Website analysis and performance improvement

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Archive for the ‘Analysis’ Category

Is exit page really the most useless metric?

Monday, September 10th, 2007

Generally yes. Everybody has to leave a site at some point whether they have completed a task or not.

Once I have bought a flight from an airline website and I have reached the confirmation page containing details and booking receipt my objective has been completed, there is no further reason for me to remain on the site and I will probably leave. I might do this either from the receipt page or I may return to the home page and depart from there. I may even browse for some final piece of information before leaving.

For this reason exit page reports in web analytics tools can often contain as many pages as entry page reports but with varying levels of weighting for each page.

The home page is often one of the main exit points from a site, this in part is because it is one of the main entry points and bounce rate plays a role here as it does in the exit rates of other pages.

The argument for looking at which pages visitors exit from follows the idea that there are pages that don’t do enough to drive visitors on to the next action, as result they prematurely reach the end of their journey and leave because they can’t see what they want or where they should go next.

Mission accomplished or mission aborted…
As already mentioned, there may be mitigating factors for this behaviour. The question then becomes how to identify and filter “acceptable” exits from “wasted” exits.

It now becomes useful to look at exit pages in the context of the preceding two or three pages using a path analysis report.

If 10,000 sessions end on the home page and 2,500 of those are attributable to the bounce rate of that page then there are 7,500 sessions that ended after seeing one or more other pages on the site. If, for arguments sake 1,000 of those sessions saw an order complete page immediately preceding the home page then it can reasonably be assumed that those visitors left having completed a purchase and their mission has been accomplished. That leaves 6,500 sessions where the mission was aborted.

The 2,500 visits that left as a result of the bounce rate have other reasons for not staying and that’s an issue relating to marketing as well as home page design. However of the 6,500 sessions, if a further 4,000 saw the search results page immediately preceding the home page then it is clear that they were not able to find what they wanted and returned to the home page for one more attempt to find what they were looking for before aborting.

Apply this logic to (for example) a category page or a product page and it becomes apparent that there are some situations in which the page has not done enough to meet expectation.

By looking at pages where the majority of exits occur then assessing why they occur, it should be possible to focus resource on exit pages where more can be done to reduce the number of “wasted” visits.

Doing Bad things to get results

Friday, August 10th, 2007
I’ve always worked on the basis that doing calculations using mixed metrics ( by which in this case I mean page views, visits/sessions & uniques) whilst doing an analysis is generally not good. There are some exceptions but when looking at conversion I have tended to avoid calculating it based on page views as a percentage of visits/sessions.

There have been many cases when, in my work with clients, I have faced situations in which their conversion figures have consistantly been a shade higher or lower than my own over a given time period. These have in almost all cases been due to their figures being based on actual sales as measured in their sales management systems whilst I have generally only had access to the analytics data. Not an ideal situation as I would always rather work with actual sales data but it hasn’t been a major concern since the data is generally trended over several months and we are able to see where the changes have occurred – crucial insight has still been available.

In one instance I broke my own rule and took it a step further by looking at the conversion rate using page views to the Order Complete page instead of visits and naturally the figure went up. Of course there are several reasons why the Order Complete page may be viewed more than once in a single visit and not all relating to multiple purchases.

In a follow up session I looked in more depth at regional visitor profiling using weighted segmentation described here. It showed a significant difference in conversion (based on visits only) between the UK and “Rest of World” – not surprising since in this particualr instance overseas delivery was not catered for. However there was a small market oversees that was using the site for purchases to be delivered in the UK.

I got back to thinking about the original difference in conversion between their figures and mine and decided to run a comparative analysis of the Order Complete page based on UK segment and “Rest of World”, this time looking at page views per visit on the Order Complete page and trending over the Christmas period. The pattern became much clearer. Whilst visitors from the UK viewed the Order Complete page on average once per session throughout the period, page views per visit on the Order Complete page for the “Rest of World” segment spiked at 2 around Christmas time.

Rationale? The site didn’t have multiple addresses functionality in the checkout process and so overseas visitors looking to do their Christmas shopping had to repeat the process for each purchase.

I would still be wary of doing this kind of thing but in some circumstance it can yield some surprising and interesting results.

Is a high Bounce Rate always such a bad thing?

Friday, August 3rd, 2007
Bounce Rate (a.k.a. Single Access Ratio) is much used and well known in web analytics. Described simply as the ability of an entry page to retain a visitor after arrival and drive him/her onto another page or goal within the site, it is easy to understand its importance. As the Bounce Rate goes up the apparent ability of an entry page to retain a visitor and solicit another action leading to another page or goal goes down.

It is so important that in Google’s recent upgrade of its analytics tool, the overall profile was considerably raised throughout the user interface. Given the huge uptake of GA this is only likely to bolster its overall profile as a benchmark metric.

Google’s own notes on the Bounce Rate read as follows:
“Bounce Rate is the percentage of single-page visits (i.e. visits in which the person left your site from the entrance page). Bounce Rate is a measure of visit quality and a high Bounce Rate generally indicates that site entrance (landing) pages are not relevant to your visitors. You can minimise Bounce Rates by tailoring landing pages to each keyword and ad that you run. Landing pages should provide the information and services that were promised in the ad copy”

If the resultant action from an observed high Bounce Rate is to make changes to an entry page then it is probably worth setting some additional context.

Without wanting to reduce the status of Bounce Rate in the performance analysis of any site it is worth asking the question of whether a high Bounce Rate is always such a bad thing. It is precisely because of the growing popularity of the metric that it is worth considering its status.

