Development of an analytical framework for the implementation of Social Listening

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Hochschule für Angewandte

Wissenschaften Hamburg

University of Applied Sciences

Fachbereich: Wirtschaft und Soziales

Studiengang: International Management and Foreign Trade (B.A.)

Bachelor Thesis

„Development of an analytical framework for the

implementation of Social Listening”

Vorgelegt von: Marlen Vehlow

2018344

1. Prüfer: Prof. Dr. Annette Corves

2. Prüfer: Mag. Johannes Fiegenbaum

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List of tables

Table 1: Overview definitions of Social Media Monitoring in researches ... 4

Table 2: Criteria and sub-criteria for the evaluation of alternatives ... 22

Table 3: Examples for weighing criteria with sub-criteria ... 24

Table 4: Potential result of scoring model using criteria categories ... 25

Table 5: Potential result of scoring model for several alternatives without using categories ... 25

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List of abbreviations

API Application Programming Interface B2B Business-to-Business

B2C Business-to-Consumer BI Business Intelligence

BVDW Bundesverband Digitale Wirtschaft CRM Customer Relationship Management DB Deutsche Bahn

EA Expert A EB Expert B

eWoM Electronic Word of Mouth HR Human Resources

KPI Key Performance Indicators NewMR New Market Research PR Public Relations

SEO Search Engine Optimization SMBC Social Media Balanced Scorecard SME Small and medium-sized Enterprises SMI Social Media Intelligence

SMM Social Media Monitoring SMR Social Media Research SL Social Listening

UGC User Generated Content

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Abstract

This paper aims at contributing to the long-lasting discussion on the profitability of Social Media. It offers an analytical framework on the implementation of Social Listening for companies based on different findings in literature and in practice. The framework intents to equip brands with know-how about existing opportunities and thereby support them to make a profound decision towards a successful investment.

In order to evaluate existing listening solutions with regard to their suitability for brands this paper introduces an individualized scoring concept. It shows different options currently existing on the market and thereby preselects the alternatives to be evaluated and scored as well as lists their advantages and disadvantages without offering a list of current providers because plenty of other sources have covered this issue.

The concept allows for qualitative criteria and facilitates their quantification. It can be understood as an approach towards a Social Media strategy without raising a claim of completeness or general validity. To the contrary, the concept needs to be adjusted to the needs of each individual company.

The target audience consists of executive boards as well as managers of marketing, products and innovation, customer relations, sales and distribution, corporate communication, IT, research & development and human resources who are planning the implemenation of such solutions or want to thoroughly acquaint themselves with this topic. The long list of potential target groups illustrates the need to discuss Social Listening tools in all corporate divisions.

Keywords: thesis, Social Listening, Social Media Monitoring, implementation

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1 Introduction

Companies still face difficulties adjusting to new media and the sheer variety of possibil-ities that come with it. Specifically the analysis of the overwhelmingly amount of data present brands with new challenges which are being discussed in the context of big data. (Lütters & Egger, 2013, p. 34)

An example of the opportunities that exist today can be illustrated by the recent devel-opment of IBM’s Watson™ User Modeling service. Watson operates as a personality profiler which IBM states can analyze anyone’s personality based on a text. This text could be extracted from a twitter stream or a weblog, basically any text written by an individual and accessible for IBM’s Application Programming Interface (API). The service will output a score based on the "Big 5" personality traits which are: openness to experi-ence, conscientiousness, extraversion, agreeableness and neuroticism. It enables apps to gather insights from different web sources and thereby helps brands to understand customer’s preferences and needs. This could help companies to adapt marketing activ-ities or other consumer oriented activactiv-ities to different personality groups. (IBM, 2015) (Appendix A1)

Simultaneously, if a consumer wants to know more about products and services from commercial suppliers the information is usually usually sought online. The individual would likely end in a Social Media network where detailed descriptions and experience reports of other users can be found. This kind of media information is also referred to as user generated content (UGC). Purchase decisions of customers are more and more based on UGC. As stated above, it also became the new foundation for gathering insights on the buyer decision process for marketers. (Fiege, 2012, p. 64)

Ignoring this data would be fatal since it perfectly matches the market research process. According to Ray Poynter, knowledge based on the analysis of Social Media sources and other web information, the research may even have the potential to replace the implementation of interviews within market research. (Poynter, 2010) in (Lütters & Egger, 2013, p. 34) The descriped development can be summed up by stating “Listening is the new asking”. (Lütters & Egger, 2013, p. 34)

In order to efficiently use this immense amount of voluntarily provided consumer insights and accomplish to be relevant in the eyes and ears of the target audience, brands need to learn to listen first. Nothing is as unstable as consumer preferences which makes it all the more important to find out what they are at any given time.

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Social Media in particular offers a variety of opportunites for brands to listen to their customers. (Kreutzer, et al., 2015, p. 5) Modern technologies can provide companies with the nessassary tools that can gather relevant content from the internet, especially from the social web and analyze it using numerous methods. Selecting one or more of these tools from hundreds of vendors is linked to a sea of difficulties and often resource-intensive. (Kasper, et al., 2010, p. 8) To stay on top of the data this paper provides selected alternatives and criteria for evaluating these alternatives based on individual needs of every brand.

1.1 Objectives

This paper contributes to simplifying the decision making process of selecting the right tool for analyzing content found in the world wide web with a focus on Social Media. By offering an analytical framework the thesis in hand wants to equip companies with know-how about existing services and listening tools as well as strategic recommendations in order to help them decide wheter or not to make investments in the according field. Limitations of the paper include offering a complete list of tools presently available on the market as well as a comparison of concrete software solutions from different providers.

1.2 Ways of investigation

First the issue of a synonymous application of the terms Social Listening and Social Media Monitoring is examined in order to explain the techniques and approaches of the according software solution. Secondly the utilized scoring model will be described and a step-by-step manual for the application of the model will be provided. Different alterna-tives of existing Social Listening tools on the market as well as their advantages and disadvantages will be demonstrated. By illustrating relevant criteria for the implementa-tion of Social Listening the framework submits companies with the necessary tools to make profound strategic decisions. At the end of the process companies should be able to allocate an individual score to each of the alternatives. Included is the proportioned cost of said service. The last part of the paper deals with potential methodical errors of the framework as well as the applicability of the model and according criteria. Moreover alternative and additional strategic recommendations are given followed by a critical as-sessment. Finally implications for theory and practice are summarized.

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2 The concept of Social Listening

Findings in literature as well as in practice show a divergent use of terms for seemingly equivalent processes. Therefore it is questionable if the terms can be used synony-mously. The following chapter examines the current state of the art in research and in practice and provides a definition for both terms.

