Internet Banking Web Analytics

Internet Banking is a different arena of web analytics, which require a totally different perspective and problem solving capabilities. The rest of the article will talk about some problems and solutions in such areas.

In traditional ecommerce sites, KPIs and key metrics are tracked by setting up page-tracking and Goals. Users are tracked through funnel process, like movement from one page to another page until the sales confirmation page. Usability and productivity of the page is evaluated by bounce rate, exit rate, conversion rate and click stream behavior on each of these pages. 

However, consider a case of Internet Banking, it is very interesting that such funnel navigation or bounce rate gives a very little information about its effectiveness, here is why? Lets say a user has a bank account and is using Internet Banking for transaction.

There are various things are tracked to understand his behavior, a person who wants to transfer funds from one account to another will do it even if it is a difficult process and does not fully understand, a user will try and figure out the ways to understand process and transfer funds online. Therefore the drop out rate in funnel navigation is very less, unlike ecommerce sites. Most users will inevitable complete the funnel and navigate all important pages to reach thank you page, even if they do face difficulties. They would invariably figure out how to do a transaction online.

The problem for web analytics guy is, a lot of users seem to be using internet banking very well but how do you find out where exactly is the problem, what needs to be mended.

Here are some areas of data to be looked into, that gives us insights in this direction.

1)     Pageviews of Error pages.

a.      How many times error pages were thrown up?

b.      Source of error pages, which page led to error pages most and their ranking.

c.      Errors per transaction.

2)     Pageviews of help section and FAQs, which part of help section was most viewed and their ranking.

3)     Total Pageviews per page per transaction. Example, a fund transfer has 4 pages, how many times each of the pages were viewed per transaction.

4)     Offline feedback on errors and complaints on Internet banking transaction.

5)     Average time taken per page online

a.      Rank pages on average time per transaction

6)     Number of fraudulent transactions or security complaints.

These are my personal views and opinion on this subject. Please do let me know your views as comments.

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