Proceedings of the 12th European Conference on Knowledge ...

Alexander Schneider and Alexander Steinh<strong>of</strong>f
Micros<strong>of</strong>t Excel. Regarding import options, nei<strong>the</strong>r Google Analytics nor Piwik <strong>of</strong>fer any possibilities to
import data from o<strong>the</strong>r sources. However, SiteCatalyst <strong>of</strong>fers different opportunities to import data, for
example, from customer relationship management (CRM) tools. Regarding export options, Google
Analytics <strong>of</strong>fers PDF, XML, CSV and TSV. In addition, Piwik <strong>of</strong>fers a JSON and RSS export <strong>of</strong>
reports. A native export to Micros<strong>of</strong>t Excel or Word is only included in SiteCatalyst. Ano<strong>the</strong>r advantage
<strong>of</strong> SiteCatalyst is <strong>the</strong> availability <strong>of</strong> a SOAP-based Web service API, and <strong>the</strong> ability to integrate its
reports with o<strong>the</strong>r reporting tools.
An important means to determine <strong>the</strong> success <strong>of</strong> a website is to measure conversions. The term
conversion refers to <strong>the</strong> transformation <strong>of</strong> a visitor to a customer (Stern 2002). Extensively used in ecommerce,
conversions can, for example, be defined as <strong>the</strong> purchase <strong>of</strong> a product. The presented
web analytics data analysis excludes all data and respective reports <strong>of</strong> conversions. The reason is
that conversions are difficult to define for social s<strong>of</strong>tware and not <strong>the</strong> focus <strong>of</strong> this paper.
4. Potential benefits for users
The integration <strong>of</strong> web analytics tools in enterprise social s<strong>of</strong>tware environments, as for example a
wiki-based intranet portal, can be beneficial for various kinds <strong>of</strong> stakeholders:
Consumers: users reading content
Authors: users generating new content
Site operators: people administering <strong>the</strong> s<strong>of</strong>tware
Developers: people developing and maintaining <strong>the</strong> s<strong>of</strong>tware
For each <strong>of</strong> <strong>the</strong>se roles we identify potential benefits which can result from <strong>the</strong> integration <strong>of</strong> web
analytics tools with Enterprise 2.0 systems.
4.1 Benefits for consumers
For every user <strong>the</strong>re are typically several contents that he visits frequently. Based on <strong>the</strong> web
analytics data, <strong>the</strong> system could recognize <strong>the</strong>se contents and provide quick navigation links. The
necessary tracking data can be provided by many web analytics tools given that <strong>the</strong> user can be
identified for more than one session, for example by setting a cookie.
Search engines have become an essential part <strong>of</strong> social s<strong>of</strong>tware since <strong>the</strong>y provide easy access to
many kinds <strong>of</strong> information. If <strong>the</strong> data ga<strong>the</strong>red by web analytics tools is understood as implicit
feedback <strong>of</strong> users (Agichtein et al. 2006), it can be used to significantly improve <strong>the</strong> ranking <strong>of</strong> <strong>the</strong>
search results which we will show in <strong>the</strong> next section.
Especially in enterprise social s<strong>of</strong>tware environments users <strong>of</strong>ten share same interests and so <strong>the</strong>y
are interested in <strong>the</strong> same content as o<strong>the</strong>rs. Because web analytics tools are able to track <strong>the</strong>
number <strong>of</strong> views for each page in real-time, this data can be used to easily implement some type <strong>of</strong>
recommender system based on <strong>the</strong> actual interests <strong>of</strong> <strong>the</strong> user base. Beside a search engine such a
feature can ease <strong>the</strong> user’s access to relevant content.
4.2 Benefits for content authors
Social s<strong>of</strong>tware relies strongly on users generating content. While many blogs or wikis allow o<strong>the</strong>r
users to provide explicit qualitative feedback in <strong>the</strong> form <strong>of</strong> comments or ratings, authors do not get
detailed quantitative feedback about <strong>the</strong>ir contributions. With web analytics tools this kind <strong>of</strong> feedback
can be provided. For example, information about <strong>the</strong> readers <strong>of</strong> <strong>the</strong> user’s generated content can be
interesting as well as motivating to generate more content. O<strong>the</strong>r figures <strong>of</strong> interest might be <strong>the</strong> time
o<strong>the</strong>r users spend for reading <strong>the</strong> content and <strong>the</strong>ir loyalty (return rate). These figures can be
presented as numbers or visualized as charts showing <strong>the</strong> progress for <strong>the</strong> last days. Ano<strong>the</strong>r
possible feature is <strong>the</strong> determination <strong>of</strong> a user’s most accessed and maybe most interesting content.
Topics currently interesting for <strong>the</strong> user base might attract authors to contribute to <strong>the</strong>m. With a
sophisticated integration <strong>of</strong> a web analytics tool such topics can be identified and recommended to
authors. In turn authors can also be categorized according to <strong>the</strong> topics <strong>the</strong>y have already contributed
to.
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