The social innovator : a qualitative study of the use of social media for the innovation of products and services

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The Social

Innovator.

A qualitative study of the use of Social Media for the innovation of products and services

University of Amsterdam M.Sc. Business Administration - Marketing Track

Student Roxanne Markus Student number 10003540

Supervisor ProfessorA. Zerres

Date January 27th_{, 2017}

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This document is written by Roxanne Markus who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Table of Contents

1.

INTRODUCTION

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2.

LITERATURE REVIEW

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2.2. (Online) customer knowledge management 13 2.3. Using online customer knowledge for innovation 18

2.4. Concluding remarks 19

2.5. Research questions 20

3.

METHOD

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3.1. Research design 22

3.2. Research approach 23

3.3. Validity and reliability 26

4.

ANALYSIS

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4.1. The use of online customer knowledge for product innovation 28 4.2. How organizations use online comments for product innovation 34 4.3. The success factors of using online customer knowledge for innovation 40

5.

GENERAL DISCUSSION

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5.1. The use of online customer knowledge for product innovation 46 5.2. How organizations use online comments for product innovation 47 1.1. The success factors of using online customer knowledge for innovation 48

2.

CONCLUSION

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2.1. Theoretical implications 51

2.2. Managerial implications 52

2.3. Limitations and suggestions for future research 52

REFERENCES

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APPENDIX 1: OVERVIEW OF INTERVIEW PARTICIPANTS

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APPENDIX 2A: INTERVIEW GUIDELINE 1 – ORGANIZATIONS

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APPENDIX 2B: INTERVIEW GUIDELINE 2 – EXPERT ORGANIZATIONS

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APPENDIX 3: INTERVIEW TRANSCRIPTS

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Appendix 3A: R. Van Thoren 60

Appendix 3B: R. Schueler 64

Appendix 3C: K. Van den Broek 70

Appendix 3D: R. Landeweerd 72

Appendix 3E: P. Chaturi 77

Appendix 3F: E. Karel 80

Appendix 3G: M. Dreise 87

Appendix 3H: B. Abrahamse 89

Appendix 3I: T. Siddique 91

Appendix 3J: C. Van Roosmalen 94

Appendix 3K: R. Pioli 97

Appendix 3L: Anonymous 100

Appendix 3M: S. Hesterman 104

Appendix 3N: L. Ronner 107

Appendix 3O: E. Rikken 109

Appendix 3P: H. Voerman 114

Appendix 3Q: J. Van Nimwegen 115

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Abstract

The increasing amount of online word-of-mouth that is being posted on social media platforms potentially contains critical customer comments about brands and products. This potential customer feedback contains knowledge from customers (rather than knowledge about customers, which is often being acquired through traditional market research methods) can especially be a valuable source in the process of product innovation for organizations. Online customer knowledge can be used to identify customer needs, promote new product innovations and to ensure that product innovations will succeed once implemented. As acquiring online customer knowledge seems to be mostly beneficial for

companies, this study aims to provide for a deeper understanding of what would be reasons not to use it and how it can be successfully acquired for the purpose of product innovation. Using a qualitative research design through which 18 in-depth interviews with social media and innovation practitioners were analyzed, this study demonstrates that online customer knowledge is indeed an advantageous source of product innovation. Nevertheless, technology- social media- and online customer knowledge related challenges must be considered when adopting online customer knowledge. Moreover, the content analysis of the interviews resulted in an overview of the main online customer knowledge acquisition tools that can be adopted and the provision of several key success factors for the acquisition of online customer knowledge for product innovation. Doing so, this study has contributed to marketing theory about online word-of-mouth as well as user innovation.

Keywords: online word-of-mouth, customer knowledge, user innovation, innovation process, new

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1. Introduction

Social media enable every individual who has access to the Internet to express their thoughts to a large online audience. For organizations, this means that online word-of-mouth (the information that passes from consumer to consumer online) about their brands or products is publicly available, plentiful and mostly free and easy to access (Sawchuk, 2011). A recent study shows that this is why many organizations seek for ways to make profitable use of the customer knowledge that can be rooted in online comments (Chua & Banerjee, 2013). Consequently, firms deploy online market research methods such as social listening (tracking and monitoring social media content to determine volume and sentiment of online conversations) and netnography (interpretative research of the interactions and experience of customer on social media) to gain knowledge about their customers (Kozinets, 2002; Etlinger, 2011). However, not only does online word-of-mouth contain information about customers, who they are and what they want, it could also contain knowledge from them. Gibber, Leibold and Probst (2002) argue that it is the knowledge from customers, customer

knowledge, that can be especially valuable for organizations as it contains customer experience,

creativity and (dis)satisfaction with products and services. The management of customer knowledge allows firms to share and expand knowledge in collaboration with customers, which could enhance the success in the process of product innovation, because it stimulates joint value creation (Darroch, 2005). Studies have indicated that joint value creation leads to improved products and services that are likely to result in successful innovative products (Andreassen & Streukens, 2009). The customer knowledge that is embedded in online comments, which will be referred to as online customer

knowledge (OCK) in this study, can therefore be an easily accessible source of innovation and could

then serve as a cost-efficient means to reduce the risk that is often paired with the innovation of products (Chesbrough, 2006; Laurssen & Salter 2006). By using OCK in the process of innovation, organizations can transform their customers from passive recipients of products to active contributors of innovation (Schlagwein & Björn-Andersen, 2014).

Understanding how customer knowledge can be acquired from online word-of-mouth seems crucial not only to support practitioners in trying to make optimal use of online customer knowledge,

6 but also to advance word-of-mouth literature. The existing body of literature about the use of online comments by companies is rather understudied. The benefits of customer knowledge combined with the benefits of online word-of-mouth imply that investing in OCK acquisition to increase the success rate of product innovation would be an advantageous strategy to engage in. However, it also raises questions that cannot be answered by the existing literature about OCK. For example, it would be interesting to know why organizations do not acquire OCK in the innovation process. By comparing this to the benefits of OCK acquisition, this would allow scholars and practitioners to evaluate OCK implementation for product innovation as a beneficial strategy. Furthermore, existing literature does not provide an overview of how firms can best acquire and deploy OCK in the process of innovation. This information would be useful for social media and innovation practitioners, as the amount of OCK is increasing and innovation remains an important means for firms to gain competitive advantage.

