The working life of Museum of London

In my last post on this topic, I explained that I gathered a number of web statistics for the Museum of London website (MOL) and the Museum of London blog site (this site referred to as MyMOL). Below is a brief explanation accompanying each area for which statistics were analysed during the reporting period (the web statistics gathered, analysed and compared were for the duration of one year from 1 April 2008 to 31 March 2009):

• Unique visits – “typically consists of one or more page views”
• Unique page views – “the number of times a page was viewed”
• Unique visitors – people “with activity consisting of one or more visits to a site”
• Repeat visitors – “unique visitors with activity consisting of two or more visits”
• New visitors – “unique visitors with activity including a first-ever visit to a site”
• Average duration of visits – “length of time in a session”
• Referrals – “the source of traffic to a page or visit”.

(All definitions from Web Analytics Association)

The results

I found from my results that during the period of analysis, the total number of unique visits and unique visitors to MyMOL was equivalent to 1% of those on MOL, and the total number of unique page views to MyMOL was equivalent to 0.5% of those on MOL.

This was despite the fact that MyMOL never received any publicity and was still very new in comparison to MOL.

The trend in visits, visitor numbers and page views for MOL and MyMOL showed that though the pattern for MOL and MyMOL started of differently in the first three months, by the fourth month the pattern on both sites were very similar.

Figure 1: Trend comparison for MOL and MyMOL visits, page views and visitor numbers

I also discovered that the trend for repeat visitors to MyMOL started of much higher than MOL, but by the end of the year of analysis, the repeat visitors to MOL was in significantly in the lead.

Figure 2: Repeat visitors trend for MOL and MyMOL

To try to answer the reason behind why that may have been, I looked at some possibilities:

• MOL has rich and engaging content
• MOL is a larger, well established & well publicised in comparison to MyMOL
• MyMOL was unavailable between December 2008 and January 2009 when there were technical problems that resulted in content migration
• The number of posts published on MyMOL during and post content migration was much less than before and since the analysis period
• Visitors may have made visits from more than one computer, or have different IP addresses, or have simply deleted their cookies.

One of the problems with looking at repeat visitors as a form of analysis on the level of engagement with a site is that if someone is repeatedly coming back to a site, it does not necessarily mean they enjoyed their visit. It could simply be that they did not find the information they were looking for the first time. Therefore, even though both sites received a large number of repeat visitors, it did not conclude that all repeat visitors returned to the websites for more information because they were interested in the content.

However, for this particular study, I concluded that MOL looked to be more engaging and able to retain its visitors more than MyMOL.

The new visitors to MyMOL, on the other hand, were exceeding the trend of MOL by the end of the year of analysis.

Figure 3: New visitors’ trend for MOL and MyMOL

This is important on one level as “the number of new visitors you are able to attract to your web site is a direct measure of the efficacy of your reach” (Peterson 2004).

Average time on site

Analysing the average time visitors spend on websites can be interesting. However, the conclusions drawn can be both positive and negative, for if visitors spend much time on a particular site, it can be encouraging as it can show that visitors are engaging with the content and are interested and consuming information. On the other hand, it could be negative and show that visitors cannot find what they are looking for, and so are spending the time trying to find information.

Looking at the trend for the duration of visits, the average time on MOL appears to be much steadier than that on MyMOL.

Figure 4: Average time on site trend for MOL and MyMOL

There appears to be some similarity in the pattern for the seven months in the middle of the year of analysis, however, the actual rise and fall in the average time spent on MyMOL is significantly uneven. There appears to be huge drops that follow large rises, with no apparent reason that can be seen from the web statistics alone.

There is the strong possibility that a single page was viewed on MyMOL during a visit with a timestamp for the start of the visit (which as a blog site, I thought it may have been the case), but as there were no more visits to other pages, the time spent on that single page may have been zero.

New audience for MOL

A new audience for MOL website would determine the success of MyMOL because it would prove that there are values in having social software sites such as blogs that can be quantified. This can be tested by looking at the number of new visitors that are gained through referrals from MyMOL.

I saw from the new visitors and unique visitors trend that MyMOL is attracting at least 1% of new audience for MOL that may or may not have visited the MOL website before.

Figure 5: Actual number of referrals from MOL to MyMOL and MyMOL to MOL

Looking at the actual number of referrals from MyMOL to MOL website and vice versa, it is very clear that firstly, there are not many referrals being made between the sites, and secondly, the referrals that are made, are of similar pattern on both sites.

Only 0.065% of all visitors from MOL went on to visit MyMOL in the year of analysis, whilst 4.85% MyMOL visitors ended up on MOL. So if visitors to MyMOL were to increase, the possibility is greater that more new visitors will end up on MOL.

However, increasing visits to MyMOL alone is not enough to retain visitors or to refer visitors onto MOL. It is about writing good content on MyMOL that provides relevant links to MOL website and encourages visitors to go there.

I actually took this to be the most significant of findings in my results as it made me ensure that more blog posts were written regularly and that every single post had at least one link back to the Museum of London website.

Enquiries and comments

To look at the level of engagement on each site, I had also looked at the number of email enquiries to info@museumoflondon.org.uk that came via MOL as a proportion to the number of visits on the website. The average enquiry per visit for the year turned out to be 0.0027 enquiries for each visit on MOL.

On MyMOL I looked at the number of comments over the year as a proportion of the number of visits and it turned out to be that there were 0.0041 comments for each visit. Both of the averages are very small. Nevertheless, the average level of engagement on MyMOL is double that of MOL.

To conclude

Well written content and regularity of posts is vital for the success of a blog site and to increase visits to the Museum website, well placed links back to the site must be in each post.

References

Black, G. The engaging museum: developing museums for visitor involvement. Routledge, 2005. Print.

Peterson, E. T. Web Analytics Demystified: a Marketer’s Guide to Understanding How Your Web Site Affects Your Business. Celilo Group Media, 2004. Print. p.110

Web Analytics Association. (b) “Web Analytics Definitions.” Web Analytics Association. 22 September. 2008. Web. Accessed 21 August 2009. <http://www.webanalyticsassociation.org/attachments/committees/5/WAA_Web_Analytics_Definitions_20080922_For_Public_Comment.pdf>