Exploring the role of client communities in increasing companies' value
Role of client communities in managing relationship with customers. Client communities implementation: best practices. Comparison of telecommunications companies which have, do not have online client communities. Limitations, future research directions.
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| Язык | английский |
| Дата добавления | 23.09.2018 |
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ФЕДЕРАЛЬНОЕ ГОСУДАРСТВЕННОЕ АВТОНОМНОЕ ОБРАЗОВАТЕЛЬНОЕ УЧРЕЖДЕНИЕ
ВЫСШЕГО ОБРАЗОВАНИЯ
«НАЦИОНАЛЬНЫЙ ИССЛЕДОВАТЕЛЬСКИЙ УНИВЕРСИТЕТ «ВЫСШАЯ ШКОЛА ЭКОНОМИКИ»
Факультет бизнеса и менеджмента
Тургунбекова Жибек Джамалбековна
ИССЛЕДОВАНИЕ РОЛИ КЛИЕНТСКИХ СООБЩЕСТВ В ПОВЫШЕНИИ ЦЕННОСТИ КОМПАНИЙ
EXPLORING THE ROLE OF CLIENT COMMUNITIES IN INCREASING COMPANIES' VALUE
Выпускная квалификационная работа - БАКАЛАВРСКАЯ РАБОТА
по направлению подготовки 38.03.02 «Менеджмент»
образовательная программа «Менеджмент»
Москва 2018
Оглавление
Введение
1. Теоретические основы клиентских сообществ, отношения компании с клиентами и ROI сообщества
1.1 Понятие и виды клиентских сообществ
1.2 Роль клиентских сообществ в управлении отношениями с клиентами
1.3 ROI клиентского сообщества
2. Исследование эффекта клиентских сообществ в повышении ценности компаний
2.1 Внедрение клиентских сообществ: лучшие практики
2.2 Факторы клиентских сообществ, оказывающих влияние на результативность компаний
2.3 Факторы клиентских сообществ, выявленные в результате контент-анализа
3. Сравнение компаний телекоммуникационной индустрии, имеющих и не имеющих онлайн клиентские сообщества
3.1 Методология исследования
3.2 Успехи компаний телекоммуникационной индустрии, имеющих онлайн клиентские сообщества
3.3 Ограничения и направления будущих исследований
Заключение
Список источников
Приложение 1
Приложение 2
Приложение 3
Приложение 4
Приложение 5
Приложение 6
Приложение 7
Приложение 8
Table of Contents
Introduction
1. Theoretical foundations of client communities, company-client relationships and community ROI
1.1 The concept and forms of client communities
1.2 Role of client communities in managing relationship with customers
1.3 ROI of a client community
2. Exploring the effect of client communities in increasing the companies' value….
2.1 Client communities implementation: best practices
2.2 Client communities' factors affecting companies' performance
2.3 Client community factors derived from content analysi
3. Comparison of telecommunications companies which have and do not have online client communities
3.1 Research methodology
3.2 Success of the telecommunications industry companies which have online client communities
3.3 Limitations and future research directions
Conclusion
References
Appendices
Appendix 1
Appendix 2
Appendix 3
Appendix 4
Appendix 5
Appendix 6
Appendix 7
Appendix 8
Introduction
In today's economic relations, the role of maintaining long-term relationship of a company with its clients, suppliers and distributors is notably increasing. This leads to gradual transition of many companies from transaction marketing to progressive relationship marketing. It is marketing where a company makes an emphasis not only on attracting customers, but also on retention of current customers. The term "relationship marketing" was introduced by L. Berry and was meant as acquiring customers, nurturing and strengthening relations with them (Berry, 1983).
Relationships become the most substantial resource that an enterprise possesses along with physical, financial, human and other resources. And since individual relationships with each client are not always possible and manageable, some companies have solved the task of interacting with customers by creating client communities. It allows businesses to maintain an open dialogue with the client. It also gives the client an opportunity to participate on an equal basis with the manufacturer in creation and improvement of the product/service. Thus, client communities establish a new form of interaction with a client.
It is crucial to distinguish a client community from a social network page. Firstly, the structural difference is that a social network page is provided by Internet-based application, while a client community is fully sponsored and run by the company. Secondly, similarly to a social network page, client community users interact with each other, ask questions, share ideas in discussions and easily find experts and like-minded peers. However, a primary goal of any client community is to formulate replies to customer support requests and pre-purchase questions. Additionally, it is set up to produce results after customers' feedback in the form of new product launch or product improvement. Thus, social networks are not the place where companies' communication with customers can deepen. Customers intend to more than just "follow" companies' social media accounts.
Also, the difference between a client community and a brand community should be explained. A brand community is the same as a client community - it gathers visitors, members, customers, brand fans and brand advocates. Moreover, a brand community can be social-media-based and offline. As for a client community, it is always a specialized web-platform where customers connect with each other and with a company. Customers ask questions, reply to them, share experience of product/service use, and suggest improvements, ideas and even innovations.
