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customer research will get easier and more sophisticated in the realtime interactive communication of social media. Bourdeaux (2011 b, 30) introduces different benefits for different parts of an organization. Product development can benefit from social media by receiving new ideas through crowd sourcing, by accessing qualified test subjects and researching their opinions, and by increasing their ability to leverage expertise and find ideas across the entire organization. Customer service and support, on their behalf, can benefit from social media by finding new opportunities for self-service and lower costs of maintaining knowledge bases through integrated internal and external media, and by greater personalization as they get more access to customer behaviors and preferences. Hiring and professional development may benefit by increased access to the best candidates, decreased costs per hire, increased collaboration and access to internal experts, and decreased time to competence with social knowledge management applications. Finaly, marketing and sales can benefit from social media by improved targeting through self-selected social media users, decreased costs through free applications, and through increased acquisition efficiency and penetration rates through viral mechanisms. (Bourdeaux, 2011 b, 30). 3.5.4 Measuring the social media success The online advertising industry has standardized a few key metrics and tools, but the measuring of social media success is still in its infancy, without any standardizations. However, a new possibility that social media has brought is the listening to the voice of the customer. (Zinner & Zhou, 2011, 70). Social media provides organizations with hunderds, thousands, or even millions of hits every day. These are signs of what their customers are thinking and doing, having to do with the operations of the organization. This information is highly valuable in understanding the needs and wants of the customers and potential customers, not to mention in predicting the future trends. Positive aspects about this information is that it is free of charge and already in a digital format. The downside then again is that someone needs to interpret the masses of data before it can be turned into valuable information. The style of social media feedback is more emotinal than feedback on, for exaple, traditional questionnaires. Also the amount of data is much higher than ever before, and it cannot easily be predicted when customers react passionately and when nothing happens. The feedback is complex and an organization needs to decide when to react and when to simply ignore something. (Zinner & Zhou, 2011, 88-89). There are technologies 53
developed for the function of filtering the data and analysing it into more comprehensible form. These technologies, however, are not solid as they can not always separate the tone of some individual message, as a person could. These robots can, for example, look for hits in any online content with specific key words and try to categorize the messages into either positive, neutral, or negative. (Zinner & Zhou, 2011, 78). There are various tools for analyzing online data. Some tools, like the widely used Google Analytics, have gained a strong foothold in the market, but there is a countless amount of other tools available online as well. The vast amount of different tools can make their comparison tricky. (Xun & Reynolds, 2010, 19). These tools are used for example for following the visitor amount of a certain site, blog, application et cetera, the trail of how a person found to that site (through search engines, for example), the length they stay at the site, the activity they show on the site, how they share content from that site, how much people are talking about a certain subject online, et cetera, the list is endless, and there are different services for finding all of the information needed. According McDaniel (2011) there are three simple metrics to be utilized when measuring social media success of an organization. First, Total Online Community Size (sCRM) can be calculated by adding together all of the different application followers an organization might have (fans in Facebook, Followers in Twitter or blog et cetera). This information needs to be manually collected by saving the weekly or monthly key figures. The second measure is Monthly Referred Social Traffic to Site (sTraffic) that tracks social media link clicks, content pass-along, and other deeper metrics. The third metric is Social Monthly Impressions (sMI) that estimates the social monthly impressions using free alerts tools, such as Google Alerts. (McDaniel, 2011). The challenge to organizations here becomes the one of choosing which information to gather and what to do with it ones it is available to them. Organizations would thus need to modify their aspirations into a numeral format and then follow those numbers also from the online activities of customers and potential customers. After the data is gathered, an organization needs to analyze it and make adjustments according to the received feedback in the data. (DiViA, 2011). 54
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Is there more to it than posting a
Page 3 and 4: Tiivistelmä Tämä tutkimus osalli
Page 5 and 6: 5 FINDINGS OF THE RESEARCH ........
Page 7 and 8: 1 INTRODUCTION “Winning and keepi
Page 9 and 10: museums, are expected to outperform
Page 11 and 12: 1.1 Research questions and structur
Page 13 and 14: & Levy (1969) defined it, it is jus
Page 15 and 16: profit, and governmental. Each of t
Page 17 and 18: and the consumer of a service are t
Page 19 and 20: 3 THEORY: RELATIONSHIP WITH THE CUS
Page 21 and 22: 3.2.1 A mindset for customer relati
Page 23 and 24: depends on the customer and industr
Page 25 and 26: to understand in service organizati
Page 27 and 28: fact that a service is created at t
Page 29 and 30: RM, however, is not a new phenomeno
Page 31 and 32: step to creating a relationship. Wi
Page 33 and 34: 25). When the clientele of an organ
Page 35 and 36: all problems, for example, also in
Page 37 and 38: Traditionally customers have seen t
Page 39 and 40: entire process of co-creation of va
Page 41 and 42: messages received by the customers
Page 43 and 44: confused with the technology behind
Page 45 and 46: engage with the organization in soc
Page 47 and 48: media in an organization, and thus
Page 49 and 50: 3.5.1 Social media applications Soc
Page 51 and 52: & Leighton 2011). Kozinets et al. (
Page 53: approximately 30 percent of the use
Page 57 and 58: important, what will it give to the
Page 59 and 60: 4 METHODOLOGY In order to find out
Page 61 and 62: interviews, instead of unstructured
Page 63 and 64: The methods used for data collectio
Page 65 and 66: with regard to the number of organi
Page 67 and 68: collections, the museums spent 2,8
Page 69 and 70: using the internet, but also they a
Page 71 and 72: Registered as a user in a social ne
Page 73 and 74: does what, at least almost on case
Page 75 and 76: wise to consider the style of writi
Page 77 and 78: there is or how to behave, or what
Page 79 and 80: Even though a few museums seemed to
Page 81 and 82: …There, in the online world a mus
Page 83 and 84: sized museum had, not only customer
Page 85 and 86: We don’t know whether people from
Page 87 and 88: Yes, you could day the experience i
Page 89 and 90: inquired on whether different conte
Page 91 and 92: 6 DISCUSSION In this chapter the fi
Page 93 and 94: Another concern the museums pointed
Page 95 and 96: utilization, would be clear to them
Page 97 and 98: 7 CONCLUSIONS In this chapter a dis
Page 99 and 100: that even when people do arrive int
Page 101 and 102: large-scale interactions with exter
Page 103 and 104: 8 REFERENCES Alasuutari, P. Laadull
Page 105 and 106:
Conway Tony & Debra Leighton. ”Co
Page 107 and 108:
Grönroos Christian. ”Service Qua
Page 109 and 110:
McDaniel Clay. ”3 Key Metrics To
Page 111 and 112:
Passebois Juliette & Philippe Aurie
Page 113 and 114:
Sorav Jain. ”40 Most Popular Soci
Page 115 and 116:
APPENDIX 1: List of Finnish art mus
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