Therefore, the current study explores why and how organizations acquire customer knowledge from online customer comments for the purpose of product innovation. The aim is thereby to discover what factors contribute to successful acquisition of OCK that leads to product innovation. This study therefore results in an evaluation of the use of OCK in the innovation process and provides an overview of the OCK acquisition methods that practitioners currently use together with their characteristics.

A detailed description of the research questions that this study attempts to answer will be presented in the concluding section of the literature review. Reviewing the literature about current methods of knowledge acquisition for innovation will lead to a deeper understanding of how online knowledge can provide potential additional benefits and thus how it must be studied. Furthermore, a qualitative research design was chosen for the method of data collection and analysis, because of the relatively low amount of prior theory about this topic and because this study aims to explore questions as “why” and “how” the phenomenon of OCK acquisition occurs. This study is aimed at gaining insights about a phenomenon, as opposed to empirically gather data and generalize findings which is the aim of quantitative research. Studies reveal that qualitative research methods are particularly useful for explorative studies such as the current one (Merriam, 1988; Patton,

7 1990). Hence, semi-structured in-depth interviews with 18 social media and innovation practitioners will provide the textual data that will be coded and analyzed in this study.

The aim is therefore not to provide evidence that OCK is indeed a valid source of innovation, but rather provide an interpretive analysis of interviews to evaluate its challenges and benefits. Although many types of innovation can be studied (such as, process innovation, business model innovation), this current paper will focus only on the use of OCK in the process of ‘product innovation’ (which also entails intangible products, services). Moreover, the overview of the OCK acquisition methods that this study results in is not meant to be an exhaustive list of all the possible OCK acquisition methods and their criteria (for this, a larger sample and different research approach would be required), but is to provide an overview of the most commonly used methods by the interviewed practitioners.

Knowing how organizations use online customer comments for innovation will expand the current body of literature about online word-of-mouth, customer knowledge and innovation. The current paper therefore contributes to marketing theory by expanding the knowledge there is about online customer comments and by explaining how they may be used for purposes other than promotion of products. Additionally, this work expands marketing knowledge by explaining how online customer comments and the potential customer knowledge they bring, can lead to optimal results for organizations.

1.1. Thesis Structure

The following chapter (chapter 2) will provide a review of the literature pertaining to innovation, customer knowledge and how it can be used for product innovation. Furthermore, chapter 2 will introduce the research questions that form the foundation of this study and will explain how the study of these questions contributes to the existing body of marketing knowledge. In chapter 3, the

qualitative methods that were used to conduct this study will be justified and explained. This includes the choice for semi-structured in-depth interviews as well as the description of the coding and analysis strategy adopted. Chapter 4 presents the results of the semi-structured interviews with 18 social media and innovation practitioners and provides the answers to the research questions. Chapter 5 will discuss

8 the answers to the research questions and will link the findings of this study to results of prior

marketing and innovation literature. The concluding chapter (chapter 6) describes the contributions that this qualitative study has made and provides suggestions for future research.

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2. Literature Review

Online customer comments can have an important impact on the production of innovative products and services. The factors that lead to the success of this process are yet unknown, but will be explored in the coming study. Before doing so, the following theoretical framework provides an overview of literature about innovation (chapter 2.1). This is to explain what definition of innovation will be used in this study, why it is important to study this concept and how customers (and their knowledge) have the potential to drive product innovation. This chapter also explains why the knowledge from customers is more likely to lead to successful innovations than the knowledge about customers that traditional market research methods explore (chapter 2.2). Furthermore, the following chapter discusses how online word-of-mouth provides for a valuable source of customer knowledge that can be used in the process of product innovation. Therefore, chapter 2.3 also explains the importance of gaining a deeper understanding of this phenomenon by conducting qualitative study. Lastly, this section provides some concluding remarks (in chapter 2.4.) and introduces the research questions that are at the center of the forthcoming study.

2.1. Innovation

The concept of innovation of products has gained a lot of attention from different scholars over the past few years. Up until now, there has not yet been a unifying definition which all these scholars agree on (Baregheh, Rowley & Sambrook, 2009). Because of its many definitions and interpretations, it is important to clarify how the term innovation is used in the current study.

A reappearing factor pertaining to the definition of innovation is that it should include the production of something ‘new’, either new to the world, to a market or to an organization (Schumpeter, 1934; Roberts, 1987; Baregheh, Rowley & Sambrook, 2009). Another factor that is often used in the definition of innovation is that it satisfies a certain customer need and thus creates value (Rickards & Richards, 1985; Roberts, 1987; Crossan & Apaydin, 2010). Because product innovation involves the creation of something ‘new’ which creates customer value, it is often used interchangeably with the concept of New Product Development (NPD) (Urban and Hauser, 1993), this also applies to the current study. One of the first mentions of the term innovation was by Schumpeter

10 (1934). He made the distinction between incremental innovations, which are often less impactful, smaller innovations, and radical innovations which lead to creative disruption, or a new way of specific consumer need. In Schumpeter’s terms, the focus of the current study is on the innovation of new products (and services) in both radical and incremental sense. This definition has been adopted, because customer knowledge can be a potential source for small product improvements (incremental innovations) as well as completely new innovative products (radical innovations).

Although it has promising results, innovation is a complex, expensive, time consuming and risky engagement (Simon, 2009). Despite the fact that numerous new products are introduced every year, the majority of these products end up in failures. For this reason, Tidd, Bessant and Pavitt (2005) argue that innovation is a process that requires careful management. Many authors have attempted to depict the process of product innovation (new product development) (e.g. Cooper, 1990; Tidd Bessant & Pavitt, 2005; Chandra & Neelankavil, 2008). For instance, Chandra and Neelankavil (2008) have modeled the new product development process as depicted in figure 1.

Figure 1- New Product Development process (Chandra & Neelankavil, 2008)

All stages are equally important for the eventual outcome and can be performed in a multitude of orders (Urban & Hauser, 1993). The innovation process models that can be found in extant literature usually consist of a number of overlapping stages. However, a review of the literature clarifies that the innovation process of new products typically passes these four stages as can be seen in figure 2.

11 Figure 2 - Innovation process as adopted in the current study (Sources: Cooper, 1990; Tidd Bessant & Pavitt, 2005; Chandra & Neelankvil, 2008)

‘Ideation’ is the phase in which new ideas are formed. These ideas can come from a variety of sources, such as customers, technology and brainstorming. The selections phase entails the consideration of all the ideas that have been developed in the first phase and selecting those that are eventually chosen to be developed into products and implemented into the market. The development stage includes the prototyping, testing and validating of the selected idea(s). The last stage of implementation is when organizations launching the new product into the market. In each stage, OCK could have a potential impact on the success of the eventual innovative product, however this has not yet been studied in existing innovation or NPD research.