The central objective of the paper is to reveal benefits of online client communities and identify their effect on companies' value.
To achieve the objective, it is necessary to fulfill the following research tasks:
1) Give a definition of a client community, introduce its forms, the role in managing relationship with customers and ROI indicators;
2) Highlight and discuss the best practices of client community implementation;
3) Identify factors of client communities that affect companies' performance by conducting content analysis;
4) Compare Twitter pages of telecommunications companies which have and do not have client communities on the subject of favorable/unfavorable/neutral/non-relevant content
5) Review relationship between implementation of a client community and a company's value.
The research object is online client communities of companies from various industries. The research subject is the role of client communities in increasing companies' value.
In the research, the combination of qualitative and quantitative methods is used. Qualitative approach is utilized through the content analysis of 107 case studies of client communities gathered from seven websites: Jive Software, Lithium, Get Satisfaction, Higher Logic, AnswerHub, eXo and inSided. Through implementation of the content analysis, factors of client communities that affect companies' performance are identified.
Quantitative part of the methodology includes using the Janis-Fadner Coefficient of Imbalance. By applying the Coefficient of Imbalance, Twitter pages of five telecom companies from the case studies sample and of five telecom companies which do not have client communities are analyzed and compared on the subject of favorable/unfavorable/neutral/non-relevant content. Additionally, as the value indicator of a company, the stock price dynamics for the last 10 years of these telecom companies is collected. The goal is to find the relationship between dynamics and implementation of client communities.
The research consists of three chapters. In the first chapter, theoretical foundations of client communities, their role in managing relationship with customers and ROI indicators are discussed. The second chapter considers the best practices of client communities implementation derived from the case studies sample. The results of content analysis introduce client communities' factors affecting companies' performance. The third chapter analyzes Twitter pages of telecommunications companies which have and do not have online client communities by the means of the Janis-Fadner Coefficient of Imbalance.
1. Theoretical foundations of client communities, company-client relationships and community ROI
1.1 The concept and forms of client communities
According to Muсiz and O'Guinn's (2001) core definition of a brand community, it is a specially designed, non-geographically constrained community. It is based on a structured set of social relations among admirers of a brand. Customers play an important role in it. As brand communities do not have geographic boundaries, they can reside anywhere and even in virtual environment. Brand communities may take shape of local clubs with prevalence of direct interaction (Algesheimer et al., 2005), or they may be present entirely on the Internet.
An online brand community (OBC) is a crucial platform for companies to differentiate themselves and advance competitive position. An OBC allows firms to bolster relationship with customers and engage them in joint brand creation (Tsai et al., 2012). Online brand communities are run by companies and organizations from different areas. It includes but not limited to retail, telecommunications, financial services, education, healthcare, IT services, etc.
There are various classifications of online brand communities described in research literature. Hook et al. (2017) suggests that four forms of brand communities are found: offline, online, virtual, and social-media-based. An offline brand community comprises the in-person face-to-face gatherings of community members linked around a brand, with occasional interaction and a high level of involvement required from the brand itself.
Online brand communities, or online client communities, have no geographical constraints. They are located in online or virtual environment where members share information regarding a brand. Participation in online client communities occurs in a way that members engage through instant photo and video sharing at a global scale, as well as via discussions without in-person meeting. A virtual brand community is a social group emerging on the Internet where information exchange takes place around one central brand. The definitions of both online and virtual brand communities are similar in terms of exchanging information about the brand.
Lastly, social-media-based brand communities are formed on social media platforms such as “Facebook”, “Twitter” and others. Social media platforms are capable to host several brand communities at the same time, unlike online brand communities where the focus is directed to only one brand.
Advantages and disadvantages of online client communities. Nowadays more companies realize the advantages of online client communities, which include:
Low cost and global coverage (as opposed to offline brand communities) (Sicilia and Palazуn, 2008);
Physical context is not necessary (de Valck and Dambrin, 2007);
More active involvement, thanks to online feature (comparing to absence of such a convenient medium in offline BCs) (Sicilia and Palazуn, 2008).
Customers are a valuable source of innovative ideas for companies to create the right product or its modifications (Von Hippel, 2005);
Existence of practices in client communities that generate value for both companies and customers (Schau et al., 2009);
Opportunity to boost positive feelings about the brand and product category (McAlexander et al., 2002).
As for the disadvantages of the online client communities, researchers do not distinguish any of them, but the one:
Absence of physical contact (Sicilia and Palazуn, 2008).
Almeida et al. (2013) analyzed differences between firm-managed and customer-managed brand communities. Firm- and customer-managed communities share some commonalities, however there are multiple differences between them. They are presented in the Table 1 below.
