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Stickiness and Loyalty

Stickiness has traditionally been viewed as a measure of engagement, success, satisfaction and loyalty. If someone spends a long time on a visit or repeatedly visits, then the site might be regarded as 'sticky' and that could be considered a good thing. This is especially the case where the site is not engaged in direct selling; if the value of the site cannot be measured by the revenue it generates then perhaps the value may be measured by the users it detains and retains. In the context of Europeana, however, we need to tread more carefully as it is more of a gateway, portal or search engine than a destination site, and it could be argued that Europeana's main task is to pass on visitors to the original version of the digital object at a provider site, at a healthy rate of knots.

First, let us provide the necessary general usage data as a context to the stickiness investigation. How is overall usage going over time and what patterns can we see? Comparing the more regular and settled periods: autumn 2011 (Aug–Jan) with autumn 2012 (Aug–Jan) (Fig. 3) a clear picture emerges with visitor numbers growing healthily by 120 %. The numbers have been growing steadily since July 2012, but the gain 2012 over 2011 was most marked in November. The peak of activity on weekdays compared to weekends is greater, and there is a more pronounced fall-off in activity toward the year-end. The rate of growth has increased compared to a year before, so it appears to be accelerating.

Figure 4 charts the daily visitor count 2010–2013. Note the seasonal pattern which follows the rhythms of the school and academic calendar, the drop each weekend and holiday, and—despite perturbation—the steady spiral of growth.

Fig. 4 Europeana daily visits 2010–2013

Returning Visitors

Stickiness has most often been associated with site loyalty and the propensity of people to revisit. Returnees, unlike dwell time, are definitely a quality metric. We have not been able to undertake this analysis before on Europeana because of an absence of cookies in the raw logs (the surest method for identifying revisits). These cookies are available in the 'ClickStream' series, but only from June 2012, so we are really limited to GA data. As mentioned earlier cookie-based visitor identification is not 100 % reliable: cookies may be deleted; the same person may access the site from more than one browser. It is therefore probable that there is a systemic overstatement of 'New' and 'Unique Visitors' and a corresponding under recording of returning visits. But we do not know the extent of this and given the relative importance of this metric, far more meaningful than a Facebook 'like', for instance, Europeana hopes to do more research to establish its real significance, by triangulating the data with demographic, survey or qualitative data.

Only one in four visitors return to Europeana, as compared to two out of five for a typical publisher website. This says something about dependency. Within that 25 %, 10 % return only once, 4 % make three visits, 2 % four. Nine per cent of visi-

Fig. 5 Europeana: return visits. (Source: GA)

tors returned five times or more. GA may understate the return rate a little but the distribution follows is a typical 'power law' (Fig. 5). This suggests that Europeana's core audience, defined as those people visiting five times of more, is about onetenth the size of its visitor numbers—about 500,000.

When looking at returning visitors it is well to remember that most visits are very fleeting; even when bouncers (one visit, on view) are ignored many returning visits are measured in seconds rather than days. So strong is this phenomenon that it is difficult to convey on a single chart. The following three charts (Figs. 6–8) are derived from a single dataset, a sample of 600,000 visits made between June and December 2012. These are visits selected because the Google cookies were present and contained timing data for a previous visit. The Google cookie expires 2 years after the last visit so first we look at a timescale of 24 months. In many cases the cookie will have been deleted earlier so the evidence of long-term use of Europeana will be understated. Nonetheless we do see evidence of users who first used Europeana over two years ago, and even a few who have recorded no other visit in the intervening period. But these are counted in single figures compared to the thousands who return within a month (Fig. 6).

When we look even closer (Fig. 8), at those visitors who return within three days rather than months an interesting pattern can be seen. Regular users appear to have a daily routine; there is a distinct series of peaks in the graph at 24, 48, and 72 h. In fact, equipped with this insight, we can turn to a daily plot (Fig. 8) and see the same

Fig. 6 Europeana: months between visits. (Source: GA)

daily routine persists through a whole month. It is also possible to see traces of a weekly cycle: the daily peak is a little higher at 7, 14, 21 and 28 days.

One explanation for this phenomenon is that a significant part of Europeana use takes place within institutions using browsers set up in kiosk mode. However, even when the data is reprocessed with a filter to remove the most obvious heavy institutions referrals the daily pattern persists.

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