2.1.1. The importance of innovation

Understanding what drives innovation and what would lead to successful innovation is important for organizations aiming to survive and compete in their markets (Crossan & Apaydin, 2010). The author of ‘The Competitive Advantage of Nations’, Michael Porter (1990), argues that innovation is an important enabler of differentiation, and thus an important driver of competitive advantage. The reason why companies innovate is often for this exact reason. Firms want to stay competitive in the dynamic markets in which they reside, and to do so, it is necessary for them to renew their offerings, methods of production or the markets in which they compete (Porter 1990). Moreover, studies have found a positive relationship between innovation and firm performance (Kleinschmidt & Cooper, 1991; Klomp & van Leeuwen, 2001; Calantone, Cavusgil & Zhao, 2002). For example, Kleinschmidt and Cooper (1991) conducted a study of 195 new product cases from 125 industrial firms. They found that the relationship between product innovativeness and commercial success is U-shaped, which means that both incrementally and radically innovative products are more likely to be successful than non-innovative products. In addition, other authors have found that a firm’s commitment to learn from and exchange knowledge combined with its innovation capability leads to enhanced firm

12 innovativeness. This, in turn, positively affects firm performance (Calantone, Cavusgil and Zhao; 2002). Although these studiees was conducted more than 15 years ago, recent studies show that they are still applicable to current organizations (Crossan and Apaydin, 2010; Camisón & Villar-Lopez, 2014). The findings imply that innovation is most likely to occur when organizations exploit and share knowledge and that this will lead to enhanced business value. For this reason, a popular approach is for organizations to use customers in their innovation processes. Recent studies indicate that sharing knowledge with customers, ‘being connected’ to them, allows firms to understand their customers better and enables them to provide solutions that fulfill specific customer needs especially tailored to the customer (Chang & Chen, 2014; Heij, Volberda & Van den Bosch, 2015) and that using customer knowledge in the innovation process seems to be a fruitful strategy for organizations to follow (Cook, 2008; Bilgram, Brem & Voigt, 2008). The use of end users’ knowledge in the process of innovation is often referred to as user innovation, customer-led innovation or

consumer-based innovation, and is one of the main topics of this study.

2.1.2. How customers can be used for innovation

Although it has promising results, innovation is a complex, expensive, time consuming and risky engagement (Simon, 2009). Despite the fact that numerous new products are introduced every year, majority of these products end up in failure. Using customers in the innovation process allows organizations to exploit the numerous voluntary contributions that people make to companies, ranging from informed opinions and subjective word-of-mouth to computing resources (Cook, 2008). User innovations create incredible value for other customers of a firm, and thus for its shareholders as well. Because of the high failure rate of most innovations (Castellion & Markham, 2013), companies are trying to alleviate the lack of user-acceptance by opening their innovation process to customers (Brem, 2008). Although the research stream has gained more attention in the past two decades, ‘user innovation’ is not a new term. Early research streams have explored the important role that users play in the provision of critical inputs to firms, that are necessary to develop and market products that better meet consumer needs (Burns & Stalker, 1961). One of the most active and leading contributor to research about the role of users in innovation is Von Hippel. His studies have found that users can

13 indeed be the sources of innovation, as they do not only help producers to innovate but could be the innovators themselves (Von Hippel, 1986; Von Hippel, 1994). Though von Hippel is one of the most prominent authors of user innovation research, his early studies (on which many other user innovations studies are based) are mostly literature reviews in which the findings he makes are based on his own interpretation and suggestions, rather than confirmation from empirical research. Nevertheless, empirical studies do provide evidence that users are indeed important sources of external knowledge (Chatterji & Fabrizio, 2014; Hienerth, von Hippel & Jensen, 2014). In one recent study von Hippel conducted the first empirical exploration of the relative efficiency of user versus producer innovation (Hienerth, von Hippel & Jensen, 2014). Interestingly, results of this study suggest that user innovations lead to even more significant innovations than producer innovation. These findings imply that innovations that include users are more successful than innovations that do not.

Identifying, inviting and stimulating users to collaborate with organizations to create innovations that cover their specific needs, can be a particularly valuable activity for a firm to engage in. For companies, it is important to have a substantiated understanding of how customers can serve as valuable partners with whom new innovative ideas can be discovered and explored (Gibbert, Leibold & Probst, 2002). A qualitative investigation of how new, online tools can optimize the integration of customers in the process of innovation would provide scholars and practitioners with a deeper understanding this phenomenon.

2.2. (Online) customer knowledge management

Du Plessis (2007) argues that innovation is extremely dependent on the availability of knowledge. In the literature related to innovation, knowledge is often referred to as the element that is inherent to the generation of innovation (Galunic and Rodan, 1988; Grant, 1996). For instance, Cantner, Joel and Schmidt (2011) argue that firms who apply knowledge management achieve higher rates of innovative products success (in terms of higher-than-average shares of turnover) compared to their competitors who do not apply knowledge management. The use of customer knowledge management is an aspect of knowledge management that refers to the management of knowledge from customers,

14 i.e. the knowledge that is resident in customers that contains their creativity, experience and (dis)satisfaction with product (Gibbert, Leibold and Probst, 2002). In contrast to knowledge about customers (here referred to as customer insight), such as their characteristics and preferences, customer knowledge draws on the intelligence of customer. Organizations can make optimal use of the qualities of their customers by focusing on customer knowledge rather than customer insights. Customer knowledge may therefore be especially valuable in the process of innovation as the creation of new value occurs in collaboration with customers, rather than learning from customers and then creating value. Compared to literature about user innovation (for example, Hienerth, von Hippel & Jensen, 2014), literature about customer knowledge focuses on one specific aspect of customers, their knowledge, instead of the individual as a whole. Focusing on customer knowledge, rather than ‘customers’ enables researchers to examine how this one component of a customer can efficiently be acquired. Nevertheless, the current literature does not reveal how this is done. Though there are studies of how knowledge about customers is being retrieved. These methods can also be deployed for the acquisition of customer knowledge. This chapter therefore explains how customer insights and knowledge can be acquired according to existing literature.