Table 1 - Differences between firm- and customer-managed brand communities
|
Differences |
Firm-Managed BC |
Customer-Managed BC |
|
|
Community manager's goals |
Achieve marketing objectives Collect market research insights Boost participants' loyalty to their products and brands Increase their purchase behaviors |
Rarely have specific marketing goals Express their love and admiration for the brand through organizing and managing the community |
|
|
Customer profile |
Customers are more similar to each other in demographic characteristics |
Customers share psychographic commonalities |
|
|
Community managers' constraints |
Focus is on accordance between the tone and content of community members communications and other marketing communications being sent by the firm Unlikely to provide too much attention to discussions of competitor products |
Greater learning among customers about the product category |
|
|
Trust and identification |
More trust in the community manager Identifying with the community to a greater extent |
Less trust in community manager Less community identification |
Source: Almeida et al. (2013); compiled by the author
There is a term “a firm-hosted online brand community” which implies an Internet forum dealing with the products of a particular company's brand(s) and is started and afterwards served by the company (Gruner et al., 2014). A firm-hosted OBC has three types described in the Table 2 below.
Table 2 - Types of firm-hosted online brand communitites
|
Community access |
Activity control |
Host integration |
Member engagement |
||
|
Open OBCs |
High - consumers can freely join and leave this community type without obligation to meet any membership requirements |
Low - host firm does not restrain communication content and monitors it on irregular basis, letting members freely say own opinion about a product or share personal information |
Moderate - host firms are minimally integrated into the community, usually through responses to member questions, and they only occasionally participate in community communications |
Low - members seldom participate in other community activities |
|
|
Discerning OBCs |
Moderate - requires members to sign up before they can participate in any way, with no guarantee to be accepted to the community |
Moderate - community members may be discouraged from posting personal information |
High - host firm is highly integrated into the brand community through studious replies to member questions and regularly takes part in community activities and member conversation threads |
High - members involve in complex and contemplative interactions, and frequently participate in community activities |
|
|
Restricted OBCs |
Low - membership must be earned; new members may have to pay a fee to receive a community access code |
High - host firms carefully audit member communications; communication content is often restricted by limiting number of symbols in messages/prescribing the selection of particular words that members can use |
Low - host firms tend not to respond to member questions or take part in community communications |
Moderate - members' interactions are ordinary and usually irregular; members infrequently participate in community activities |
Source: Gruner et al. (2014); compiled by the author
1.2 Role of client communities in managing relationship with customers
For customers, relationship establishment and identity formation are easily shaped in the process of interaction activities. Therefore, it is imperative for ?rms to develop stronger relationships with them.
To develop relationship with customers within a client community, it is important for three antecedents to be present: identification with the brand sponsoring the community, a positive experience and trust in the client community (Martнnez-Lуpez et al., 2017).
Identification. Greater identification with a brand has a positive impact on motivation to interact with its other users. Identification with the community is a strong predictor of engagement with it (Yeh and Choi, 2011). Established social relationships help to create engagement with the community (Parmentier, 2015). Customer engagement with the client community positively effects his identification with it (Chou et al., 2016). So, the more a consumer identifies himself with the client community, the greater his engagement with it.
Experience. A brand community able to provide its members with good experiences is likely to see them have more stable relationships with it (Morgan-Thomas and Veloutsou, 2013). Online engagement entails consumers' cognitive and affective dimensions leading to an active relationship with the brand; the experiential value of such a relationship has a positive impact upon engagement (Mollen and Wilson, 2010). The process describing a consumer's engagement with a brand is influenced by the outcome of interactive experiences within its online client community (Brodie et al., 2013; De Valck et al., 2009).
Trust. For online client communities, in particular, where relationships also take place within a social space, trust has been found to be pivotal: a community cannot be successful if its members are unable to rely on it (Belanger et al., 2002; Corritore et al., 2003). Trust in a client community is defined as its members' overall reliance on each other and the brand sponsoring it; members have trust when they believe that other members and the sponsor will not act opportunistically. Trust is formed through a process of repeated positive experiences in the community, and steers consumer intentions towards engaging with it. An absence of trust is the main reason for consumers not interacting with online brands (Morgan-Thomas and Veloutsou, 2013).Thus, trust helps to stabilize relationships and enables cooperative and useful interactions between community members (Bruhn et al., 2013). Consumers believe more in other consumers than in companies, as they tend to attach more credibility to horizontal relationships (Kotler et al., 2010).
According to Yeh and Choi (2011), trust increases stickiness, which makes a user feel as a part of a community. Trust is a critical factor for establishing long-term relationships in a client community (Jung et al., 2014). When there is trust between the parties, it is more probable that there will be engagement (Fang and Chiu, 2010). As consumers develop trust in a brand, the relationship with it becomes more emotion-based (Hess and Story, 2005), and engagement intensifies when ties to the brand are more emotional and less cognitive (Franzak et al., 2014).