2.1 Distinct definition of Social Listening

The term “Social Listening” has not been defined and classified in scientific discussions yet. Consequently defining Social Listening and distinguishing it from other terms used in the same context is an essential element of this paper in order to proceed.

Social Listening (SL) was chosen to be the topic of the paper based on the recent devel-opment in the field by several brands such as Sprinklr, Meltwater and Microsoft. (Microsoft, 2014) (Sprinklr, 2015) (Meltwater, 2015) Sprinklr describes their SL service by stating it enables brands to “find, analyze, and engage with conversations or trends across any geography, language, and social network”. The brief description of Microsoft states that their SL service analyzes “what people are saying on Social Media”. (Microsoft, 2015) Whereas Meltwater equates Social Listening with Social Media Moni-toring and further says that at a technical level, Social Listening would be another way of saying “search.” According to Meltwater SL tools extract insights from conversations which can be found on Social Media. (Meltwater, 2015). They also consider it “one of the most important business intelligence developments in recent history”. (Meltwater, 2015) The actual scope of the service offered can vary from brand to brand but will be dis-cussed at another point in this paper.

Social Listening compared to other terms used within the same context seems to be something that anyone can understand by intuition which made the term particularly in-teresting to this work. However, it has been pointed out that the fact it is such a basic language poses an inherent risk. The fact that people think they understand the term intuitively amplifies the confusion of what Social Listening can really accomplish. Never-theless findings in literature – although referring to the same process – did use different wordings for Social Listening. Only ten years old, the market for Social Media Listening is still in its infancy. (Smith, 2014) (Expert A, 2014) (Hofmann, 2014, p. 162)

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There is a variety of terms regarding listening and analyzing content from the social web. (Lütters & Egger, 2013, p. 35) Among others Social Media Measurement, Web Monitor-ing, Social Media Analysis (Eckenhofer, et al., 2014, p. 67) Social Media-Research (SMR), Social Business Intelligence (Social BI), Social Media-Intelligence/Insight (SMI), New Market Research (NewMR) and Social Media-Monitoring (SMM) are used in the same context. (Lütters & Egger, 2013, p. 35) The latter seems to be the most prominent one of the before mentioned examples.

2.2 Distinct definition of Social Media Monitoring

Although there are a lot more academic sources about Social Media Monitoring, re-searchers that have worked on this concept have experienced difficulties describing the term as well. Nevertheless, for further examination it is advisable to research on SMM rather than SL and examine if it is accurate to equate both terms. Various definitions by organizations and authors exist and can vary widely. (Eckenhofer, et al., 2014, p. 67). (Weiber & Wolf, 2014, p. 44)

Table 1: Overview definitions of Social Media Monitoring in researches

Reference Properties Data Sources

(BVDW e.V., 2014, pp. 68, 80) Observation,

Analysis unstructured, texts, qualitative social web (Kollmann, 2013, p. 197) success

measurement own social activities, quantitative (Eckenhofer, et al., 2014, pp. 67-68) Collection UGC, own, external activities,

quali-tative Blogs, Forums, Social Media

(Lüdtke, 2014, p. 16) Analysis, acquisition Online conversations, qualitative

(Fiege, 2012, p. 64) Observation online opinions Blogs, social networks,

fo-rums, websites (Etzel, 2014, p. 75) monitoring,

observation activities Social Media

(Steffen, 2014, p. 98) analysis qualitative content

(Wagenführer, 2012, p. 203) analysis consumer opinions and engage-ment, big data, qualitative and quantitative, trends

social web

(Schreiter, 2014, p. 68) listening, management, evaluation

topics, content, trends social overlay

(König & Gügi, 2014, pp. 424-425) observation,

analy-sis UGC social networks, discussion forums, weblogs & blogging services

(Kreutzer, et al., 2015, p. 214) observation,

analy-sis UGC, qualitative Social Media (forums, blogs, networks) (Kasper, et al., 2010, pp. 7-8) Identification,

ob-servation, analysis UGC Including but not limited to Social Media/social web (platforms, wikis, forums, blogs, social networks) Source: Own presentation

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Two main indicators can be drawn from existing research. First, several sources suggest that one has to distinguish between different data sets that are chosen according to the definition. Second, researchers provide different definitions of Social Media Monitoring based on the sources that are analyzed with the according IT-tools. Regarding the data sets it is stated that SMM is being used to measure the success and reach of Social Media activities using Key Performance Indicators (KPIs) (Kollmann, 2013, p. 197) oth-ers clearly isolate SMM from quantitative analysis and emphasize the importance of gain-ing qualitative data. (Kreutzer, et al., 2015, p. 214). Thus, many researchers differentiate between Social Media Monitoring and Social Media Analytics or Social Media Control-ling. Distinguishing the terms is crucial because different measurements are used for both techniques. (BVDW e.V., 2014, p. 68) (Fiege, 2012, p. 64)

Also the term UGC is mentioned frequently but in practice it seems as if tools do not differentiate between UGC and content generated by professionals. Depending on the software, results can be filtered by sources, such as blogs or news. (Eckenhofer, et al., 2014, p. 68)

Referring to the second indicator the words suggests that the data analyzed stems ex-clusively from Social Media sources. We must ask if this rather intuitive definition proves to be accurate in practice. For this purpose, we must look at the term "Social Media." The results of several interviews with experts in the field showed that Social Media is defined as a form of online communication in new channels which engage their users to comment and share different multimedia content primarily in social networks or plat-forms. (Höller, 2013, p. 73) As a result researchers have discussed if the broad interpre-tation of Social Media Monitoring and a more fitting term such as web monitoring. In fact, several sources consider web monitoring the more accurate expression since it suggests that the IT-tools are not restricted to Social Media. At the same time it is stated that the expansion to other internet sources such as blogs and social networks and its increas-ingly fast development made it inevitable to include those channels. Consequently the term Social Media Monitoring is given preference to. (Fiege, 2012, p. 64) (Kasper, et al., 2010, p. 8) Clearly there is no consensus on the interpretation of the term. However, there are several points that can be considered as a common aspect. The consistent basic principle of all applications is the systematic observation, collection and analysis of data gained from conversations in weblogs, forums or Social Media. In practice the examined sources vary widely and additional steps might be taken, such as structuring the data through categorizing or assignment of meta-data like author names or media type with Social Media Monitoring tools. (BVDW e.V., 2014, p. 68)

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2.3 Social Media Monitoring and Social Listening in

comparison

2.3.1 Interviews on both terms and their usage in practice

It has been pointed out that no consensus is achieved so far on neither of the topics. However, explanations for both terms have been provided in chapter 2.1 and 2.2 so that a comparison of both terms can be further examined. In order to gather a direct insight on the usage of either one or the other term in practice two experts on the field have been interviewed.

