Data Exploration and Information Retrieval in the B2C Marketing Department of the Financial Times

An in-depth research into how members of the marketing team explore and analyse data to gain insight, with design recommendations for dashboard reporting tools.

UX Research Proposal

1  INTRODUCTION

  

1.1  Title:

Recreating the positive user experience associated with tablet business/productivity apps in computer business/productivity software.

1.2  Question:

To what extent can the positive user experience associated with tablet business/productivity apps be recreated in computer business/productivity software?

1.3  Background:

The backdrop to my proposed research lies in the current transformation of the personal computing industry.  Commercial research of North American and Western European markets indicate an increasing preference by consumers for tablet devices over desktop and notebook computers (Reisinger, 2012). IDC forecast tablet sales to grow by 123.23% between 2012 and 2016 (Mainelli and Song, 2012) with PCs and notebooks growing by 7.1% in comparison (Kobie, 2012), albeit from a significantly larger base. NPD DisplaySearch forecasts that, in 2017, 416 million tablets will be sold, surpassing notebook sales of 393 million (Himuro and Shim, 2012). The factors driving this trend are of interest not only to the IT industry but also the academic community, particularly within the field of user experience (UX) design.

Besides differences in their respective physical form, the user interface (UI) and mode of interaction also differ between tablets and traditional computers. I hypothesize that these differences in design produce distinct UX attributes that can be identified and measured. The extent to which computer business/productivity software can be designed for the UX associated with tablet business/productivity apps can thus be evaluated.

The decision to focus the research on business/productivity software is based on market data – the top paid Mac software on the App Store[1], after OS X, are Pages and Numbers while the second best-selling PC software on Amazon is Microsoft Office (“Amazon Best-Sellers,” n.d.). This implies that the most popular usage of computers is for productivity and if tablets are seen as substitutes, the UX of business/productivity apps may be an influential factor.  

1.4  Objectives:

My objective is to identify and measure the attributes that contribute to the positive UX of tablet business/productivity apps and determine the degree to which they can be replicated in a traditional computing environment.

To achieve this, I will need to:

1. Identify the two most popular tablet apps in the business/productivity category, in order to gather data that is broadly representative of usage patterns.
2. Evaluate the apps to identify and define their positive UX attributes and associated UI features.
3. Assign metrics to each UI feature to determine its relative value.
4. Determine the extent to which the UI features can be supported in computer software.

1.5  Products:

The products of the research will be a set of UX attributes and associated UI features of tablet business/productivity apps, and factors supporting or preventing their implementation in computer software.

1.6  Beneficiaries:

The intended beneficiaries of the research products are developers of computer software that run on Mac OS X Mountain Lion (“Apple - Here’s everything you need to know about OS X.,” n.d.) and Windows 8 (“A new look for Windows 8 - Microsoft Windows,” n.d.), both of which possess aspects of tablet UX design paradigms.

2  ACADEMIC CONTEXT

2.1  The Need for UX Evaluation:

The UX body of knowledge is not mature and incremental research is required as the nature of the relationship between users and interactive products evolves from functionality to emotiveness (Hassenzahl and Tractinsky, 2006). Whereas traditional computers might have been founded on such usability goals (Rogers et al., 2011) as accomplishing tasks efficiently and effectively, the popularity of tablets is driven by broader UX goals (Rogers et al., 2011) like satisfaction and enjoyability.

The shift from usability to UX parallels the progression of human needs from physiological to self-actualisation (“Maslow’s hierarchy of needs,” 2011). However UX does not diminish usability; it encompasses and extends it (Mahlke and Thuring, 2007, cited in Kujala et al., 2011). As users have both a contextual need to accomplish tasks with minimal problems and an innate need to be challenged, appreciate beauty, esteemed by others, etc., it is proposed that interactive products should be designed to fulfil the former, pragmatic goals as well as the latter, hedonic goals (Hassenzahl and Tractinsky, 2006). Given a choice between a product that only meets pragmatic goals and one that meets both pragmatic and hedonic goals, user preference tends to be for the latter and there is a positive correlation between a product’s perceived hedonic quality and its perceived pragmatic quality (Schrepp et al., 2006).

It is suggested that products which generate a sustained positive UX are likely to engender customer loyalty (Kujala et al., 2011), therefore if computer software is perceived to have lower hedonic quality than tablet apps, that could negatively affect its relative demand.

2.2  Challenges of UX Evaluation:

The success factors for technology products go beyond their technical functionality and efficiency of task performance; they also include the emotions, thought processes and attitudes experienced when the products are being used, which in turn inform the users' actions. As such, these factors need to be identified and measured to establish a benchmark against which the product can be evaluated (Beauregard et al., 2007).