2.2.1. Traditional methods for obtaining insights about customers

Organizations that use the customer knowledge for their advantage often have created methods for storing and leveraging the contributions of their users in a way that is profitable for the organization (Cook, 2008). Market research (or marketing research) is the term that is often used to describe the organized effort to gather information about customers. Market research is performed mainly to acquire market intelligence, which includes the information about current and future customer needs, as well as competitive information and trends in the market (Shapiro, 1988). In the contemporary market, it is difficult for firms to survive without investing some amount of time, finances and/or effort into the acquisition of market intelligence. Traditional market research methods therefore are ideal devices to understand customers and their markets. These methods are either categorized as quantitative or qualitative and include surveys, polls, individual and group interviews trend analysis and secondary analysis. Studies have shown that listening to customers is important, because it can

15 lead to higher degrees of product success (Sawchuk, 2011). Characteristic of traditional market research methods is that they are mostly used to retrieve knowledge about customers, i.e. customer insights, but it is also likely that these methods can be used to acquire customer knowledge. This however, has not been confirmed by the previous studies. Because of the advances of the internet, the ability of companies to retrieve information on their customers have been enhanced. These recent digital developments open doors for organizations that aim to find new ways in which information about customers can be retrieved.

2.2.2. Online customer insights

The emergence of the internet enabled an easy way for customers to express their opinions of and experiences with companies and products on what is called social media. Social media is here referred to as computer-mediated technologies that allow creating and sharing in virtual communities and social networks (Kaplan & Haenlein, 2010). Social media make it possible for customers to create, share and view other comments and in so doing enhance the distribution of online word-of-mouth. It has opened up new possibilities for companies to retrieve information about how they are perceived by their customers. Sites such as Facebook, Twitter, Amazon.com and Trip Advisor, have enabled customers to enter virtual communities where they can post reviews and experiences about products and services. Customers often contribute online comments on social media platform to share their experiences, (dis)satisfactions and sometimes even suggestions for improvement to other (potential) customers (Kozinets, 2002). The market research industry has been greatly affected by developments in social media (Patino, Pitta & Quinones, 2012). According to Smithee (2011), ‘social media have changed marketing by shifting the scalability of influence, and the ways in which consumers share, evaluate and choose information’. The market research industry has recognized the importance of social networking and user-generated content. These comments provide organizations with potentially valuable knowledge about customers, but are also means to obtain knowledge from them. As the goal of market research is to obtain a better understating of who customers are and how they perceive a brand, product or service, social media is an ideal lever for such research (Patino, Pitta & Quinones, 2012).

16 For this reason, many organizations have recently aimed their attention to investing in obtaining this information from customers online through methods such as social listening and

netnography. Social listening (or social media monitoring) is a quantitative market research tool that

describes the act of monitoring the numerous comments that people have made about a brand, its products and services or a specific topic on websites, blogs, forums and social networking sites. With social listening, companies use the already existing body of knowledge there exists about customers to understand who they are (i.e. customer demographics analysis), what they do (i.e. customer behavior analysis), whether their comments are positive or negative (i.e. sentiment analysis), what kind of information they present in their comments (i.e. content analysis) and to identify the topics customers are interested in (i.e. trend analysis). Social listening is a great method to quantify a brand or product’s online image and is therefore often used by market researchers, marketing teams, social web agents and sales teams to improve marketing and innovation practices. Moreover, netnography (a fusion of the terms internet and ethnography) is defined by Kozinets (2002) as ‘ethnography adapted to the study of online communities’. It is a qualitative and explorative research approach to analyze consumer dialogue on social media. Like traditional ethnography, netnography is an empathic, observing, naturalistic and unobtrusive means to analyze explicitly verbalized and implicitly existing need- and solution-information about customers. Similar to social listening, netnography researchers use the information that is publicly available on online communities. However, in contrast to social listening, netnography is more about understanding, rather than measuring insights about customers. Netnography is therefore often used to identify and understand the needs and decision influences of relevant online consumer groups so that organizations become more aware of their customers’ needs and behaviors.

2.2.3. Limitations of current market research techniques

The described customer insight generation methods are ideal for measuring a firm’s brand health, to optimize marketing activities, to determine where and how revenue is or can be generated, to determine where and how company expenses can be reduced (Etlinger, 2011). Nevertheless, these market research methods have some limitations. Critics of marketing research techniques argue that

17 these methods seem to be based on an artificial separation of production and consumption (Xie et al., 2008; Firat & Venkatesh, 1995). According to Witell et al. (2010) this means that customers are seen as passive responders to market offerings rather than active participants in the value-creation process. Both social listening and netnography methods are initially designed for the acquisition of publicly available information about customers, rather than the knowledge from customers. Critics therefore argue that it would be beneficial to organizations to replace a passive view of a customer with a more active view in which customers are invited to use their own knowledge and intelligence for the generation of innovative ideas (Gibbert, Leipold & Probst, 2002; Schlagwein & Björn-Andersen, 2014). This could provide companies with new opportunities to create new product innovations with greater customer value, because these products innovations are made in collaboration with the very customers they serve. Identifying, understanding and satisfying the latent needs of a customer or the discovery of new market opportunities is important for firms to gain competitive advantage (Du Plessis, 2007). Using the social listening and netnography then for the acquisition of online customer knowledge would be advantageous for customers. Nevertheless, how these methods can be deployed has not yet been examined in research.

The devices that would constitute the generation of customer knowledge from online word-of-mouth expressions on social media would be interesting for scholars and practitioners. By discussing online comment practices with the practitioners that already make use of them, a deeper understanding of how organizations currently acquire customer knowledge online could be developed. For this reason, the current study aims to explain how the customer knowledge that resides in online comments (referred to as online customer knowledge or OCK in this study) is currently used for innovation. The reason why this topic is currently ill-represented in literature, may be because it may not be as advantageous for firms as it seems. Therefore, this study also aims to give answers to the question of why acquiring customer knowledge from social media may not be a beneficial decision. First, however, the reasons why organizations should invest in online customer knowledge acquisition are discussed.