Since the research topic is rather complex and as mentioned earlier in the paper scientific research has not yet offered clear definitions, qualitative methods are particularly suita-ble. To gain insights in the practical application of Social Listening as well as the utiliza-tion of the coherent terms two qualitative interviews have been conducted.

The interviewees are experts in the field of Social Media Monitoring and Social Listening. They work for brands offering professional Social Listening tools along with other Social Media analysis services brought together on a platform. The findings have been anony-mized due to aspects of research ethics based on suggestions from research literature. (Gläser & Laudel, 2009, p. 279) in (Zollner, 2013, p. 264) The following part will examine the results with a focus on qualitative statements.

The assessed information is not supposed to be statistically representative which is why expert interviews are a good measure. Interviewees had the chance to contribute infor-mation on the topic that they considered important, potentially exceeding the questions. Qualitative interviews can be conducted in various ways. Generally two forms can be distinguished: standardized and non-standardized interviews with or without a guideline. In this case both interviewees received questions in beforehand, so they were able to prepare for the interview. The interviews provide a subjective insight on the practical application of Social Media Monitoring and listening tools. For further analysis one inter-view has been recorded and transcribed, the other interinter-views were conducted via email and a summary of the answers can be found in the survey. The transcription was followed by further analysis in which information not relevant to the initial research topic was being filtered. In a next step corresponding and contradictory information of all the interviews has been emphasized and analyzed in order to identify the content which contributes to the research topic.

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On one side, the aim of the interviews were to gather more detailed information on the difference between the terms Social Listening and Social Media Monitoring. On the other, the interview was also aimed at gathering information on the conduction and potential target group of analysis tools.

On the topic of Social Listening Expert A (EA) pointed out that it provides a “holistic view of what people are saying across all social platforms.” EA also stated that Social Listen-ing can enable brands to quantify formerly not quantifiable aspects like brand perception. It has been emphasized that Social Listening contradictory to SMM does not usually lead to immediate action. As an important factor EA identified the knowledge about actions and conversations in the social web beyond a brand’s own Social Media channels in order to be able to analyze competitors. (Expert A, 2014)

According to EA, the difference between Social Media Monitoring and Social Listening exists. EA explains it by using a practical example: It has been stated that Social Media Monitoring requires a community manager who monitors the feeds of a brand in real time, takes care of responding to fans and thereby remains “on the front lines of commu-nication”. (Expert A, 2014) Whereas SL is considered to be of more use on a long-term basis, referring to strategic planning and purposes. Interview partner Expert B (EB) holds the opinion that both terms can be distinguished in theory but in practice both terms are used synonymously. This theory is supported by other sources. (Steffen, 2014, p. 98) EB agrees to the effect that Social Media Monitoring seems to be more analytic than Social Listening. To EB, Social Listening enables brands to listen to clients as well as prospects in order to gain insights benefiting several departments. “EA highlights that many people think they understand what Social Listening means because it is a very basic language. But to EA there still is a lot of confusion on how Social Listening is con-ducted and what it can actually measure. It has to be distinguished from social analytics which measures social presence in terms of community size, engagement & reach. These measures cannot be conducted by a Social Listening tool. (Expert A, 2014) (Expert B, 2015)

2.3.2 Comparison of both terms by other resources

The BVDW distinguishes Social Media Monitoring from Analytics by pointing out that SMM primarily deals with unstructured data like comments and posts in blogs or social networks whereas analytics deal with likes, shares and other quantifiable data which is in direct contravention to what has been said by one of the experts. (Expert B, 2015)

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The authors of “Appearance and Reality of Social Media Monitoring” put the definition of the term in relation to a time frame regarding the stage of a company’s involvement in Social Media, i.e. Start Phase, Prelaunch Phase, and Rollout-Phase. Within this concept it has been stated that a first step for companies towards social business is aiming at listening and watching conversations in Social Media. In their opinion the actual assess-ment of performance is not of interest since there are no activities at this point. This would confirm the proposition of earlier findings that Social Listening does not include performance measures. At the same time the statement implies that measuring perfor-mance becomes relevant as soon as a brand is socially active which would be contra-dictory to the findings (Eckenhofer, et al., 2014, pp. 69-70) Whereas companies offering the service of Social Listening refer to SMM as a monitoring action of a brand’s feeds, which postulates that a brand is already active in Social Media. (Expert A, 2014) (Expert B, 2015)

2.3.3 Conclusions

Overall it can be stated that Social Media Monitoring and Social Listening are closely linked. Using both terms synonymously has neither a negative nor a positive impact since definitions for each individual terms vary as well. It is more important to distinguish both terms from Social Media analytics. Whereas Social Media analytics measure the perfor-mance of Facebook fan pages or YouTube channels with the number of fans, shares or likes Social Media Monitoring or listening tools deal with unstructured data like texts. Since divergent measures are needed for both analysis they cannot be used synony-mously. (BVDW e.V., 2014, p. 68) However, Social Media Monitoring is used more com-monly than Social Listening. A research using various SL tools supported this theory (see Appendix A2). But there is general need for both terms to be defined in the future since there still is a lot of confusion on how Social Listening or Social Media Monitoring is conducted and what they can actually measure. Social Listening in specific has to be distinguished from social analytics which measures social presence in terms of commu-nity size, engagement and reach. These measures cannot be conducted by a Social Listening tool. They might however be offered within a platform service that offers both measures. (Expert A, 2014)

Examining mentions and conversations in the social web has led to more results for the term Social Media Monitoring than Social Listening. The range of definitions for both

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terms coincide at so many points that it can be considered to be accurate to use either one or the other term within the same context. This statement was reaffirmed by several assertions of brands and experts in the field who claimed that both terms already are used synonymously in practice. In the course of this paper the term Social Listening will be used synonymously for Social Media Monitoring.