The subjective nature of UX implies that a definitive evaluation of UX quality is improbable, since individual perception is a synthesis of the natural context of use (Kujala et al., 2011), mental model and resultant gulfs of execution and evaluation (Rogers et al., 2011) and personal values. This questions the plausibility of the speculation that UI could be engineered to derive positive evaluation from users (Schrepp et al., 2006); a more achievable goal would be designing UI features conducive to a positive UX (Hassenzahl and Tractinsky, 2006). How successful such features are can then be measured from either the product or the users’ perspective (Khan, 2012).

Additionally, the benchmark for perceived UX quality shifts as technology and human behaviour evolves (Beauregard et al., 2007), demonstrated by the impact of the consummerisation of IT on the expectations of business software users. Hence UX evaluation should be on-going, ideally.

2.3  Existing Research Products on UX Evaluation:

Research using the AttrakDiff2 tool (“AttrakDiff,” n.d.) shows that hedonic and pragmatic factors are equally influential to typically task-motivated business software users (Schrepp et al., 2006), supporting the near-universal relevance of personal development, “Stimulation”, and personal image projection, “Identity” (Hassenzahl, 2006), to the UX of interactive products. The paucity of rich explanations by users constrains the research’s capacity to inform future product development, however. Gathering data in a controlled environment, in a single usage instance also excludes data about environmental influences, and the evolution of UX over time (Kujala et al., 2011).

In a survey measuring the general UX of mobile phone users (Khan, 2012), it was concluded that context-independent methodologies and metrics are unavailable. However Semantic Differential Methodology (SDM) was demonstrated as viable for measuring UX during use (Beauregard et al., 2007; Schrepp et al., 2006) and retrospectively (Khan, 2012). Consideration should be given to which adjective pairs for bipolar scales are relevant to the product, either through literature review (Khan, 2012) or collection of primary data.

The UX Curve is proposed as a cost-effective method of evaluating the nature and causes of UX changes over time (Kujala et al., 2011), drawn freehand or with online tools like iScale (Karapanos et al., 2012). The retrospective evaluation yields qualitative data from the selective memories that shape “long-term” UX perception and user behaviour (Oishi and Sullivan, 2006, cited in Kujala et al., 2011). The UX Curve’s advantage over SDM is it draws out the UX attributes that are most significant to users rather than selecting from a pre-determined list. Conversely, the qualitative data analysis is more complex but this can be alleviated by mapping coded themes to established categories (Khan, 2012).

A research on evaluating the UX quality of Intel-based systems suggests a three-step approach to guide UX design and evaluation: ranking product “features and usages” desired by users; selecting associated UX attributes and devising metrics for them; and establishing quality benchmarks (Beauregard et al., 2007), although it was unclear how the first step was achieved in the UXQ Benchmark Dashboard Study. The “platform approach” taken, encompassing the whole ecosystem from hardware to software, is generalizable; the inseparability of app UX from a tablet’s physical form necessitates the consideration of how software fits into hardware and operating systems.

  

3  METHODS AND TOOLS FOR ANALYSIS AND EVALUATION

3.1  Apps Selection:

1.  The two most purchased Tablet business/productivity apps on Google Play will be selected. Although the iPad is the leading platform, it would be difficult to contact app users for participation without access to their social media profiles.

3.2  Participant Selection:

1. The Google+ page of each app will be visited to identify users.
2. A demographically-diverse sample will be invited to participate, following the Research Ethics Checklist guideline to: exclude those under 18 years or deemed vulnerable; explain purpose of research and relevant procedures; seek express consent. No material reward will be offered to participants.
3. 10 demographically-balanced willing participants per app will be selected, with long-term usage of 6-12 months (Karapanos et al., 2010). Participants will be informed of their: unrestricted freedom to withdraw; views represented accurately; personal data held confidentially in accordance with the Data Protection Act, including data destruction upon withdrawal; fair treatment in accordance with the Equality Act.