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2.3. Using online customer knowledge for innovation

Using customer knowledge for innovation would not only harness the voice of the customer, but take it beyond traditional market research by integrating users as problems solvers in various phases of the innovation process (Bilgram, Brem & Voigt, 2008). Online user innovation would draw on the premises of the wisdom of the crowd (O’Reilly, 2005). This concept explains how dotcom businesses such as online communities and blogs constantly retrieve more and more data about people’s everyday lives. In discussion with each other, community member’s aggregative and collective opinion would result in better quality of insights than that of a single expert. In online social spaces such as the review section of the website Amazon.com, customers are able to build on each other’s comments to discuss with each other the ideas that would make a specific product better. Organizations that catch up on these discussions would have valuable insights into the needs and wants of their online user innovators and could use these insights to improve existing products (incremental innovations) or create completely new ones (radical innovations). A brief examination of two case studies in literature demonstrates how online customer knowledge benefits organizations.

2.3.1. Benefits and challenges of using online customer knowledge for innovation

An example of a company that uses online word-of-mouth for new ideas is LEGO Ideas. Lego Ideas is a website started by Cuuso and the Lego Group in 2008 on which users are able to contribute by submitting their ideas for new Lego products (Schlagwein & Björn-Andersen, 2014). Once an idea has gained 10,000 support votes from other users on the site within a span of 3 months, the idea will be reviewed and evaluated by LEGO staff. After the idea has been accepted by LEGO staff it will be developed and released by LEGO. Users who have their project produce will then receive 1% royalty of the product’s net sales In the same year, 2008, Starbucks also launched a community website named My Starbucks Idea (Chua & Banerjee, 2013). In addition to ideas for new products, Starbucks allowed customers to provide feedback on many Starbucks-related services such as the products, stores and Starbucks staff. Similar to LEGO ideas, other users get to vote on the suggestions made on the My Starbucks Idea website and the ideas with the most votes make it to the Starbucks review stage. Starbucks keeps every user updated about the process of their idea review stage: “under

19 review:, “reviewed”, “coming soon” and “launched”. The success of My Starbucks Idea became evident when the website was nominated as the most embracing social media application in the 2008 Forrester Groundswell Awards (Chua & Banerjee, 2013). Within the two months after its launch, the website received over 41 thousand contributions by customers. LEGO ideas and My Starbucks idea demonstrate that social media is a powerful tool for finding online user innovators and for the creation of innovative ideas.

The examples of LEGO ideas and My Starbuck idea show that using the online knowledge from customers provides organizations with many benefits. Using online user innovation is a means to transform customers from passive recipients of products and services into active contributors of innovation. Therefore, customer knowledge is efficiently utilized. A high user involvement and the fact that customers’ knowledge is being acknowledged by the organizations could have a positive impact on the loyalty of customers (Chua & Banerjee, 2013). Moreover, user-generated content can create a lot of buzz, especially in a community where users need to support an idea as often as 10,000 times before it is deemed as ‘successful’. This creates natural marketing promotion for the innovation once it is produced. Lastly, the product innovation will have proven to be successful even before it has entered the market. The numerous support votes it has gained from other users reveal that the innovation fulfills a wide-ranging customer need.

2.4. Concluding remarks

The previous literature review, reveals that OCK acquisition provides benefits to organizations that make it an attractive means to deploy in the process of product innovation, although possible disadvantages remain unexplored. Studies have indicated that there currently are three main methods of OCK acquisition, which are presented in figure 2. These three methods can be divided in methods that use passive OCK (which already exists online) and active OCK (which has been acquired through activation of customers.

20 The relative low amount of academic literature about the use of OCK implies that the practice has not received attention from scholars and practitioners in the field. It is likely that more methods can be deployed for the acquisition of OCK for product innovation. Further, apart from the classification of passive and active online knowledge, there might also be other criteria upon which the choice of OCK acquisition can be based. Because the review of the literature raises questions about how OCK can (best) be deployed for product innovation, this study is attempts to fill this gap in literature.

2.5. Research questions

Chapter 2.3.1. explained the benefits of using OCK in the process of product innovation, by examining two examples. The benefits demonstrate that OCK can bring even more value to organizations than the product innovation it potentially results in (e.g. free promotion, higher customer loyalty and evaluation of product innovations by the market). However, by examining the reasons why OCK would not be a good strategy to achieve product innovation, it will be possible for scholars and practitioners to evaluate OCK as a prospective source for innovation. Therefore, research question one is as follows:

1. Why do companies not systematically acquire customer knowledge from online customer comments for product innovation?

If organizations do make use of customer knowledge, then it will be interesting to understand how they do so. In the previous chapter, some of the methods for gathering online customer comments

Us e o f o n lin e cu sto me r kn o w le d ge fo r i n n o vatio n Passive online customer knowledge Social intelligence Netnography Active online cutomer

knowledge Online communities

Figure 3 - How online customer knowledge can be used for product innovation according to current literature

21 have been identified, such as social listening and netnography. Exploring the ways in which

organizations use online customer comments for product innovation will grant scholars and

practitioners with an even deeper understanding of the ways in which OCK can best be implemented in the innovation process. Therefore research question 2 is:

2. How do companies systematically acquire customer knowledge from online customer comments for product innovation?

The aim of research question 2 is to explore the additional methods organizations use to acquire OCK when their goal is to use that knowledge for product innovation. It is expected that some methods will require higher customer engagement than other methods and that some methods are more likely to yield the best results if they are deployed in a particular stage of the innovation process. Exploring how practitioners have utilized OCK in the past, will give us an overview of the ways in which OCK can be acquired for product innovation and to explore criteria upon which organizations may choose the right OCK acquisition methods.

Furthermore, this study aims to discover what practitioners believe to be the factors that have helped them or could help them to successfully acquire and utilize OCK for product innovation. Research question 3 reads:

3. What are the potential success factors of acquiring customer knowledge from online customer

comments for product innovation?

‘Success factors’, in this respect, are divided into two categories: 1) success in the process of obtaining those online comments that contain customer knowledge or 2) success in the process of turning OCK into profitable product innovations. Knowing what practices can lead to the best results is interesting for practitioners who consider to invest in OCK acquisition. Like research questions 1 and 2, research question 3 is an explorative one and relies on historical information of how OCK has actually been used. For this reason, the current study uses a qualitative research design in with which the experiences of practitioners will be explored.

22

3. Method

3.1. Research design

The aim of this study is to gain a deeper understanding of how organizations use the customer knowledge that is embedded in online comments for product innovation and the success factors of this practice. This research is therefore explorative in nature and uses a qualitative research design. Qualitative research is especially suitable for questions like these, because it enables the researcher to explain phenomena for which there is a small body of existing literature (Given, 2008). In contrast to quantitative research, where the systematic empirical investigation of observable phenomena can validate mathematical models, theories or hypotheses, qualitative research collects data in order to describe information and discover new themes and patterns (Denzin & Lincoln, 2011). Critics of qualitative research methods argue that replication of a qualitative studies is difficult, because it often heavily relies on human subjects and it may lack consistency and reliability (Given, 2008). In order to minimize the limitations of qualitative research, the following sections explains in detail how a structural research approach was used for this research.