Engagement in a client community refers to community members' interactions, with each other and the brand, carried out on an iterative basis (Baldus et al., 2015; Brodie et al., 2013). It is also associated with the members' intentions towards collaboration (Laroche et al., 2012) and participation (Algesheimer et al., 2005) in the community. Every aspect affecting this iterative relationship between the consumer and the client community -- trust or perceived experience with the community--will have an impact upon engagement. It has been concluded that engagement with a client community has a positive influence upon more frequent participation.
One of the main challenges faced by brands in their client communities is to ensure that consumers participate there. Participation is particularly important for such communities' success and longevity (Woisetschlдger et al., 2008). It helps win new members and strengthens ties between existing ones (Tsai et al., 2012), and helps with the achievement of goals by both the brand sponsoring the community and its members (Bagozzi and Dholakia, 2006).
It has been suggested that client communities provide a unique platform for enhancing innovation activities by broadening the reach of actors as well as increasing interaction richness among them (Wurster & Evans, 1997). The rapid adoption of Internet-based communication technology adds capabilities for customer input to all stages of the innovation process. Product concepts can be shared more easily, and the Internet allows these to be tested and/or modified by customers.
1.3 ROI of a client community
Metrics play an important role in ROI calculations of a client community (Cothrel, 2000). They can be divided, according to the objectives that the company states when running own client community. Three client community objectives - Insights & Innovations, Client loyalty, and Awareness increase - are the basis for metrics division which is shown on the Table 3 below:
Table 3 - ROI metrics for a client community
|
Insights & Innovations |
Client loyalty |
Awareness increase |
|
|
-number of generated ideas -quality of feedback -survey results -number of implemented ideas -cost reduction -community improvement -time reduction on receiving feedback -average time of problem ticket solving |
-repeat visits -postings per day/week/month (in member-to member interaction programs) -session time -page additions (in member-generated content programs) -page revisions (in member-generated content programs) -frequent visitors |
-registered members -page views -session time -unique visitors -community click-through (what percentage of visitors to the home page click through to a community program) -read-to-post ratio (in member-to-member interaction programs) -audience penetration (if the total size of the target population is known) |
Source: Cothrel (2000); compiled by the author
Most of these measures describe the current situation in the community, but they do not provide complete picture on what it suggests to the business. There are three kinds of metrics that every client community should track. Economic metrics measure the ongoing financial value or ROI for the community. Activity measures describe the general health of the community and aid in managing the community on a day-to-day basis. Topic measures assess the ongoing insights that the community offers into the business's products or processes.
Topic measures may be the most difficult to define. They include measures of the most heavily trafficked community areas or discussion threads and the most commonly discussed subjects, based on content analysis across the community. They can also address concentration of interest, describing how member activity is distributed across the most commonly discussed subjects.
Three key concepts. Three concepts are core when considering community ROI: incremental value, conversion rate, and community member.
Incremental value is the difference between the value created by a business with an online community and estimated value that the business would generate in the absence of a community. It involves a comparison of community members and non-community members in terms of activities that are most relevant to the business objectives of the community. There are multiple ways to define community members. They can include all registered members, all users of community programs, only frequent users, only long-time users, or only active participants. Incremental analysis for a B2C client community focuses on the following metrics: visits, return visits, purchases, frequency of purchase, transaction size, and referrals. Incremental value analysis is not unique to online communities, as it can be used whenever a merchant or manufacturer wants to understand the purchasing behavior of one customer segment relative to another.
Conversion rate. While many people think of conversion as the process of driving commercial transactions, the notion can be applied to any situation in which a business seeks to motivate action on the part of the user. The e-commerce leader Amazon.com has long segmented its users into three categories: visitors, users, and customers. Visitors include anyone who comes to the site; users include anyone who has offered information, from providing feedback on the site to writing a book review; and customers are people who have made a purchase. Amazon.com focuses on conversion at each level, despite the fact that only customers put money in the till. In community ROI calculations, conversion rate is an important input to calculating the impact of community management. Once the incremental value of an individual community member has been established, the value created by converting additional members can also be quantified.
It has been suggested that brand loyalty develops from the positive reinforcement received from trying a brand and being satisfied with it, which leads to repeat purchase (Jacoby & Chestnut, 1978).
Stickiness. Retailers have long understood the value of keeping customers in a store longer and getting them to return more often (Hirschman, 1981). In the online world, this concept is called “stickiness” (Gillespie et al., 1999). Stickiness is “the sum of all the web site qualities that induce visitors to remain at the site rather than move on to another site” (whatis.com). In other words, site stickiness is the ability to encourage customers to stay longer, navigate more deeply into a site, and return more often (Gillespie et al., 1999).
Site stickiness, as measured by duration of visit, depth of visit (i.e., number of web pages viewed at a given site), and repeat visits may be an effective indicator of favorable attitudes leading to brand loyalty for experiential uses of the Web, but efficiency measures unrelated to stickiness may be more appropriate for task-oriented uses of the Web.