2.4 How it works

There are different approaches on the extent to which Social Listening tools gather dis-cussions. Some tools use Social Media warehouses which store discussions on servers at their disposal and thereby enable the attribution of time frames and analysis based on historic data. Simultaneously, the analysis is limited to the historic data saved on these servers. Others access data via open internet search engines in order to find relevant content like Social Media posts. There are technical and contractual parameters that limit results of search engines. Consequently, there is a tendency to use content aggregators to find and assemble data from several Social Media sources which allows the vendor to concentrate on the analysis and visualization services. At the same time adding new sources in a timely manner can be problematic and take a lot of resources. (Steffen, 2014, p. 99)

The basic principle of Social Listening can be described in four steps. First the data needs to be collected. The sources for this collection have been discussed in detail in the second chapter. The more sources are considered the broader the database which will increase the relevance of the analysis. In a next step the data has to be processed. (König & Gügi, 2014, p. 425) Invalid or redundant data needs to be eliminated. At the same time meta-data such as the date or name of the author is extracted, saved and tags are added which will make the following analysis easier and faster. (Fiege, 2012, p. 68) Subsequently, the data is analyzed. Insights and correlations of the underlying data are gained with different techniques such as filtering, grouping and condensing. Finally the results are visualized so that users can conceive them promptly. (König & Gügi, 2014, p. 425)

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2.5 Why Social Listening

The real challenge for brands today is understanding the needs of their customers and finding a way to respond to them in real-time. Therefore listening to conversations hap-pening online regarding the company, brand or products is essential. Monitoring the online “buzz” can help companies to become less vulnerable and gain a strong and pos-itive reputation which will emphasize opportunities on the long run. (Barnes & Jacobsen, 2013, p. 157)

A study from 2012 showed that 90 % of the surveyed companies do not actively conduct Social-Media-Monitoring and almost all of the surveyed brands stated that they have not set KPIs to evaluate the achievement of their objectives. (Kreutzer, 2014, p. 199) A dif-ferent study showed a slightly higher engagement of organizations in monitoring their “buzz”, depending on the sector they are in, revealing that the non-profit sector seems to be very active in Social Listening. (Barnes & Jacobsen, 2013, p. 152) This illustrates that many brands are not prepared for the challenge that Social Media presents them with. It further shows why many companies still experience no success through Social Media. (Kreutzer, 2014, p. 199) This begs the question why companies are still resistant to a change towards Social Listening respectively Social Media Monitoring. The absence of monitoring measures seems to be the result of the complexity of a successful SL pro-ject. Opinions also differ on the question what SMM can achieve. (Elgün & Karla, 2013, p. 51) The following chapter deals with opportunities and risks on the implementation of Social Listening and thereby wants to illustrate the importance of discussing the issue.

2.6 Opportunities and fields of application

One key takeaway from researchers is the advantage of being able to control a brand’s reputation by monitoring conversations about companies. But the major potential of So-cial Listening tools lies within avoiding the risks that occur if brands choose to ignore online conversations and thereby what is being said about them. The consequences of failing to acknowledge the importance of this issue can be fatal. Potential risks range from crisis like the uncontrollable distribution of negative content regarding products or the company itself, public trust or even a decline in shares. Non-actions can further lead to increasingly dissatisfied customers and revenue losses. (Barnes & Jacobsen, 2013, p. 150)

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Taking monitoring seriously can function as an early warning system in reputation man-agement. To ensure the success of the early warning system, Social Media channels are continuously browsed for current discussions which could have a potentially negative influence on the company and promptly informs about the findings. Given this timely advantage brands can react to relevant conversations in real-time. Another important aspect resulting from time advantage is the early detection of trends. Often discussions take place in Social Media long before they are raised in conventional mass media. Equipped with this information brands discover insights on expectations and require-ments of future products or services. (Elgün & Karla, 2013, pp. 52, 54) It is important to remember that Social Media provides companies with the opportunity to listen to the largest focus group in the world. (Smith, 2014, p. 2) And it has another significant ad-vantage compared to conventional market research approaches. Users provide all of the information voluntarily which eliminates most of the systematic contortions otherwise found in research results. Data collected with Social Listening largely meets criteria re-garding reliability and validity. (Wagenführer, 2012, p. 87)

The immediate reaction to what is also referred to as electronic Word of Mouth (eWoM) has in once case verifiably enables brands working in the e-commerce sales sector to influence product sales significantly. (Barnes & Jacobsen, 2013, p. 150) In addition So-cial Listening facilitates the opportunity to identify opinion leaders and key influencer. These are characterized by being active communicators and having an established net-work with other users. As a consequence they have a rather big influence on current topics and conversations in Social Media which makes them significantly important to companies and should be involved in upcoming plans of the brand. (Elgün & Karla, 2013, p. 52) (Hauptmann, 2014, p. 78)

A study by Millward Brown „BrandZTM_{Top 100 Most Valuable Global Brands 2012“}

sup-ports this thesis by stating they have found a correlation between brand equity as well as its increase and the online “buzz” as well as number of online fans of the regarding brand. The study examined B2C as well as B2B brands. According to this study “Buzz means money” meaning that Social Media can be vital to the development of brands. (Barrowcliff, 2012, p. 14) in (Kreutzer, et al., 2015, p. 220) Other fields of application are risk management, competition and market analysis, campaign monitoring and customer relationship management (CRM) as well as Human Resource Management (HR).

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2.7 Risks and barriers

There are several risks that companies have to face when implementing Social Listening tools. First there is the risk of an immense resource expenditure regarding budget, per-sonnel and time. An exact calculation is not always possible and depends strongly on the chosen implementation strategy. Since there is a vast number of vendors for existing Social Listening tools there is also a good chance of choosing an ineffective alternative resulting in higher costs and potentially worse results.

An example for an inefficient alternative would also result from untrained or incompetent personnel regarding the use of Social Listening tools. (Elgün & Karla, 2013, p. 53) (Barnes & Jacobsen, 2013, pp. 155-156) If the monitoring is not carried out adequately the goals of Social Listening cannot be met. Relevant discussions or conversations in the social web might be considered in a timely manner which can result in a loss of power on the issue. Unprofessional behavior through untrained personnel might even aggra-vate the situation and in a worst case scenario result in a reputational catastrophes cur-rently referred to as “shitstorms”. Disasters like these could have been prevented with the efficient use of monitoring tools. (Elgün & Karla, 2013, p. 54) (Weinberg & Grässel, 2014, p. 116) There are several risks regarding the collected and analyzed data. Apart from the before mentioned risk of choosing faulty sources, the quality of the data also depends on the users providing it. Even though some platforms offer valuation systems about users the provided information can still be falsified and manipulated. It is difficult to validate the authenticity and quality of the data which makes it inevitable to scrutinize the results. In addition all Social Listening tools are based on automated software algo-rithms which illustrates the need for human interpretation at least to a part.

Furthermore companies have to consider privacy protection laws which means they can-not access all the information existing on Social Media platforms such as Facebook. Facebook in specific has certain guidelines that won’t allow companies to access all user data. (Elgün & Karla, 2013, p. 55) These privacy settings can be seen as a barrier to the quality and efficiency of data collected with Social Listening tools. (Eckenhofer, et al., 2014, p. 68) Finally the analysis of unstructured data, such as text or audio content is prone to errors because the software is still in development. Another example for this issue is the feature of sentiment analysis which examines the tonality of comments or conversations. At the moment, the identification of sarcasm or irony still is very difficult. (Elgün & Karla, 2013, p. 52)

Other difficulties that companies have to overcome in order to successfully implement Social Listening are of internal nature. Brands might be faced with cultural resistance within their company. The controlling department might have difficulty accepting Social

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Media as a source for the measurement of success. Other staff might not be familiar with the use of Social Media and fear the change. Implementing Social Listening will affect all departments. People in leadership positions in the company might fear the loss of control over corporate communications and other functions. It has to be clear how results are handled, by whom and which tasks are delegated to certain employees. Depending on the structure of the company there might be a risk of non-compliance with a micro-man-agement culture.

