Avinash has posted a week ago a new Web Analytics tip on his blog (Excellent Analytics Tip #8: Measure the Real Conversion Rate & “Opportunity Pie”) and
Avinash’s tip presented 3 ways of increasing the conversion rates to which John disagreed (I rephrase and simplify their statements, so if you feel I got it wrong, please feel free to comment):
1. Use bounce rates
Avinash advises to look at bounce rates and non qualified visits that spend too little time in your website and don’t count them when calculating conversion.
John dosen’t agree with this statement and says that it’s like if you have a high crime rate, the best way to lower it down is to legalise crime.
IMHO, this last assertion is a bit easy. When I look at our clients websites many of them have bounce rates in their home pages ranging from 20% up to 70%. I don’t think that you can consider this traffic qualified and I agree with Avinash’s point of view as it’s more accurate (I won’t say perfect as we all know that 100% accuracy dosen’t exist) to take them out of your calculations.
Let me give you the example of our Webanalytics.be website. The bounce rate of the Home page of visits coming from France is extraordinarily high and I know the reason: french like to read in french and our website is in English. The only way to solve this is to translate it in French (working on it for our next release) but in the meantime I don’t see the point in counting them in my conversion rates. A few months ago we got a link from a big french website and during one week the visits from that source were the majority of the website visits. But as expected most of them left after seeing that our Home Page is in English. This increased dramatically the number of unique visitors (and visits) reported in the different WA tools that we use but on the other hand my conversion rate decreased by 2/3. From my point of view it makes sense to take out those ‘non qualified’ visits from my CR calculation, as the reason of the decrease is not a problem in my website but from where the visitors came from. So this takes out the noise caused by the different acquisition strategies that will evolve with time.
Besides the bounce rate, another metric proposed by Avinash to define a qualified visit, is to take into consideration only visits lasting more than 10 seconds. John didn’t agree neither with this tip as he said that for example “When you go to Amazon.com to buy a book, do you stare at the site for 10 seconds, waiting to be convinced? Or, already familiar with Amazon’s fairly standard navigation, do you instead quickly type in the book/DVD/gadget you were actually looking for?”. While I agree with John’s explanation I think there’s a problem in the understanding of the 10 seconds tip. I don’t think that Avinash meant that people needed to stay 10 seconds without doing anything else but being persuaded. A returning visitor can of course do things quickly, and nobody expects every visitor to stare at the first page for 10 seconds, but I don’t think that you can buy a book on Amazon in 10 seconds even with their one click buying solution (or you’re really really quick). The 10 seconds must be seen as a way of eliminating the noise from unqualified visits/visitors.
2. (If you use Web Logs) Filter out search bots, image requests, 404 errors, website monitoring software “visits” etc.
This tip provided by Avinash is criticised by John as he says that since 1999 the advice was out there. Yes it is true that it’s been there for quite a long time. But let’s be honest it’s not yet followed by everybody. I know lots of companies here in Europe that still use Web Logs for their Web Analytics (and not only little SMEs as I know for example one of the top 3 top world banks!). I even have competitors in the Belgian market that use this technique as a general practice and say that Web Logs are comparable to Tagging. It’s like the 1st/3rd party cookies issue, while I understand that most of us are sick and tired of hearing it, this dosen’t mean that everybody has got it right. IMHO Avinash’s purpose being to help not only the skillful website owners but the majority of them, it makes sense to find this advice there.
3. Use Customer Intent
Avinash explains that not every visitor comes to your website to convert. John disagrees with this assertion and for him every visit is a chance to convert. And if you don’t agree with this is that you don’t do your scenarios right. While I respect and admire a lot Future Now’s work around Persuasive Architecture and the notion of setting scenarios beforehand, let’s face it this is not always done. Not every client has the possibility to invest in PA and definition of scenarios (at least here in Europe there aren’t many of them). And most of the companies I know that use scenarios, use them only for certain goals (the important ones). For example are you going to build a scenario for the students that come to your website searching information for an academic paper? Are you building scenarios for the competitors that come to your website to understand what you’re doing?
Persuasive Architecture and Scenarios are a great thing but as many tools available (I’m thinking of MVT for example) they are not used by the majority of website owners. Avinash intention is to help a maximum of people around there and as said many of them are not (yet?) using complex and costly techniques. When I look at Belgium or France, most of the companies I’ve seen don’t even use KPIs or conversion rates when dealing with Web Analytics, they just look at visits, visitors and page views!
John, don’t get me wrong, I understand your concerns but let’s be frank, the market is really behind in comparison with the knowledge and expertise available. And I’m sure that Future Now even if it’s present in a huge market (US) is providing services mainly to large corporations that can afford their services.
Avinash, if I may I would like to share another way of dealing with your third tip ‘customer intent’:
Not everybody can have access to market research or accurate surveys. Another way we use at OX2 to exclude certain visits from conversion calculations is the content that they access. Take for example a forklifts website. The persons interested in this kind of goods are mainly large corporations and you can assume that visits from a university IP range are not likely to buy anything; same thing applies to people that come to the website and have a look only at the corporate section and mainly the jobs offerings. If you understand your business and your potential buyers you can define different rules that you will use to exclude traffic from your CR and thus have a more insightful figure. And let’s not forget that the most important thing is to look at the trends of your conversion rates over time once they have been clearly defined and that you have filtered out what you consider to be noise for your conversion rate (not every website is alike so rules might be different in different cases).
This is my point of view and as always coments are welcome, specially if you disagree 😉