Increased brand loyalty has measurable results for each consequence predicted in the model: affective, cognitive, and behavioral. Site users who become community members increase the length of time spent on the site, return more often, and generate more activity (as measured by community postings) compared to users who are not community members.
Conclusions from the academic literature review
The current chapter of the paper examines existing academic literature on the subject of the client community concept, its forms, consequences of implementing a client community on the relationship with clients and community ROI indicators. As a result of the conducted literature review, multiple conclusions are made:
- Various classifications of client communities exist: (1) offline, online, virtual, social-media-based brand communities; (2) firm-managed and customer-managed brand communities. Client communities' advantages are global coverage, boosting positive feeling about a company's brand, positive experience, trust and engagement of customers into community;
- In order to develop fruitful relationship with customers, a client community has to provide them with the feeling of identification with the brand, positive experience and trustworthy nature of collaboration. Moreover, these antecedents have an impact on customer engagement into community and loyalty to the brand.
-A client community's ROI metrics can be divided into several categories. Firstly, Insight & Innovations include number of generated ideas by customers, quality of feedback, number of implemented ideas, etc. Secondly, Client Loyalty comprises such indicators as repeat visits, postings per period, frequent visitors, etc. And lastly, Awareness Increase consists of registered members, read-to-post ration, community click-through, etc.
The subsequent chapter considers case studies of companies which implemented client community and results of implementation. Categories of client communities' factors affecting companies' performance are derived from the content analysis.
2. Exploring the effect of client communities in increasing the companies' value
2.1 Client communities implementation: best practices
In this section, the most outstanding cases of client community implementation are discussed which are included in the sample of 107 case studies. Particularly, the problems that companies faced before implementation of client communities are described with found solution and results. The case studies were gathered from multiple IT-providers of client community platforms - Jive Software, Lithium, Get Satisfaction, Higher Logic, AnswerHub, eXo, and inSided. Six corporations were chosen as the “best practices” for this section. The thorough analysis of 107 case studies is made in subsequent section.
EMC
EMC Corporation (until 2016, presently - Dell EMC) is an American multinational corporation. It sells computer software aimed at data storage, information security, analytics, cloud computing and other products and services (Wikipedia).
Problem. In 2010, EMC's global marketing department was encountering flat budgets. EMC had been benefitting from Jive communities to support customers since 2003. Over the years, the external communities had become a platform for peer-to-peer interaction, collaboration and customer engagement. However the EMC Chief Marketing Officer and his team realized that there was still plethora of untried potential. The CMO knew that the company had to raise customer engagement if it was planning to go on with generating sound revenue growth with current resources. The goal was to ease customer interaction and establish deeper relationships, It implied turning prospects into clients and clients into brand advocates.
Solution. Consolidation of the multiple external communities into one accessible environment led to the creation of the EMC Community Network (ECN). ECN went live in 2010 and provides a single platform for prospective buyers and customers searching for information, support and resources on EMC products and technology. The users have an access to the knowledge base consisting of articles, blogs, videos, Moreover, they can ask questions, exchange ideas and find experts and users with shared interests.
Results. In the past, EMC held live product launch events across the country. However after implementing ECN, the company replaced these live shows with virtual format delivered through ECN. Thanks to ECN, event participation boosted from several hundred visitors to over 10000 online participants per event. By this, company saved approximately $750000 per year in launch costs. Moreover, customers joining the community created 240% more bookings than those who did not.
Best Buy
Best Buy is a multinational retailer of consumer electronics and entertainment products and services. It operates in the U.S., Canada, Europe, China, and Mexico (Lithium, Official website).
Problem. Best Buy is one of the leading electronics retailers in the world. But it had the problem of engaging target audience, providing reliable support and building advocacy among customers. It also wanted to collaborate across channels in an expandable and manageable way.
Solution. In 2008, the company launched the new Lithium-powered Best Buy Community. Thanks to the community, Customers can engage in conversations with other customers and also with Best Buy's advocates. Best Buy also started blogs about lifestyle and electronics topics. These interactions are supposed to connect customers with knowledgeable experts who can give them assistance with their queries and support with their technology experience.
Results. In average, 600000 customers visit the community and post 20000 messages. The success of the Best Buy Community has encouraged the company to new steps. Presently it runs 4 communities with the new one about mobile devices.
TechSmith
TechSmith is a global leader in developing screen recording and video editing software for Windows and MacOS. It also licenses them to corporations, small and medium enterprises, educational institutions and government agencies.
Problem. The initial goal of launching a client community was finding a more contemporary way of collecting product feedback.
Solution. TechSmith launched Get Satisfaction-powered client community. TechSmith interacts with the customer base in agile development process. The users can ask questions, report problems, suggest ideas and co-create with the company. When TechSmith releases new product, it provokes new conversations in the community. It is because customers face challenges using it. The community allows the company to gather more detailed information from customers in a faster way which becomes a source of product improvement.