Common qualitative research methods include archival data, observation, classical ethnography, case studies and in-depth interviews. The latter method will be used for the purpose of this study, because it allows the researcher to address the knowledge from practitioners who have experienced particular phenomena.

3.1.1. Semi-structured in-depth interviews

Interviews are particularly useful methods for exploring new research areas. In-depth interviews enable the researcher to discover new insights that can then be validated or justified with quantitative research methods. A single case study would be another way to approach this research as case studies are designed to investigate a phenomenon within its real-life context (Patton, 2005). However, case studies often include only one case which may be specific to a company, situation, or person. In depth-interviews allow the researcher to interview a sample of participants ranging from a multitude of companies, this enhances the generalizability of the findings and allows for the discovery of multiple different possible themes (Merriam, 1988). Because this study aims to provide for an

23 exhaustive overview of the reasons for how OCK is used, semi-structured in-depth interviews held with practitioners from a multitude of organizations seem to be a proper research approach. Semi-structured interviews, as opposed to Semi-structured or unSemi-structured interviews are centered around a mixed framework of general themes and pre-established question, which can be adapted in the context of individual situations (Given, 2008). This leaves the researcher with the freedom to omit certain questions, mix their order or to ask standard questions in different a way, depending on the context. This method has been selected as a sole method of inquiry, because it suffices in discovering and exploring a variety of different themes, as is the objective of this study.

3.2. Research approach

A diverse sample ensures that a wide range of insights can be explored, which suits the purpose of this study. Participants were selected on the basis of their occupation: they had to be involved with either social media strategy (digital media, or online media) or with innovation or new product development. This was to ensure that all participants knew their company’s policy when it comes to the use of online comments for innovation and had some degree of responsibility in that process. The only criteria for the organizations the sample practitioners of this study worked at, was that their organizations had to be actively involved with social media and had to deliver end products to consumers (so business-to-consumer or business-to-business-to-consumer companies). This in order to ensure that participating companies engage in social media and that the comments they receive contain customer insights or customer knowledge. Other company-specific criteria such as sector, size or type of offering (product or service) was not considered in this study, as the aim is to provide for as much variety in themes as possible, as opposed to the discovery of company- or industry-specific themes.

Furthermore, in the selection phase of the sample it became apparent that two types of social media or innovation practitioners can be distinguished: 1) those that work for ‘industry’ organizations that have a social media presence and 2) those that can be qualified as ‘social media or innovation

24 experts, advisors or consultants’ who offer social media services to other organizations. Both types of practitioners were included in this study, however the second category was specifically asked to provide more information on the specific cases of one or two of their customers in order for the interview data to remain homogeneous. The interview data from both types of practitioners was analyzed in the same manner as described in chapter 3.2.3.

Setting

The participants were invited through various methods: 1) through cold acquisition via LinkedIn, the participant received an invitation to join this study; 2) through consulting the researcher’s personal network; and 3) through the snowballing effect, where participants were asked to provide the names of peers who were also practitioners of social media or innovation (Noy, 2008). This resulted in 24 appointments with managers in the fields of social media and/or innovation of which 18 actually took place (6 interviews were cancelled and could not be rescheduled within the time constraints of this study). Due to time constraints, some interviewees were not able to partake in lengthy interviews, while others did not mind. For this reason the length of the interviews varied from 30 to 75 minutes, however the majority of the interviews took 45 minutes. The interviews were held either in person, through phone or via Google hangout (in the case of participants living outside of the Netherlands). Previous study has found no evidence as to the differences in research results of interviews held over the phone or in person (Sturges & Hanrahan, 2004). The interviews were held in the months of October, November, December 2016 and January 2017. Most respondents spoke Dutch, because this study was held in the Netherlands, however some respondents spoke English, because they either live in the United States or Belgium. An overview of the participants of this research together with their additional information can be found in appendix 1.

3.2.2. Semi-structured interviews

The questions of the interviews were divided into sections corresponding to the research questions that were described in chapter 2.5. The course of the interview strongly depended on whether an organization was an opponent or proponent of the acquisition of OCK in the innovation process.

25 Therefore, two courses of interview were possible, as summarized in figure 3. The full interview structure can be found in appendices 2A and 2B.

Figure 4 - Structure of interview questions

For easy comprehension from the interviewees, the act of acquiring customer information from online comments was defined as ‘social listening’ in the interviews, although other terms could have been used to describe this practice. When asked how employees deployed social listening they sometimes actually indicated netnography methods or other types of OCK acquisition, which will be explained in the following chapter. Furthermore, ambiguous concepts were defined or explained, such as social

listening and customer knowledge and sometimes also innovation before questions were asked.

3.2.3. Analytic strategy

After approval from the participants, every interview was recorded and transcribed using transcription software Insqribe. Unfortunately, one of the interviews was only partly recorded, as became evident during the transcription of the interviews, which is why data from this interview was drawn from the interview notes that were made during the interview. Subsequently, the resulting interview texts (which can be found in appendix 3A - appendix 3R) were imported in the qualitative research software Atlas.ti. Furthermore, the content of the interviews was analyzed using the content analysis

Does your organization extract customer knowledge

from online comments for the purpose of product innovation? Why (not)?

How does your organization do so?

What were the success factors of using online comments for product

innovation?

How does your organization use online comments?

What could be the potential success factors of using online comments for product

innovation?

If yes: If no:

RQ3: RQ2: RQ1:

26 method. Content analysis is a commonly used method for analyzing qualitative research data that allows the researcher to categorize the textual data using codes and nodes (Yin, 2013). Doing so requires the generation of codes, which are the labels given to data that appear to be conceptually similar and that are grouped together by the researcher (Lockyer, 2004). Coding is essential because it allows researchers to reduce data to concepts, to develop concepts in terms of their properties and dimensions and to differentiate one concept from another (Corbin & Strauss, 1997). Codes can be generated deductively (prior to analysis, based on existing theory) or inductively (after analysis). In this research, a mixed approach was used. Similar to Miles and Huberman (2013), this study began with a list of codes (concepts) derived from the literature; next, these codes were revised by

comparing them with the actual textual data from the interviews. This resulted in addition of several other codes. Some codes were determined deductively (those related to online data acquisition methods) while others were determined inductively (those related to the reasons for why not to use OCK and the success factors). The codes that were found in the interview data are presented in the following chapter as the results of this study.

