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A Conceptual Investigation of the
 Value of Social Media Data as a
   Source of Customer Insight
  Ana Isabel Canhoto, Oxford Brookes University
  Jan Kietzmann, Simon Fraser University




                  Canhoto and Kietzmann, 2012
The issue




Canhoto and Kietzmann, 2012   Source: Kietzmann et al 2011
The issue




Canhoto and Kietzmann, 2012
The goals
• Investigate the potential of SM channels to
  contribute to customer insight
• Conceptual research: move theory and practice
  from a predominantly micro perspective to a
  fairly macro one (MacInnis, 2004)
• Availability of data vs. Value in use
  – Information Systems: to make good decisions,
    managers need to assess the quality of the input
    data on its own, as well as in terms of its usefulness
    for solving specific tasks (Watts et al., 2009)

                      Canhoto and Kietzmann, 2012
The goals
• Theory into practice:




                  Canhoto and Kietzmann, 2012
The goals
• Practice into theory:
  – Emerging techniques – Keynote speech
  – Knowledge gaps
• Different stakeholders’ perspectives
  – Users vs. developers of customer profiles
• Segmentation discourse
  – Possible vs. acceptable approaches
  – Quality
  – Effectiveness, efficiency…
                    Canhoto and Kietzmann, 2012
The approach
1. Identify a suitable framework to assess the
   quality of social media data
2. Adapt the framework for the specific
   context of segmentation
3. Validate the framework with users and
   developers of customer profiles
4. Apply the framework on social media data


                  Canhoto and Kietzmann, 2012
1. Literature Review




      Canhoto and Clark, 2012
2. Developing the framework
             Dimension                                             Segmentation
Intrinsic           The data in      Bias, errors, lies or exaggerations (Lichtman et al., 1992)
                    its own right;   [Keynote: Jameson and Bass 1989]
                    and source
                                     Results can be distorted by unique occurrences or local
                                     effects (Humby, Hunt, & Phillips, 2003)
Contextual          Context for      Cost and practical difficulties of obtaining and updating
                    which the        detailed customer typologies (Quinn, 2009)
                    data is to be
                    used             Solutions need to be manageable (Dibb, 2005)

                                     Key variables not easily observable (Hines & Quinn,
                                     2005)

                                     Gap in the literature concerning specific business
                                     contexts (Dibb and Simkin, 2001)
                                     Canhoto and Kietzmann, 2012
2. Developing the framework
            Dimension                                           Segmentation
Representational   The format    Practitioners value ethnographic research (Zolli, 2006)
                   and the       and qualitative insight such as video footage (Quinn,
                   meaning of    2009)
                   the data
                                 Intuitive approach (Palmer & Millier, 2004)

                                Broader, soft, more exploratory than operational data
                                (Canhoto, 2008)
Accessibility      How the data Multiple data sources (Bailey et al., 2009) and
                   is retrieved distribution channels (Meadows and Dibb, 1998)

                                 Transfer all the data into a single database (Meadows
                                 and Dibb, 1998)



                                  Canhoto and Kietzmann, 2012
2. Developing the framework




         Canhoto and Kietzmann, 2012
3. Validation
     Dimension                Segmentation                              Application
Intrinsic The data in   Bias, errors, lies or               Avatars in Second Life as self-
          its own       exaggerations (Lichtman et          idealizations of the user; Facebook
          right; and    al., 1992)                          profiles deemed to reflect actual
          source                                            personality fairly closely (Back et
                                                            al., 2010). LinkedIn, as a
                                                            professional social network, might
                                                            be seen as a better source
                                                            (Kietzmann et al., 2011)
                        Results can be distorted by         People generally share true
                        unique occurrences or local         consumption decisions on
                        effects (Humby, Hunt, &             Facebook, but lie on dating sites
                        Phillips, 2003)                     (Epstein, 2007)
                                                            Users can have several identities
                                                            through conscious or unconscious
                                                            disclosure of personal information
                                                            (Kaplan and Haenlein, 2010)
                                   Canhoto and Kietzmann, 2012
3. Validation
• Qualitative interviews (key informants)
  – So far: 2 users + 2 developers
  – Goal: 30 or saturation
• (Very) preliminary findings:
  – Dimensions: all relevant
  – Factors: not all equally relevant for every
    scenario