Results. TechSmith observed multiple community effects. First is gathering specific product insights. Second is reduction of product testing costs, thanks to the feedback which saves thousands of dollars. Third, knowledge base of frequently asked questions constantly grows and covers approximately 14000 topics. As for the business results, the company saved up to $500000 in product testing costs.
NAASF
The North American Association of Subway® Franchisees unites Subway® restaurant owners. They interact and share information via the community forum, town hall meetings, educational webinars, etc. The purpose of the association is advocating for the needs of the small business owners and sharing news and information within NAASF. It helps Subway restaurant owners succeed in their work every day.
Problem. Franchisees seek communication with each other and sharing resources and best practices. However they do not always want franchisors to manage those conversations. NAASF member have regular town hall meetings where they can talk literally about everything concerning their business. However NAASF recognized needs of its franchisee members to cooperate in a private medium that would be easy to operate and quick to engage into. An online forum where members could speak about problems in real time was the best solution which would be of huge benefit for members.
Solution. NAASF launched Higher Logic-powered online client community platform. Higher Logic extracted member data from the current NAASF database and synchronized with the management software. After launching the community in 2015, NAASF set a goal to attract franchisee members into the community. It conducted educational webinars for members about the advantages, registration process and how to use the community.
Results. As of 2016, the community had 6690 total members and contained a total of 1015 discussions, which is an average of 85 conversations per month. Total unique authors compose 14.5% of community members. Member participation rate is estimated as 83%.
SAP Hybris
SAP Hybris is a computer software company producing software for digital commerce. As they mostly work for the technology heads, they create multichannel e-commerce and product content management software (SAP Hybris, Official website).
Problem. SAP Hybris wanted to build a commercial online community. It would be a place where users could interact in Q&A format, get recognized for contributions and acquire good user experience. Moreover, SAP Hybris wanted to simplify the moderation process of content posted to the community.
Solution. SAP Hybris implemented AnswerHub in 2014, as it was capable to handily integrate existing business tools and provide all the features mentioned above.
Results. In 2015, 7300 new members joined the community, with 600 new members visiting AnswerHub every month. 83% of the community consisted of external users. Moreover, SAP Hybris achieved progressive moderation and control, so only quality contributions are visible to the community. SAP Hybris also made navigation around the community much easier by segmenting the content.
Two important engagement metrics for the community managers are number of questions asked and time to answer. In 2015, 7400 questions were made with 56% answered. Two days was an average time to respond and community had 1200 Best Answers. All of these indicates high engagement and decreased support volume.
Mutavie
Mutavie is the life insurance subsidiary of MACIF, a major mutual insurance company in France. It delivers life insurance products and manages a portfolio of more than 21 billion euros for more than million subscribers.
Problem. The company wanted to modernize the 10-year-old main website. However as it was initially created without the support of a content management tool, redesigning it was quite an effortful task. Additionally, the customer portal was integrated with the website. However it was using different technology and maintained by a different team. The objective of modernization of the website was set by Mutavie to be able to offer secure transactional services to its customers.
Solution. After modernization which took a few months' work, the Mutavie website had a new interface with sections about product information, savings simulators, and company and financial news. Additionally, the customer portal enabled members to independently control account status, update personal data, contact an advisor, and make different kinds of financial transactions.
Results. The Mutavie's new website has become more visited with over 300000 regular members. In less than a year, the number of subscribers has grown twice. The website has 7000 unique visits/a day the majority of which are subscribers carrying out various financial transactions regarding to insurance.
Offering a complete digital experience is at the core of Mutavie's accomplishment. Earlier, many of these actions were done offline and required human interventions and much paper bureaucracy. Now via its online service, Mutavie has advanced its operational efficiency and cut the associated costs. All these are antecedents to increase the market share for Mutavie.
As a result of discussing six case studies, the major trend can easily be identified: launching a client community delivers plenty of important benefits and advantages to the company. It includes but not limited to creation of centralized knowledge base, reduced associate, support and other costs, higher customer engagement and participation, etc. As the next step of the research, it would be consistent to acknowledge emerging factors when implementing a client community which affect a company's value.
2.2 Client communities' factors affecting companies' performance
Content analysis is utilized as the method for analyzing qualitative data. The main objective of the present content analysis is to reveal certain categories of factors which emerge when implementing client communities and which affect companies' performance. The sample for the analysis consists of 107 case studies (also so-called customer stories and customer success stories) of online client communities' launch. Those case studies were selected from the multiple providers of collaboration and communication solutions for enterprises - Jive Software, Lithium, Get Satisfaction, Higher Logic, AnswerHub, eXo, and inSided. Only case studies describing implementation of external communities and extranet were selected for the research, as the paper focuses on communities aiming at clients and customers.
Enterprises in case studies for which client communities were launched come from various industries: telecommunications, retail, consumer electronics, financial services and banking, IT services, computer software and hardware, air transportation, education, healthcare, professional associations, logistics, etc.