Below are six points which add a bit of context to the Bounce Rate metric:

1. Networked sites with separate analytics accounts (same tool)
Larger organisations may run a suite of sites or micro-sites which complement each other but are not fully integrated. As a result each site may have its own analytics account. There may also be a roll up account sitting across all sites. In circumstance like this a visitor arriving on one micro-site from PPC search may then move straight onto another if there is relevance and an available link. This may be an entirely desirable outcome but the Bounce Rate report in the analytics account for the original site will show the visit as a single page visit and therefore contribute to a higher Bounce Rate. In this case it is worth looking at the same page in the roll up account to get a better idea of the overall Bounce Rate.

2a.Variations: Home Page, List page, product page
As with many reporting metrics in web analytics, averages can sometime be misleading. The same goes for Bounce Rate. The Bounce Rate will vary considerably between different types of page. Generally it is likely to be lower on the home page and increase the deeper into the site the entry page is. So a category page will have a higher Bounce Rate and a product page Bounce Rate will most likely be higher still. As the pages become more focused and less generalised there is less to encourage a visitor entering to look around. If they don’t see what they want immediately it is easier to go back than forward.

2b.Weight of entry visits
The previous point has greater relevance when linked with the weighting of entry visits. In an extreme example, if 90% of visits enter on a home page which has a Bounce Rate of 10% and the other 10% of visits enter on product pages which have a Bounce Rate of 90% there is clearly little point in diverting resource to address the Bounce Rate issue on the product pages. The overall site Bounce Rate will be low anyway and until the landing strategy changes to make more use of product pages, or better still landing pages, there is little point in diverting resource.

3. News & media sites
Bounce Rate may be viewed very differently when looking at news and other media sites. Peaks in traffic on these sites often occur on week days at around 9am and again at around lunchtime. Visitors may often come in, take a quick look at the home page headlines and leave again. This would be enough to get a quick fix until there is time to read more. As lifestyles become busier and more time pressured this kind of activity is less surprising. On the web this would results in a high Bounce Rate. The solution might not be to encourage the visitor to delve deeper (thereby lowering the Bounce Rate) but in fact to make sure visitors can get exactly what they want on that fleeting visit thereby ensuring they continue to return for their fix. Bounce Rate has reduced status here.

4. Brochureware sites / offline calls to action (web-centric telephone numbers)
Some sites may not have a business goal that can be easily measured online. The desired action may require a telephone call. In this case it is possible that a landing page could supply all the required information for a visitor to take the decision to act and pick up the phone – hopefully to dial a telephone number that is unique to the website or landing page. High Bounce Rate + desired outcome.

5. Traffic source: Banners Vs PPC entering on a landing page
Just as different entry points have different Bounce Rates the same entry point may have different Bounce Rates depending on the sources of referral traffic. One landing page may be acting as a receptor for an advertising campaign which uses both online display (banners etc) as well as pay per click search (PPC) advertising. It is quite possible that banners may direct the greater volume of traffic and have a lower Bounce Rate whilst PPC may drive a lower volume with a higher Bounce Rate yet despite this the overall volume of good outcomes may still be low. In this instance it would be worth looking at overall volume of good outcomes for both referral sources and see which has the better conversion rate – sometimes the effect of a higher Bounce Rate can actually act as a quality filter to weed out the wheat from the chaff.

Making more of segmentation

Friday, July 13th, 2007

A thought: Who among us is NOT an individual?

Solutions implemented to improve site performance will not always appeal to everybody.

The average conversion rate may rise (and fall) but really there’s no such thing as an average conversion rate. Performance and conversion rates become more useful when they are segmented based on audience type.

Audience types can be defined and segmented in many different ways and people who buy advertising space spend their lives thinking about this. In web analytics segmentation is based on actual observed behaviour and leaves less to guess work. Segmentation ranges from how a visitor found your site to what they did on site. Depending on the level of sophistication of the analytics tool, cross segmentation can be used to obtain even better insight. Segmentation can then be used to represent groups of visitors with different objectives and levels of motivation.
Developing some understanding of visitor motivation helps minimise the risk of losing customers and maximise the potential for retaining new and existing customers.

It also helps to give some kind of weighting to your segments. This makes it easier to know where to concentrate resources.

A 3 dimensional bubble chart can help visualise this (you can click on the chart to enlarge).

In this example the Y axis shows the conversion rate within each segment based on a specific KPI; the X axis shows, as a percentage, the contribution by each segment to the total volume of good outcomes; the size of the bubble for each segment effectively acts as the weighting metric – the larger the bubble the bigger the weighting in context of all site visits.
By creating this chart it’s possible to see which segments are the heavy hitters and which have the most potential. It also gives more meaning to scenarios when the segments are overlaid on them.
Segments and scenarios
Scenarios are created to understand visitor behaviour by looking at conversion through the scenario. If several different segmented visitor types are overlaid on a scenario it’s possible to get a much richer insight into levels of motivation.


In this simple two step example scenario, it’s possible to see how the various segmented sources of traffic convert on a comparative bases. (Click to enlarge)

As I’ve already mentioned, once you start looking at segments overlaid on to scenarios, it may help to cross reference some of them to gain deeper insight. For example, say 40% of your traffic entered on the home page and 40% entered on a product page and you’ve created segments for each to see how they convert; then assume 50% of your traffic comes from organic search and this source generally converts well. You may then want to know how does traffic from organic search that enters on the home page compare with traffic from the same source entering on a product page? More importantly even if one converts better than the other does that mean the poorer converting group has no value? Not necessarily – they may just be looking for something else – check the search terms they came in on, look at the bounce rate and so on.

As more on and off-line marketing is tracked by campaign tracking and bespoke landing pages segmentation will surely become increasingly important in assessing performance and value for money. I have already experienced this with several clients.

Any thoughts / comments please do post. Many thanks.