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3 Strategic recommendations for the decision of

implementing Social Listening

Several approaches have been considered for the development of a model on the im-plementation of Social Listening. One approach consisted of a two-by-two matrix with the following dimensions: The company’s potential for exploitation of Social Listening and the industry-specific risks and opportunities. The first aspect indicated to which ex-tent the examined company can exploit all the advantages that Social Listening offers. One of these aspects investigated the level to which market research is currently used in the company. The second indicator can be linked to which extent the company pres-ently uses Social Media on a strategic level. The third indicator conceivable considered the amount of data that can be raised by the company for research purposes. Regarding the second axis, the trade-off situation between risks and opportunities was illustrated. The two elements aimed at portraying all relevant indicators to be considered before implementing an according listening software.

In each of the resulting four strategic windows consequences for the strategic behavior of enterprises are discussed. Suggestions included the acquirement of software tools, the creation of a new department as well as the outsourcing of all functions related to Social Listening. Furthermore, it was suggested to reconsider the implementation. The strategic recommendations would have been suggested in the beginning of the paper. Their practicability and potential flaws would have been examined over the course of the paper.

Within a short amount of time the model turned out to be problematic in different ways. For one, the axes needed to be more specified in order to be practicable. At the same time, defining the axes more precisely would have limited the indicators illustrated within them and thereby the initial goals of the model would have only been met insufficiently. The second axis was especially difficult to improve. The approach was to map all relevant indicators relevant for the issue. Potential other dimension were company size, relevance of customer satisfaction for or growth rate of the company. All of the before mentioned suggested dimensions did not meet the initial criteria of the model. Finally another ap-proach was taken in order to address the issue.

The key question before deciding on the general implementation of Social Listening tools discusses the goals and strategy which are pursued in the social web as well as which issues are supposed to be answered by with the application of according solutions. Ex-perts suggest to be honest with regard to investments since listening software needs to be integrated in all marketing efforts especially social marketing. A variety of listening

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tools are set at an increased price level which has to be considered as well. Another aspect that has to be considered is the staff operating the tools in the future and the staff benefitting from the outcome. Tools have to be chosen based on the needs of the person operating them. This implies the potential training or recruitment of according personnel as well as an ongoing monitoring of the extent to which the listening solutions are used, integrated into the company as well as its distribution throughout the business. (Expert A, 2014) Other experts suggest to consider the extent to which brands are presently mentioned in the social web. It is being said that certain businesses like financial institu-tions, insurance companies, transportation as well as mobile communication providers should be more concerned than others. (Expert B, 2015) To sum it up the main factors to be considered are goals, trained staff, budget and target group.

In order to make an educated guess about the best Social Listening tool solution the utilization of scoring models is suggested. (Nufer & Graf, 2012, pp. 10-11) Scoring-mod-els employ point rating systems. The overall result equates the sum of various partial results and is further explained in the following chapter. (Nufer & Graf, 2012, p. 9)

3.1 The basic concept and structure of the proposed

scoring-model

The overall questions need to be broken down into smaller parts first. (Fiege, 2012, p. 64) It has been suggested to carry out scoring actions by a selected a group of company stakeholders relevant to the investment decision. Furthermore it is recommended to choose one of the attending members to function as a moderator or project coordinator. This position ensures the maximum fragmentation of the initial decision every time the scoring model offers alternative options. Thereby certain preferences of attendees do not influence the scoring of one alternative in favor for the other. (Kühnapfel, 2013, p. 88) Today, there are no findings in literature on the subject of the composition of such a group. However, it is useful to choose decision makers for this task such as CFO and CEO as well as directors in charge of marketing, product innovation, client management or human resources so that the most relevant perspectives on the issue are covered. Clearly, the composition of the team can influence the result significantly. Team mem-bers therefore have to be chosen wisely and should be assembled to equal parts so that there is no predominant interest group.

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With the scoring model decision alternatives can be compared based on qualitative fac-tors and appraisals. Scoring models are utilized for decision problems which are not quantifiable. It has been stated that the majority of daily operations in businesses fulfill this criterion. The basic principle of the model is the fragmentation of an issue into single criteria which can be assessed separately. Thereby the comparison of the alternatives can be conducted without preconception. The partial results (for the fragmented criteria) will then be consolidated to an overall result, the score, which will provide an objective decision based on a systematic holistic view of the problem. (Kühnapfel, 2013, p. 87) The first step of a scoring model is to point out the decision problem. In the previous chapters it became clear that there is a general need for every company willing to stay competitive to implement Social Listening tools. So the relevant decision issue lies within deciding on the right tool. This step is usually followed by the definition of goals and assessing their significance. Potential goals that have to be achieved with implementing a Social Listening tool can be found in chapter 2.5. Findings in literature acknowledged CRM, public relations (PR) and reputation management as well as achieving a compet-itive advantage by analyzing competitors and the market as important goals and thereby identifying trends at an early stage. (Hofmann, 2014, p. 161) Additionally, these goals have to be met at low risks, which can be found under chapter 2.6 such as data quality, internal cultural resistance or a wrong assignment of resources. It is important for every company to evaluate goals according to their needs since it will significantly influence the resulting decision on criteria. The goal definition has to be precise and at the same time leave enough room for a creative solution. Brands have to find the right balance. (Kühnapfel, 2013, p. 88) In a next step alternatives have to be selected.

3.2 Selected alternatives for the scoring model decision

process

The alternatives have to fulfill three preconditions: comparability, transitivity and reflex-ivity. First the alternatives have to be comparable to each other. Furthermore they have to fit into a consistent ranking system, which means if 1 is better than 2, and 2 is better than 3, than one has to be better than 3. Finally if 1 and 2 achieve the same score they have to be equally useful. The preselected alternatives will be described in the following part.

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There is a comprehensive choice of products on the market. The Social Listening solu-tions vary significantly in terms of functionality und service (Eckenhofer, et al., 2014, p. 71) Therefore it is important to accumulate this vast amount of existing solutions into categories.