From 107 case studies, client communities' factors that directly affect companies' performance and their business value are extracted for each company and presented in the Appendix 1.
The Appendix 1 shows that, in some case studies, companies' representatives indicated exclusive factors which emerged while using client community and which affected companies' effectiveness (such as “doubled productivity” at Telstra or “greater brand affinity” at Autodesk). However, majority of factors presented in the table can be classified into categories as their mentioning recurs in many case studies. Thus, the following section of the paper presents these recurring factors, sorted into specific categories, and frequency of their mentioning within the case studies sample.
2.3 Client community factors derived from content analysis
After gathering the case studies and analyzing them, factors were classified into categories with corresponding frequency distribution of their mentioning in the cases.
Categories into which the factors are classified were formulated relying on multiple research papers: Franklin et al. (2014), Holland and Baker (2001), and Cothrel (2000). Those papers attempted to identify varieties and indicators that measure online community strength.
Articles review led to formulation of the following categories:
1. Increased number of participants and visitors
2. Higher customer satisfaction
3. Increased sales and revenue growth
4. Better usability (online community must be easy to use)
5. Better information quality (i.e. information accuracy, timeliness, usefulness, completeness and customized information presentation)
6. Higher member loyalty (i.e. participation in community operations and communication with other members)
7. Large share of user-generated content
8. Improved response time and better customer support and interaction
9. Simpler moderation
10. Reduced costs
Fig. 1 - Categories of client community strength factors
The top-three leading categories in terms of frequency are: higher member loyalty (63), improved response time and better customer support and interaction (56) and reduced costs (29). Reduced costs include reduction in support and service costs: for instance, a company needs no new hires to manage community or customer complaints/support tickets decreased.
Better information quality (22) includes, among other things, regular digests prepared by companies and sent out to clients; some digests are characterized by high functionality (e.g. “easy access to answers” at Protech Associates, Inc. (case #59) and “connecting administrators and members” at Dynamic Communities, Inc. (case #63)).
The fact of mentioning “reduced costs” category 29 times is quite encouraging for the research, because we suppose that one of the results of implementation of a client community for a company is gaining cost savings and generating revenue.
Conclusions from the case studies and content analysis
As an outcome of analyzing case studies, a significant observation arises that no company in the sample indicated any adverse result after client community implementation. Both small and big enterprises, profit and non-profit organizations point out solely on affirmative factors that emerged in client communities.
Results of the content analysis of 107 case studies consist of eleven categories of client community factors affecting companies' performance. Those categories can be noted as areas of improvement for enterprises that do not have a client community. “Higher member loyalty”, “improved response time and better customer support and interaction” and “reduced costs” are the most frequently mentioned categories among the case studies and “simpler moderation” being the least frequently mentioned factor.
Based on the results of the content analysis, Twitter pages of five telecommunication companies from the case studies sample having client communities and five telecommunication companies without client communities are analyzed in the next chapter of the paper. The purpose of the analysis is calculation of the Janis-Fadner Coefficient of Imbalance.
3. Comparison of telecommunications companies which have and do not have online client communities
3.1 Research methodology
For this research phase, from the sample of 107 case studies, companies from the telecommunications industry were chosen, as companies from this industry are one of the most represented in the sample. Although the most represented industry in the sample is software, the software companies focus on developing variety of its kinds - web, marketing, information, etc. - and this would complicate analytical comparison for which this section is dedicated to. Whereas telecommunications companies produce comparable products and services, such as cellular communication, mobile internet, SIM cards, and television services.
There are 15 telecommunications companies in the case studies sample, however only 5 of them were selected for the analytical comparison. The reason for this is that the companies were also selected by existence of active and regularly updated Twitter page. Part of the companies' Twitter pages had last Tweets published two months, six months and even a year and a half ago, and they were rejected for the analytical comparison. Among companies which have active and regularly updated Twitter pages, additional selection was made by the reason of language barrier. For instance, Twitter pages of “Jawwy” UAE telecom company and “KPN” Dutch telecom company have user replies written entirely in the domestic languages. As the author is not proficient in none of the mentioned languages, such companies were also rejected. Thus, five selected telecommunications companies which have online client communities are Telstra (Australia), StarHub (Singapore), Optus (Australia), Rogers (Canada), and Sky (United Kingdom).
Twitter pages of five telecom companies with online client communities are compared with Twitter pages of five telecom companies which do not have firm-sponsored online client communities. Those companies are Yota (Russia), Tele2 (Russia), AirTel India, Vodafone India, MTNL (India).
The purpose of this research phase is to analyze user replies in Twitter pages of total 10 companies (5 with and 5 without firm-sponsored client community) for the period from 12 April 2018 to 12 May 2018 and calculate Janis-Fadner Coefficient of Imbalance. In order to calculate it, user replies are sorted into favorable, unfavorable, neutral and non-relevant content.
