions, it can generally be considered that relevant are discussions
with messages that contain defined marketing terms. The greater part of the marketing
topics relate to the message, the more the discussion becomes topical. The marketing
expert takes the decision on the marketing relevance of the discussion after analyzing
the posts in the discussion and the following groups of its characteristics:
─ topicality of discussion - the relevance of the discussion to the marketing topics;
─ proficiency of the discussion - the competence of the authors, the acceptability of
the discussion style, its correspondence to network etiquette;
─ timeliness of the discussion - the openness of the topic, the relevance of messages,
the presence of views, answers.
Classification of discussions in online communities important for marketing gives us
the opportunity to:
─ organize the first-priority processing and analysis of typical discussions concerning
the problems and queries of users (complaints, claims, etc.);
─ carry out a comparative analysis of own and outside materials located in different
communities and on different occasions;
─ analyze typical discussions related to one topic when creating a new marketing
message on this topic to avoid repetitions and inaccuracies in it.
Saving of interconnections between thematically similar relevant discussions in the
database facilitates a comparative analysis of product reviews. Moreover, the estab-
lishment of relationships between company discussions and discussions about part-
ners and competitors of the company helps in the analysis of competitiveness of the
company by participants of online communities.
If a representative of the company initiated a discussion in the community or it con-
tains his/her extended comments, then the response of other members of the commu-
nity to the content and form of the marketing messages is important.
The analysis of negative reviews and critical messages allows identifying vulnerabili-
ties in the marketing object, assess the communicative proficiency of marketing ex-
perts and outline the ways to improve marketing in online communities.
3 Conclusions
Determining the indicators of marketing relevance and marketing importance of
online communities makes it possible to select the important for marketing online
communities and use them more effectively. Due to the practically manual processing
of the input information, determination of these indicators for discussions is generally
subjective. For a transparent and high quality assessment process, the professionalism
of the staff and the option of computer accounting of the discussions and the results of
their analysis are of great importance. Because of the formalization of the marketing
characteristics of communities, a model of online communities was built, which be-
came the basis for developing a database structure for the accounting and analysis of
marketing communications and information content of online communities.
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