Some authors suggest the possibility to choose a solution based on the combination of available resources in the company and the sources that can be examined with the ac-cording tools. One of the resulting approaches is to implement in-house monitoring with open source tools. This solution scans a limited number of weblogs and other platforms. While saving financial resources open source tools require extensive labor hours to op-erate and administrate the software which should not be underestimated. Therefore this approach is recommended for cases in which only a limited number of weblogs or plat-forms is monitored. In cases where the whole, publically accessible Social Media sector is supposed to be monitored it is suggested to outsource the search process of keywords such as the brand name, certain products or campaigns. Thereby delicate content can be identified in a timely manner. (Fiege, 2012, pp. 65-66) The resulting approach of the author is the categorization of monitoring tools into three groups being: technology pro-viders, monitoring service providers and full-service providers. The ladder offers an anal-ysis and consulting regarding monitoring solutions besides offering the software itself. (Fiege, 2012, p. 74)

Other researchers use slightly different approaches to categorize Social Listening tools and services on the market. For example, providers can be categorized based on their service portfolio. Distinctions can be made between full-service agencies, monitoring so-lutions and software. According to this categorization, full-service agencies not only an-alyze clients’ data but also consult on strategic issues. They have access to various tools and provide recommendations for actions. Monitoring solutions on the other hand are platform services which provide an individualized analysis of gathered data with an ac-cording user interface. Counseling is only provided on a minimum level. Whereas plain listening software can be further divided in free-of-charge and fee-based tools which offer the monitoring of conversations in the social web including sentiment and frequency analysis but without further counseling. (Weiber & Wolf, 2014, p. 48) These solutions often target specific media like Twitter or Facebook and thereby often cover only one source. (Etzel, 2014, p. 76) Another framework divided the solutions into similar catego-ries namely self-service, full-service and hybrid. The ladder describes a self-service tool with optional counseling services and can be compared to the before mentioned moni-toring software. (Eckenhofer, et al., 2014, pp. 71-72)

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Other findings in literature suggest software solutions in the context of the level to which a monitoring or listening solution is already utilized within a company. It is suggested not to look for the online buzz of a brand, its own products and participants in the beginning, also referred to as the pre-launch phase. To the contrary, it is stated that brands should gather general information on the market and potential competitors first. At this stage an analysis of local conditions can take place with free of charge or less expensive tools. Considering test accounts of more comprehensive solutions would be another option. (Eckenhofer, et al., 2014, pp. 69-70) Others do suggest to conduct a first analysis of the own brand to see if, where and when people are talking about it. This will help brands to get an idea of the sources that have to be covered by a professional software at a later stage. (Etzel, 2014, p. 76) The following so-called rollout-phase is defined as a stage in which companies rely on automated monitoring tools to evaluate the outcome of com-munication measures. It is recommended to have an expert accompanying this phase due to an improved judgment on the results based on past experiences. (Eckenhofer, et al., 2014, p. 70) On a day-to-day basis it is important to consider that results of one solution might be divergent from those of others due to different sources used for the analysis and configuration as well as visualization options. (Schreiter, 2014, p. 149) The various categories differ in their level of support during the setup and during the analysis along with the sources they cover, functionality and price. (Eckenhofer, et al., 2014, pp. 71-72) (Fritzsche, 2012)

From a demander’s perspective the categorization can be made according to the specific goals that are supposed to be covered by the solution or which issues are supposed to be solved. For example, the establishment of a Social Media newsroom or reputation management differs widely from a brand audit or market research assignment only aim-ing at a short time frame. At the same time measuraim-ing the performance of Social Media campaign requires different strengths than the integration of a CRM system. (Fiege, 2012, pp. 75-76)

Furthermore, vendors can stand out through different professional backgrounds. Whereas some are experts on the field of market research or media consulting others are equipped with know-how about Search Engine Optimization (SEO). (Kasper, et al., 2010, p. 11) (Fiege, 2012, p. 74) Additionally it has to be considered that the number of consulting services have outgrown the number of IT solutions. This emphasizes the need to categorize solutions based on the level of service they provide which is supported by several other sources. (Kasper, et al., 2010, p. 11) (Lütters & Egger, 2013, p. 40) As a result the alternatives to be evaluated for each company are as follows: stand-alone software, full-service solutions or a mix of a software with optional counseling on analyz-ing issues.

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By choosing a stand-alone software clients select scanned sources as well as keywords and search strings without external advice which imposes a risk if the assigned staff is untrained. The client also has to ensure the quality of the resulting data.

Training periods and the amount of working hours are particularly high since competen-cies have to be build up over time. Consequently, clients using stand-alone software are agencies rather than individual companies.

Many of the full-service solutions do not own technologies for Social Listening but more so takeover data by other software providers. Often the field of expertise lies within the selection of sources, assistance with the formulation and application of search strings as well as data quality. Additionally full-service vendors provide clients with monthly reports. Clients receive access to a dashboard showing the current status regarding share-of-voice, sentiment or trends.

Full-service providers offer an additional deep analysis and consulting services for cli-ents. It is common that service providers in this category specialize in one area and are experts on their field. Globally operating media agencies, highly specialized market and opinion researchers or providers from the Business Intelligence area are only some of the examples. There is only a small number of one-stop providers covering all key Social Media Monitoring processes. (Fiege, 2012, pp. 74-75)

3.3 Determining criteria for the scoring model

The next step of the scoring concept is to develop relevant criteria in order to evaluate the alternatives developed in chapter 3.2. Several indicators are provided by findings in literature. The aim of this chapter is not to give a complete list of all factors but to provide an overview of relevant indicators that determine whether the evaluated alternative is a good fit for the company.

The scope of the scoring model does not include the significant criteria of costs. The various listening solutions differ widely regarding costs. Price models range from free-of-charge open source tools to highly expensive full-service providers with complicated pric-ing models and minimum contract durations. (Schreiter, 2014, p. 156) Overall consider-ing the costs within the scorconsider-ing model would basically make it redundant due to clear weighing preferences of price characteristics. The results of the scoring model would be biased and therefore fail to meet the goal of the scoring concept. The issue is addressed again in the last part of the paper which will discuss methodical errors as well as critically assess the results.

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The number of criteria is questionable but researchers suggest to choose a set of ten to twenty criterions. Thereby a sufficient comprehension for the fragmentation of the prob-lem will be ensured and at the same time criteria will be compact enough for efficient proceedings. A higher amount of criteria will make individual criterions seem less signif-icant. Hence, the evaluation of individual criterions will be more superficial.

A general requirement of criteria is completeness. All relevant aspects for evaluating the issue should be covered. One of the most common mistakes is the selection of overlap-ping criteria which can lead to a distortion of the result. Additionally scores have to be assignable to every criterion by every team member. It is difficult to rate a criterion if there is a lack in factual or technical background. This risk can be avoided by assembling a committee of highly competent team members with regard to the issue. Furthermore criteria have to be relevant and reproducible making sure the criterion will remain rele-vant to an analysis taken at a later point in time. (Kühnapfel, 2013, p. 90)

The first criterion that is emphasized consistently in literature is the set of sources that are scanned by the software. Sources usually refer to websites that offer data such as Twitter. Within this criteria sub-criteria can be created. Thereby the before mentioned methodical error of potentially overlapping criteria can be avoided. Simultaneously, a subjective evaluation of highly relevant criteria is prevented.