Calculation of the Janis-Fadner Coefficient of Imbalance consists of finding the following values:
f = number of favorable user replies
u = number of unfavorable user replies
n = number of neutral user replies
N = number of non-relevant user replies
Relevant content equals the sum of favorable, unfavorable and neutral user replies:
Total content equals the sum of relevant content and number of non-relevant user replies:
When f>u the imbalance is favorable and the Coefficient is given by Cf.
When f<u the imbalance is unfavorable and the Coefficient is given by Cu.
These two formulas may be used as a Coefficient of Imbalance, which expresses quantitatively the imbalance of any communication with respect to the topic or symbol under investigation (Janis and Fadner, 1943).
We propose that telecom companies which have online client communities have less user complaints on Twitter, than telecom companies which do not have online client communities. Thus, we make the following hypotheses:
Hypothesis 1. Coefficient of Imbalance for telecommunications companies with client communities less increases in negative direction than for telecommunications companies without client communities.
Hypothesis 2. Implemented client communities of the telecommunications companies increase companies' value.
3.2 Success of the telecommunications industry companies which have online client communities
The Hypothesis 1 considers that if a telecom company has a client community, its Coefficient of Imbalance less increases in negative direction than if a telecom company does not have a client community.
When analyzing Twitter pages of the telecom companies with and without client communities, user replies were classified into favorable, unfavorable, neutral and non-relevant content. It has been observed that in all of the ten companies, unfavorable user replies prevail over favorable ones. This leads to using the formula for calculating the Coefficient of Unfavorable Imbalance:
Thus, calculation of the Coefficient for both groups of telecommunications companies can be seen from the tables below.
Table 4 - Coefficient of Imbalance for the telecom companies with client communities
|
Company name |
f |
u |
n |
N |
r |
t |
C of Imbalance |
||
|
Telstra |
13 |
96 |
35 |
0 |
144 |
144 |
f<u |
Cu = -0,384259 |
|
|
StarHub |
1 |
6 |
56 |
4 |
63 |
67 |
f<u |
Cu = -0,007107 |
|
|
Optus |
11 |
112 |
36 |
23 |
159 |
182 |
f<u |
Cu = -0,390904 |
|
|
Rogers |
20 |
164 |
61 |
4 |
245 |
249 |
f<u |
Cu = -0,387115 |
|
|
Sky |
18 |
102 |
59 |
11 |
179 |
190 |
f<u |
Cu = -0,251925 |
Table 5 - Coefficient of Imbalance for the telecom companies without client communities
|
Company name |
f |
u |
n |
N |
r |
t |
C of Imbalance |
||
|
Yota |
16 |
39 |
36 |
55 |
91 |
146 |
f<u |
Cu = -0,067514 |
|
|
Tele2 |
5 |
51 |
29 |
0 |
85 |
85 |
f<u |
Cu = -0,324705 |
|
|
AirTel India |
0 |
115 |
21 |
0 |
136 |
136 |
f<u |
Cu = -0,715019 |
|
|
Vodafone India |
4 |
124 |
20 |
1 |
148 |
149 |
f<u |
Cu = -0,674768 |
|
|
MTNL |
6 |
34 |
12 |
6 |
52 |
58 |
f<u |
Cu = -0,315649 |
For companies with client communities (Table 4), the least value of the Coefficient of Imbalance is Cu = -0,390904. Whilst for companies without client communities (Table 5), the least value of the Coefficient of Imbalance is Cu = -0,715019.
Moreover, 4 out of 5 companies with client communities have Coefficient of Imbalance within the small interval (-0,4; -0,24), whereas among companies without client communities such coefficient proximity is not observed.
In order to make the conclusion about the hypothesis proposed, arithmetical means of Coefficient for both groups of companies are calculated. The following is the calculation of arithmetical mean of Coefficient of Imbalance of 5 telecom companies with client communities.
Below is the calculation of arithmetical mean of Coefficient of Imbalance of 5 telecom companies without client communities.
Thus, the Hypothesis 1 is proved, and it is possible to propose that Coefficient of Imbalance for telecom companies with client communities less increases in negative direction than for telecom companies without client communities.
The Hypothesis 2 considers the relationship between implementation of an online client community and a company's value. In this research, a company's stock price dynamics for the last 10 years is selected as a company's value indicator. Starting from the telecom companies with client communities, Telstra launched its Twitter page in July 2009 and observed the stock price decline. Subsequently when it launched Lithium-powered online community the stock price was stably growing till February 2015. As for the StarHub, after launching the client community in 2012, the company experienced sharp rise in the stock price till May 2013. Optus also implemented own client community in 2012 and the stock price increases since then. After implementing the Lithium-powered online community, Sky observes the stock price growth with only one sharp drop in 2016.
However, not all companies with client communities observed stock price growth right after implementing client communities. Rogers launched Lithium-powered client community in 2014 and only since the beginning of 2016 the stock price started increasing and grows with certain fluctuations. Implementation of the client community can be among the factors affecting the Rogers' stock price growth.
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