                     Canhoto and Kietzmann, 2012
3. Validation




  Canhoto and Kietzmann, 2012
A Conceptual Investigation of the
    Value of Social Media Data as a
      Source of Customer Insight
Ana Isabel Canhoto      Jan Kietzmann
www.anacanhoto.com      http://beedie.sfu.ca/profiles/JanKie
@canhoto                jan_kietzmann@sfu.ca
adomingos-
canhoto@brookes.ac.uk

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Am 2012 presentation canhoto and kietzmann

  • 1. A Conceptual Investigation of the Value of Social Media Data as a Source of Customer Insight Ana Isabel Canhoto, Oxford Brookes University Jan Kietzmann, Simon Fraser University Canhoto and Kietzmann, 2012
  • 2. The issue Canhoto and Kietzmann, 2012 Source: Kietzmann et al 2011
  • 3. The issue Canhoto and Kietzmann, 2012
  • 4. The goals • Investigate the potential of SM channels to contribute to customer insight • Conceptual research: move theory and practice from a predominantly micro perspective to a fairly macro one (MacInnis, 2004) • Availability of data vs. Value in use – Information Systems: to make good decisions, managers need to assess the quality of the input data on its own, as well as in terms of its usefulness for solving specific tasks (Watts et al., 2009) Canhoto and Kietzmann, 2012
  • 5. The goals • Theory into practice: Canhoto and Kietzmann, 2012
  • 6. The goals • Practice into theory: – Emerging techniques – Keynote speech – Knowledge gaps • Different stakeholders’ perspectives – Users vs. developers of customer profiles • Segmentation discourse – Possible vs. acceptable approaches – Quality – Effectiveness, efficiency… Canhoto and Kietzmann, 2012
  • 7. The approach 1. Identify a suitable framework to assess the quality of social media data 2. Adapt the framework for the specific context of segmentation 3. Validate the framework with users and developers of customer profiles 4. Apply the framework on social media data Canhoto and Kietzmann, 2012
  • 8. 1. Literature Review Canhoto and Clark, 2012
  • 9. 2. Developing the framework Dimension Segmentation Intrinsic The data in Bias, errors, lies or exaggerations (Lichtman et al., 1992) its own right; [Keynote: Jameson and Bass 1989] and source Results can be distorted by unique occurrences or local effects (Humby, Hunt, & Phillips, 2003) Contextual Context for Cost and practical difficulties of obtaining and updating which the detailed customer typologies (Quinn, 2009) data is to be used Solutions need to be manageable (Dibb, 2005) Key variables not easily observable (Hines & Quinn, 2005) Gap in the literature concerning specific business contexts (Dibb and Simkin, 2001) Canhoto and Kietzmann, 2012
  • 10. 2. Developing the framework Dimension Segmentation Representational The format Practitioners value ethnographic research (Zolli, 2006) and the and qualitative insight such as video footage (Quinn, meaning of 2009) the data Intuitive approach (Palmer & Millier, 2004) Broader, soft, more exploratory than operational data (Canhoto, 2008) Accessibility How the data Multiple data sources (Bailey et al., 2009) and is retrieved distribution channels (Meadows and Dibb, 1998) Transfer all the data into a single database (Meadows and Dibb, 1998) Canhoto and Kietzmann, 2012
  • 11. 2. Developing the framework Canhoto and Kietzmann, 2012
  • 12. 3. Validation Dimension Segmentation Application Intrinsic The data in Bias, errors, lies or Avatars in Second Life as self- its own exaggerations (Lichtman et idealizations of the user; Facebook right; and al., 1992) profiles deemed to reflect actual source personality fairly closely (Back et al., 2010). LinkedIn, as a professional social network, might be seen as a better source (Kietzmann et al., 2011) Results can be distorted by People generally share true unique occurrences or local consumption decisions on effects (Humby, Hunt, & Facebook, but lie on dating sites Phillips, 2003) (Epstein, 2007) Users can have several identities through conscious or unconscious disclosure of personal information (Kaplan and Haenlein, 2010) Canhoto and Kietzmann, 2012
  • 13. 3. Validation • Qualitative interviews (key informants) – So far: 2 users + 2 developers – Goal: 30 or saturation • (Very) preliminary findings: – Dimensions: all relevant – Factors: not all equally relevant for every scenario Canhoto and Kietzmann, 2012
  • 14. 3. Validation Canhoto and Kietzmann, 2012
  • 15. A Conceptual Investigation of the Value of Social Media Data as a Source of Customer Insight Ana Isabel Canhoto Jan Kietzmann www.anacanhoto.com http://beedie.sfu.ca/profiles/JanKie @canhoto jan_kietzmann@sfu.ca adomingos- canhoto@brookes.ac.uk