In order to evaluate a set of sources quantity and quality have to be considered as they influence the results of the analysis significantly. However, the mere quantity of sources does not give evidence on the suitability of the source. Moreover, it has to be ensured that the set of sources is updated on a regular basis to ensure that it remains relevant and available. A positive outcome can be achieved if the listening solution offers the opportunity to add individual sources either by the user or by the software providing com-pany.

Furthermore, the set of sources should be evaluated based on the access it provides to historic data stored and used for analysis. At the same time available information needs to be updated on a regular basis. Listening solutions offer different approaches regarding updates. Some sources have to be updated manually by editors whereas others are updated automatically using web crawlers or search engines. The ladder is usually per-formed with search requests, or queries, which isolate relevant content from the vast amount of information available. In one instance, specific knowledge regarding the for-mulation of queries is needed, in order to use them efficiently and find exactly the infor-mation the company is looking for.

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In another instance hand many high profile vendors limit the number of search requests according to a price model so that poorly formulated queries can become very costly. Typical queries use Boolean operators (e.g. AND, OR etc.) (Kasper, et al., 2010, p. 22) Users should be able to determine the frequency with which sources are scanned for results. (Kasper, et al., 2010, pp. 19-20) Other relevant factors to be considered within the context of data sources are the availability of data with limited access and the possi-bilities to focus on certain regions or languages. Data with limited access refers to certain licenses a service provider has available that allow for search requests in non-public social networks. (Kasper, et al., 2010, p. 21) This is a delicate issue as data protection laws differ from country to country and the application of the law depends on the location of the servers.

A criterion which can support the quality level as well as the isolation of relevant data would be the relevance evaluation of the data. Terms like impact or influence are used synonymously which show how many people will presumably read the post, or blog or other content. Typically KPIs from publically accessible providers are used, such as Google Page Rank. (Kasper, et al., 2010, pp. 22-30) (Schreiter, 2014, p. 156)

Other determining factors are the different types of analysis provided by the software. The collection and analysis of data specific to an individual are essential for every listen-ing solution. Since personal details in Social Media still provide rather unreliable infor-mation, gender, location and age can also be added in a second step. Gathered data from listening tools can be enriched with meta-data from existing data bases of the com-pany. The action of accumulating data to create a comprehensive view on individual users is also referred to as profiling. (Kasper, et al., 2010, p. 23) Another important fea-ture of listening software is the sentiment detection which determines whether content can be regarded as positive, negative or neutral towards the analyzed topic. (Kasper, et al., 2010, p. 24) Finally frequency analysis measures the “buzz” of a topic or a brand and is usually provided by every vendor or software offering listening tools. The “buzz” pro-vides information on the number of articles, posts etc. in which the requested term is mentioned within a certain time frame. (Kasper, et al., 2010, p. 23) Filters can refine search results and thereby allow for further analysis on certain parts of the results like content within a certain time frame or a certain region. (Kasper, et al., 2010, p. 25) Key-word extractions show certain Key-words commonly occurring along with the examined topic or brand. The user will be provided with a thematic overview in a short amount of time. Common visualization methods of this analysis are tag clouds (see Appendix A4) which arrange words occurring repeatedly within a cloud in different sizes according to their mentions. (Kasper, et al., 2010, pp. 26-27)

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The listening solution can be evaluated based on other visualization methods they offer. Pie charts, bar charts or time-lines should be minimum requirements of analyzing tools.

Table 2: Criteria and sub-criteria for the evaluation of alternatives

Criteria Sub-Criteria Examples

Set of sources Quantity Quality Updates,

adding individual sources By user, provider Historic data

Data updates Through crawlers, search engines or editors Queries service

Scan frequency

Data with limited access Languages & location Relevance evaluation Analysis Profiling

Sentiment In different languages Frequency

Filters

Keyword extraction Visualization

User friendliness Dashboard availabilty Indiviudalized Interface Intuitive handling

Workflow Number of users

Integration Import, export, reports Alerts

Engagement Brand awareness

Data safety Cloud computing or hosting

Source: Own presentation

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Tag clouds and other visualization methods can be found in dashboards. Furthermore these user interfaces, also referred to as cockpits, should be able to show the most rel-evant KPIs and user comments, blog posts or other content. Besides providing the user with an easy to use and intuitive handling another important feature is the individual con-figuration of the modules in each dashboard. (Schreiter, 2014, p. 158) Finally, the work-flow functions play a key role as they guarantee or limit the smooth integration of Social Media listening. (Kasper, et al., 2010, p. 28) Various user profiles should be available and adjustable to the individual needs of every person operating the software and the simultaneous work with the listening solution by several users should be considered. The workflow or integration options also refer to the interface and cross-linking abilities of tools. Individualized import, export and report capabilities are important eligibility criteria to be considered. (Schreiter, 2014, p. 158) One example which proved to be successful is the alert function which immediately informs the user about predefined events such as the discovery of new relevant content or passing a threshold. A feature which becomes more popular is the so-called engagement. This function allows for immediate reaction to Social Media content from within the software. Thereby the application can be used for certain measures and actions of CRM. (Kasper, et al., 2010, p. 29)

Another potentially relevant factor is the brand awareness of the product. If staff recog-nizes the name of the tool this might lead to a higher acceptance and therefore less internal barriers when implementing the tool. (Schreiter, 2014, p. 158)

Regarding safety, companies can choose between cloud products and hosting the data on owned or rented servers. Using cloud options can mean to give up the rights of the provided data to the platform owner. Depending on the sensitivity of the data and per-sonal goals a cloud option can have mixed results. (Schreiter, 2014, pp. 156-157) Further examples for a detailed examination of monitoring tools can be found in the evaluation framework developed by Helene Fritzsche. (Fritzsche, 2012)

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3.4 The calculation of the score

The weight of each criterion is based on the importance it is assigned by the scoring company in regard to the contribution to the problem solution. Each of the criterions gets assigned certain percentage points which have to add up to exactly 100 %. It has been suggested to weigh the criteria by assigning them to categories first and thereby simplify the rating with adequate scores. (Kühnapfel, 2014, p. 10) The higher the percentage the higher the significance of the criterion.