In the analysis and interpretation of codes, themes and categories, Corbin & Strauss (1997) argue that there are two basic analytic strategies that are used in the research process, which include the making of constant comparison between interview data from multiple interview and between interview data and existing knowledge; and also the asking of questions that contribute to the critical analysis of the data. Both strategies were used in the analysis in this study. Constant comparisons were made between what is already existent in current literature while also questions were asked as to what is the meaning of the concepts that were discovered. These strategies advance the emergence of new theories that can be made from interview data (Corbin & Strauss, 1997).

3.3. Validity and reliability

In qualitative research, transferability replaces the concept of external validity, which is used to describe the generalizability of particular findings in qualitative research (Hirschman, 1986). Because

27 this study relies on the experiences and cases of multiple practitioners, instead of one case study, the results of this study can be applied to a variety of organizations. Still, in order for the results to be completely generalizable, quantitative studies can evaluate and test these results for single cases (e.g. by making distinctions in terms of the industry of a company, its size or whether it produces products or delivers services).

3.3.2. Credibility and dependability

Credibility and dependability refer to the concepts of internal validity and dependability respectively in quantitative research (Hirscheim, 1986) . In qualitative research, credibility is sought to establish confidence in the logic of the findings. For this reason, ‘member checks’ where performed in case the answers to particular questions in the interviews was found to be ambiguous. In studies that rely on in-depth interviews, researchers should always be aware of the interviewer-effect, in which the presence and behavior of the interviewer can bias the interviewee’s response. This, in settings were the interview is held face-to-face, is a consistent challenge for researchers t avoid. Furthermore, people’s narrative explanations do not always conform to the reality of a situation, which requires consideration of reliability and triangulation. In order to ensure dependability, the methods and decisions about the research have been made available and the documentation of the data is provided in the appendices.

3.3.3. Confirmability

Like any other method for qualitative research, in-depth interviews are subject to potential researcher biases. However by following systematic research design procedures that are aimed at exploring the potential outcomes for a certain phenomenon, the potential for researcher bias can be decreased (Hirschman, 1986). Confirmability specifically addresses the issue of research bias in data analysis and interpretation. As recommended by Hirschman (1986), the study findings have therefore be presented to an outside auditor (in this case one university student) to evaluate whether the findings appear to be logical and depending . Furthermore, the researcher has attempted to follow as strictly as possible the research approach as defined in chapter 3.2., so as to ensure that data be analyzed and objectively.

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4. Analysis

The following sections present the results of the in-depth interviews that were held with 18 social media and innovation practitioners. Based on the transcriptions of these interviews and systematical analysis, this chapter provides an objective presentation of how the participants’ organizations currently utilize OCK for product innovation and what factors lead to the success of this process. Some of the arguments that are made in this chapter are illustrated with quotes. Although every interview was analyzed and used for the writing of this chapter, not all the interviews were used for quotes. This chapter is divided in accordance with the three research questions as proposed in chapter 2.5: why organizations do not use OKC for product innovation, what methods they use to acquire OCK for product innovation, and what are the success factors of using OCK for product innovation.

4.1. The use of online customer knowledge for product innovation

In order to answer the first research question, ‘why do companies not acquire customer knowledge

from online customer comments for product innovation?’,social media and innovation practitioners were asked about the ways in which their organizations use the comments that their customers have submitted online about their brand, products or services. All interviewees believe that the knowledge about customers is important for marketing and product development purposes. Therefore, all the organizations that were interviewed were engaged with offline market research in the traditional sense, i.e. they used surveys, polls and interviews to enhance their understanding of customers and competitors. Furthermore, the majority of the organizations that were analyzed used online comments in some fashion, but not all of them did so for the purpose of product innovation. This section

describes the reasons for why the participants of this study did not use OCK for product innovation. Many participants argued that online customer comments in general were important for their organizations, “after all” one research director said, “so many things are being posted online, it is almost a shame to not do anything with them”. The constantly increasing amount of knowledge from customers about brands and products that is being posted every second online is free, accessible and gives organizations an unobtrusive method to take a look at the lives of their customers. However, acquiring OCK for the purpose of innovation of products might in some cases be a useless practice.

29 The reasons for why some interviewees believe so can be categorized in either technology, social media or OCK arguments (see table 1).

Table 1 – Arguments for why organizations do not acquire customer knowledge from online comments for product innovation

Technology Social Media Online customer knowledge

There are too many unusable comments to scan before comments that contain OCK are found

Traditional market research is more suitable for acquisition of customer knowledge for product innovation.

OCK is difficult to acquire, because customers are not likely to express their customer knowledge online. Current technology does not

detect ‘noise’.

It is difficult to interact with customers through social media about product innovations.

Customers do not know what they want.

Current technology cannot yet scan textual data on a deep enough level to discover customer knowledge

Knowledge on social media is too public, everyone (including competitors) can see and use it. On social media it can be difficult to determine who made a comment.

Technology arguments

The technology arguments explain that current technology is not yet able to discover or analyze the online comments that contain customer knowledge amidst all of the online comments that are being posted on social media. Social media contains so much information that it might also be described as big data. According to Prescott (2016), big data is a large amount of data that is continuously being collected, stored and managed”. Big data sets are often so large and complex that they require unique techniques and methods for their storage, management and analysis (Gandomi & Haider, 2015). For this reason, organizations need qualified professionals and suitable technology in order to make sense of the many comments that are being posted online. Organizations that have not invested in big data analytics systems, might find it an extremely time-consuming practice to browse social media for the discovery of OCK. Therefore, they would rather not engage in OCK acquisition at all.

Furthermore, even if organizations have the right tools and people to scan social media, technology constraints make it difficult to detect what some interviewees call noise. To exemplify, one Global Innovation Manager argued that “[on social media] there is a lot of noise, you have to do a

30 lot of work to get to that one nugget of information that you can use” (Anonymous, p.c1_{., December} 12, 2016). With ‘noise’ he aims to describes: the comments that are not written by customers but rather other organizations; the comments that are practically useless, because customers only state a fact (e.g. “Today, I went to Ikea”); or comments that contain untruthful or cynical statements. Noise, is something that current text analysis tools are not able to decipher, and the large quantity of noise on social media, makes OCK even harder obtain. For this reason, some interviewees perceive acquiring OCK as looking for a needle in a haystack.