3.3  Methodology and Tools:

1. Initial data about perceived attractiveness (Hassenzahl et al., 2003, cited in Schrepp et al., 2006) will be gathered using SDM in AttrakDiff2 (“AttrakDiff,” n.d.). This will be used in validating UX Curve data.
2. UX Curve templates (Kujala et al., 2011) will be created for evaluating attractiveness, pragmatic, hedonic stimulation and hedonic identity qualities (Hassenzahl et al., 2003, cited in Schrepp et al., 2006) of the apps, using DrawUX (“DELUX DrawUX,” n.d.). Inflection points will be annotated with descriptions.
3. Descriptions will be coded to identify UI features and associated UX attributes. The research scope is limited to positive UX so negative attributes will be ignored.
4. UX Curve attractiveness data will be validated with SDM data and clarification will be sought for any variation.
5. Regression analysis will be applied to determine the extent to which pragmatic and hedonic UX attributes determine attractiveness in line with the model of Hassenzahl et al. (2003), cited in Schrepp et al., (2006). This is to establish the influence of each UI feature on preference.
6. The UI features are ranked in order of influence and those that can be implemented within the hardware and operating system environment of Windows PCs and Apple Macs are collated.
7. The collated UI features and associated UX attributes are presented as the first and second steps of the three-step guide to UX design and evaluation (Beauregard et al., 2007).

APPENDIX 1: REFERENCE LIST

• A new look for Windows 8 - Microsoft Windows [WWW Document], n.d.  windows.microsoft.com. URL http://windows.microsoft.com/en-US/windows-8/new-look (accessed 12.13.12).
• Amazon Best-Sellers [WWW Document], n.d.  Amazon Best Sellers. URL http://www.amazon.com/best-sellers-software/zgbs/software (accessed 12.17.12).
• Apple - Here’s everything you need to know about OS X. [WWW Document], n.d.  Apple. URL http://www.apple.com/osx/what-is/ (accessed 12.13.12).
• AttrakDiff [WWW Document], n.d.  AttrakDiff. URL http://www.attrakdiff.de/en/Home/ (accessed 12.15.12).
• Beauregard, R., Younkin, A., Corriveau, P., Doherty, R., Salskov, E., 2007. Assessing the Quality of User Experience. Intel Technology Journal 11, 77–87.
• DELUX DrawUX [WWW Document], n.d. . URL http://www.cs.tut.fi/ihte/projects/delux/drawux.html (accessed 12.8.12).
• Hassenzahl, M., 2006. Hedonic, Emotional and Experiential Perspectives on Product Quality, in: PhD, C.G. (Ed.), Encyclopedia of Human Computer Interaction. Idea Group Inc (IGI), p. 269.
• Hassenzahl, M., Tractinsky, N., 2006. User experience – a research agenda. Behaviour & Information Technology 25, 91–97.
• Himuro, H., Shim, R., 2012. Tablet Shipments to Surpass Notebook Shipments in 2016 - DisplaySearch [WWW Document]. NPD Display Search. URL http://www.displaysearch.com/cps/rde/xchg/displaysearch/hs.xsl/120703_tablet_shipments_to_surpass_notebook_shipments_in_2016.asp (accessed 12.13.12).
• Karapanos, E., Martens, J.-B., Hassenzahl, M., 2012. Reconstructing experiences with iScale.pdf. International Journal of Human – Computer Interaction.
• Karapanos, E., Zimmerman, J., Forlizzi, J., Martens, J.-B., 2010. Measuring the dynamics of remembered experience over time. Interacting with Computers 22, 328–335.
• Khan, K., 2012. User Experience in Mobile Phones by Using Semantic Differential Methodology. Proceedings of the European Conference on Information Management & Evaluation 143–150.
• Kobie, N., 2012. IDC slashes PC sales forecast as tablets take over | News | PC Pro. PC Pro.
• Kujala, S., Roto, V., Väänänen-Vainio-Mattila, K., Karapanos, E., Sinnelä, A., 2011. UX Curve: A method for evaluating long-term user experience. Interacting with Computers 23, 473–483.
• Mainelli, T., Song, J., 2012. IDC Raises Its Worldwide Tablet Forecast on Continued Strong Demand and Forthcoming New Product Launches - prUS23696912 [WWW Document]. International Data Corporation. URL http://www.idc.com/getdoc.jsp?containerId=prUS23696912#.UMnau7ZBnhZ (accessed 12.13.12).
• Maslow’s hierarchy of needs [WWW Document], 2011. . Teachers Toolbox. URL http://www.teacherstoolbox.co.uk/T_maslow.html (accessed 12.17.12).
• Reisinger, 2012. PC Sales Forecast: Will Windows 8 End the Slump? - Windows. CIO Insight.
• Rogers, Y., Sharp, H., Preece, J., 2011. Interaction Design: Beyond Human - Computer Interaction, Third. ed. John Wiley & Sons Ltd, West Sussex.
• Schrepp, M., Held, T., Laugwitz, B., 2006. The influence of hedonic quality on the attractiveness of user interfaces of business management software. Interacting with Computers 18, 1055–1069.

APPENDIX 2: APPLE APP STORE

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[1] See Appendix 2 as URL is unavailable for referencing.