Table 3: Examples for weighing criteria with sub-criteria

Criteria Sub-Criteria Weight Group Weight

Category A Criterion A1 40% 40% Criterion A2 10% Criterion A3 50% Category B Criterion B1 40% 40% Criterion B2 60% Category C Criterion C1 100% 20% Sum 100%

Source: Own presentation, based on (Kühnapfel, 2013, p. 93)

A fitting scale has to be selected before assigning the scores. The scale has a significant influence on the result and therefore has to be chosen with great care. (Kühnapfel, 2014, p. 10) Scales have to meet certain criteria. First, they have to be unambiguous and prac-ticable or common such as a school grade system or ten point scales. (Kühnapfel, 2013, p. 95) In the following part the ten point scale will be described as it is the most accurate option for this purpose. The advantages of ten point scales are that there is no need to convert them and anyone can understand them intuitively. At the same time they offer big enough intervals for accurate evaluation without leaving too much room for subjective grading. Other scales along with advantages and disadvantages are listed by Kühnapfel. (Kühnapfel, 2013, pp. 95-98) Furthermore ten point scales are of practicable and precise nature. The limitation to 10 points as opposed to for example 100 points simplifies the application and increases the clarity. Intervals can be set individually. However it is strongly recommended to specify a range for awarding points or in other words provide a legend for each point.

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A logical example for awarding the points would be as follows: 0 points means the crite-rion is not met, 1 – 3 points means that the critecrite-rion is met insufficiently or with substantial deficiencies, 4 – 6 points means the criterion is met but with deficiencies, 7-9 points means the criterion is met to a satisfying extent and a score of 10 points indicates that the criterion is met completely. After each group member assigned scores to the criteria the weight for each criterion is multiplied with the according score. Finally the weighted scores of each criterion are summed up to a final score. These steps have to be repeated for every alternative tool so that the resulting final scores can be compared and thereby a ranking of the alternative options can take place. (Nufer & Graf, 2012, pp. 10-11) The user should be provided with a final score for each alternative and thereby be able to see which one is suitable for the individual company.

Table 4: Potential result of scoring model using criteria categories

Alternative X

Criteria Sub-Criteria Weight Score Weighted Score Group Score Group Weight Weighted Group Score Category A Criterion A1 40% 3 1,2 2,6 40% 1,04 Criterion A2 10% 4 0,4 Criterion A3 50% 2 1 Category B Criterion B1 40% 7 2,8 5,8 40% 2,32 Criterion B2 60% 5 3 Category C Criterion C1 100% 9 9 9 20% 1,8 Sum 5,16

Table 5: Potential result of scoring model for several alternatives without using categories

Alternative X Alternative Y Alternative Z Criteria Weight Score Weighted

Score Score Weighted Score Score Weighted Score Criterion A1 40% 3 1,2 1 0,4 7 2,8 Criterion A2 10% 4 0,4 7 0,7 5 0,5 Criterion A3 50% 2 1 4 2 3 1,5 Criterion B1 40% 7 2,8 9 3,6 6 2,4 Criterion B2 60% 5 3 10 6 7 4,2 Criterion C1 100% 9 9 4 4 5 5 Sum 17,4 16,7 16,4

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3.5 Potential strategic alternatives

The scoring model described in the previous chapter provides companies with a tool for the evaluation of future investments in Social Listening solutions. Different alternatives found in practice and in research have been provided. The following chapter aims at providing information on alternative strategic recommendations.

Findings suggest companies to create a software solution in-house which is commonly accompanied by immense financial expenditures and only remunerates if there are no existing software solutions on the market that meet the company’s needs. A potential solution to the problem is suggested in bringing the product to the market and gaining a return-on-investment by merchandising it. The authors acknowledge that most organiza-tions decide on groupware offers, which consist of standardized interfaces and can be adjusted to the needs of the according organization. (Schreiter, 2014, pp. 156-157)

Other findings indicate the potential implementation of so-called Command Centers which can fulfill several functions depending on the company and equal an additional make-or-buy decision. (Lütters & Egger, 2013, p. 40). According to the authors some brands use command centers for prestige purposes because they have a futuristic im-age. Others acknowledge them for being valuable instruments for the successful out-come of various departments and teams. A variety of solutions for Command Centers already exists and additional solutions are in the works. Due to significant investments companies should know about advantages and disadvantages as well as limitations of these solutions which are also referred to as Command Center Displays before deciding on an implementation.

Command Centers are described as information displays, which can translate vast amounts of online data into easily understandable factors in real-time. However, more complex sets of interactions have to be performed in order to present the user with vis-ualizations which makes the quality of the analysis software particularly important to the performance of the command centers. The criteria to be met is comparable to the rele-vant characteristics other listening tools. Although the emphasis lies on the adjustability due to the fact that Command Centers are more than just a software. They require im-mense financial resources dedicated to labor, especially before and during the initial setup compared to paid online software solutions which can be changed or canceled within a timely manner. (Brandwatch, 2014, p. 13)

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This includes offering the opportunity for users to switch between the different screens according to the needs of individuals. Other recommended functions are remote con-trolled displays. (Brandwatch, 2014, p. 14) Furthermore, with display solutions compa-nies are provided with the opportunity to connect, display and analyze correlations be-tween Social Media data and other metrics also referred to as social intelligence. Com-mand Centers to a high degree represent an involving and continuously adjusting com-bination of hardware and software. Consequently learning curve effects can be observed and need to be considered. A user-friendly interface can help to prevent mistakes in the beginning. However, the key a successful implantation is a comprehensive customer service. An efficient service also constitutes a significant cost factor. (Brandwatch, 2014, p. 15)

There are several brands which have successfully established Command Centers. The first company to launch such an innovative solution was Gatorade, naming it their “Social Media Mission Control Center”. Shortly after Dell launched its Social Media Listening Center and it was predicted to be a new trend. (Swallow, 2010) In the meantime several brands followed the example such as Heineken, Jaguar/Mindshare, IKEA, MoneyGram and Monster to name only a part. (Brandwatch, 2014)

3.6 Examples, success stories, best practices

Although the field of Social Listening is still very in its infancy there are plenty of out-standing examples on how Social Listening can be leveraged. The U.S.-based banking company Capital One used Social Listening to come up with the name of the hash-tag they used in their new campaign. The selection was based on a word which was mostly used by their target audience. In the course of their research the marketers discovered that people used the word “ka-ching” when talking about certain winning or emotionally connecting moments. In 2012, Capital One successfully re-launched their cash card and tied #kaching in with the initiative. (Expert A, 2014) (Dragon, 2013)

As an example of the more analytic aspect of Social Listening or monitoring tools the 100-year-old cookie company Oreo successfully created an advertisement on twitter which went viral instantly. During the Super Bowl 2013 the audience and players at the stadium experienced a power outage. In less than thirty minutes Oreo managed to react to the event with an image of a highlighted cookie against a dark background with the headline saying: “You can still dunk in the dark.” The image has been retweeted more than 15.000 times within less than one day. Marketing executives and the ad agency