In addition, current technology for the analysis of textual data is not developed enough to analyze online customer comments to the extent of understanding customer comments on a deep level. The fact that text mining tools have difficulty with detecting cynical statements implies that human interference is necessary in the acquisition of OCK. One research manager argued that the amount of cynical comments about an advertisement of the reformed Christian church, impeded the social listening research he aimed to conduct for this organization (E. Rikken, p.c., December 5, 2016). Understanding whether a comment was cynical or not required of him to check the profiles of the people who placed comments to see if they were registered to a church or not. Because this practice cannot yet be automated with current technology, many interviewees argued that they would rather not engage in it.

Interviewees use technology arguments to explain that the efforts of acquiring OCK do not weigh up to the potential benefits that mining through social media comments may provide them. For these practitioners, traditional market research methods are much more effective than online methods for firms that aim to use customer knowledge for product innovation.

Social media arguments

Social media arguments refer to the notion that social media is not the right platform to acquire customer knowledge from. Although customer knowledge may be useful in the production of innovative products, interviewees argue that it is better to be acquired through traditional and offline market research methods which allow facilitate co-creation. Research director and expert of social

1 _{P.c. refers to ‘personal communication’. This abbreviation is used for the textual space constraints of} this paper.

31 listening projects, R. Landeweerd (p.c., 2016), argued in one of the interviews that traditional market research allows organizations to see the person behind the comment, “and if you don’t understand something you can ask them why and how”. Traditional market research therefore allows

organizations to ‘probe’, ask follow-up questions in order to come to a deeper and broader understanding of customer beliefs. Many of the interviewed opponents of using OCK for product innovation argue that in order for customers to be used in the innovation process they must attain a certain level of creative activity from the customer that can best be triggered in a face-to-face setting. Physical, rather than online settings, allow the organization and the customer to work together alongside each other and enables researchers to ask probing questions to customers. Some of the interviewed practitioners argue that co-creating innovative products, is something that cannot occur on social media.

Moreover, if a firm’s aim is to use customer knowledge in the ideation phase of an innovation process, some participants argue that social media is not the right place for organizations to discover customer knowledge that can be used for product innovations. Social media is a unique platform to gather customer knowledge from, because it allows customers to express thoughts from the comfort of the location of their choice. The result of which is that online comments are often pure and

unmodified representations of the customers’ thoughts (E. Riken, p.c., December 5, 2016). Interference of profit-seeking organizations could potentially damage this characteristic of social media and if organizations do so, the unobtrusive and natural characteristics of this medium will become obsolete (E. Rikken, p.c., December 5, 2016). Interviewees argue that if organizations want to use customer knowledge in the process of innovation, it requires some degree of activity of customers that is difficult to obtain through social media.

Furthermore, participants argued that social media is too public, if organizations wish to talk to customers online and use their online comments for innovation then their competition could do the exact same thing (E. Karel, p.c., November, 24, 2016). The information that is presented on social media is freely accessible for everyone (also competitors), and therefore not rare, which makes it difficult for organizations to develop something that is differentiating and innovative using only social media content.

32 Another social media argument for why OCK is not used for product innovation is because customers have the choice to be anonymous online. In an online context, customers may grant interesting customer knowledge, but organizations often face difficulty in identifying the customer and his demographic. One participant argued that sometimes it is a challenge to discover whether the provider of a comment actually fits the target group of the organizations, and thus whether his comment is relevant (R. Landeweerd, p.c., November 16, 2016). Traditional, offline market research methods allow the researcher to see who is making a specific comment so that its relevancy can be determined.

The social media arguments solicit the notion that OCK is less valuable in the process of innovation than customer knowledge acquired through traditional offline market research. However, like supporters of the technology arguments, followers of the social media arguments do find customer knowledge to be valuable in the process of innovation, while proponents of customer arguments do not.

Online customer knowledge arguments

The OCK arguments concern arguments in which practitioners imply that OCK, in general, is not a suitable source of innovation. They think so because they believe customers are not likely to express the type of knowledge that can be used for product innovation (E. Karel, p.c., November 24, 2016). Extracting knowledge from online comments would then be a useless act, as no useable knowledge can be acquired.

Some participants argued that customer knowledge is something that is very difficult to extract in general. This is because, they argue, people are much restricted by what they already know, e.g. their own frames of references. Using their knowledge to create innovative ideas for product innovation is something that is extremely difficult to achieve, because, as mentioned before, it requires users to be creative and engaged. Market insight generation tools such as social listening can be used to listen to people’s needs, but not so much to see whether certain products or services would be an answer to those needs. One research manager also argued that, “in a natural conversation space such as on social media, you don’t just come up with something new” (E. Karel, p.c., November 24,

33 2016). Organizations might ask customers about their wants and needs, but people do not just express the solutions they want to their problems if they are not triggered to do so. One manager at leasing company Leaseplan argued that “People on social media don’t say what they want. It is a place to give expression to things that are on their minds. Firms can either solve their problems or not solve them” (P. Chaturi, p.c., November 24, 2016). In other words, these managers argue that OCK is very rare, because it is people rarely discuss their customer knowledge online. Practitioners who argued that customer arguments believe that other sources of innovative ideas and evaluation such as

brainstorming sessions, the attendance of summits or reading of recently published journal articles would are more reliable sources of innovation.

4.1.1. Brief discussion

The arguments for why organizations should not engage with OCK provide for food for thought about the usefulness of OCK in product innovation processes. It seems that technology-related challenges can be resolved by the interference of human professionals. Online knowledge acquisition is therefore something that firms should invest a substantial amount of finances, time and human resources in. There are many organizations that believe that this is in investment is worthwhile, and more importantly, profitable. Social media-related arguments reveal that the type of knowledge that is necessary for the process of innovation cannot be retrieved from social media. However, if professionals adopt the right strategies, customer knowledge indeed can be found on social media. As will become clear from the following to subchapters, it is a matter of asking the right questions and deploying OCK in the right stages of the innovation process. Furthermore, OCK arguments are used to describe that the knowledge from customers is difficult to retrieve in general, let alone online. In order to still use OCK, organizations must then acquire the tools that stimulate people to share their experience, creativity and (dis)satisfaction with brands and products. This, too, can be achieved by using the right tools and methods as described in the following subchapter.