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How Web Analytics Helped Find A Million Dollar Hole
Web Analytic Solution
by Steve Jackson
I’m often asked how we go about using web analytics to really pinpoint
problems that make the tools worth the investment. Many people are dubious when
asked to fork out $50,000 a year to have reports about how people visit their
website. What I’m about to describe is a situation where one of our clients could
potentially earn $1 Million per year because of the analytics tool they have
installed. This article will describe how we used a key performance indicator to
raise the problem and then go onto describe how we then found out what the issue
was on the clients website.
The Key Performance Indicator or KPI
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Ahh the KPI! It’s the latest buzzword flying around in the industry. What key
measurements to use is an important point, but much more important is how you use
them. One KPI I have written about before is page views per
visit. It's a KPI I always use regardless of the site goal because it’s what
I refer to as a tripwire metric. Like a tripwire it gives you a warning when
something is not right.
Setting up the tripwire
The way you should use this KPI is to first find out how many pages it takes to
complete the desired action. In this case the desired action (a purchase) took a
minimum of 7 pages. Then consider what a good browsing experience might be from
your businesses point of view. In this case we figured if the visitor viewed 5-7
pages and then completed a purchase (another 7 pages) it would be a good visit
from the businesses point of view. It means that the visitor finds out that more
is on offer than simply the product they were looking for.
Then we added another
7 pages on top of this to flag a too many pages warning. So we have a bottom
limit of 7 pages, a happy medium of 14 pages and a top limit of 21 pages.
|
Savvy web analytic solution and
how web analytics helped find a million dollar hole
explained here by Steve Jackson
|
Why is too high a warning?
 In this particular case when an average visit to the website was more
than 14 pages in our view it meant one of two things. Either the visitor is
extremely happy with the website and is browsing around or the visitor is
extremely frustrated and can’t find what they want. A good experience from any
visitors point of view on an e-commerce website is that they find what they want
very quickly and in this case we figured that should mean browsing less than 21
pages on average. What we found shows why this metric is important. The KPI went
off the scale showing that on average a visitor viewed 22 pages per visit.
The next job was to figure out whether this was a good thing or a bad thing.
If an average visit took 22 pages it meant that either the visitor was happily
browsing around and our client should be very happy, or it meant that there was a
problem and if so we needed to find out where.
Good or Bad? Happy or Sad?
The KPI had raised the warning signal so we now needed to find out which
visitors this KPI applied to. In HBX (and many other tools) it’s possible to
segment the visitors into groups of people that follow the same behavior
patterns. We wanted to know if the visitors were flicking through pages very
quickly (a sign that they were unhappy) or if indeed they were traversing a great
many pages each and spending a normal amount of time on the site (a sign that
they were happy).
Therefore we segmented the visitors into only those that spent less than 2
minutes on the site and those that visited the shopping cart. This would enable
us to see if the page views per visit of those visitors only on the site for a
short period of time were racking up lots of page views or whether it was those
that hit the cart that had trouble finding what they wanted.
|
Savvy web analytic solution and
how web analytics helped find a million dollar hole
explained here by Steve Jackson
|
Less than 2 minutes showed normal behavior. The people that spent less than 2
minutes on the website generally browsed 2 or 3 pages per visit. The people that
hit the shopping cart again went off the scale but this time it was even more
problematic. The average page views per session was 58 pages. We’d found the
people who were having problems.
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58 page views per visit?
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HitLens is a much more affordable real-time tracking
web analytic solution for your site.
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Since we’d found the visitors who were having the problems we now needed to
know what they were doing. How on earth could people be going through 58 page
views on average each? It seemed unlikely – we even asked the developer to check
that the tracking code was correctly installed. However when we checked the path
analysis the problem on the website became crystal clear.
One visitor had traversed 97 pages. We looked through his visit path and
noticed that the path kept referring to one page – a search results error page.
We checked other individual visits and noticed the same key trend – the search
results error page.
|
Savvy web analytic solution and
how web analytics helped find a million dollar hole
explained here by Steve Jackson
|
This lead us to check the failed searches on the website. When we totaled
them up there were over 2000 failed keyword searches and the big majority were
product codes. The sites internal search engine simply couldn’t read a letter and
number combination and most of the product codes consist of numbers and letters.
We’d found the problem.
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HitLens is a much more affordable real-time tracking
web analytic solution for your site.
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The solution therefore is to fix the search engine. This one fix is a
potentially huge find. There were over 1000 people that keyed in those failed
keywords and didn’t complete the purchase. Our customer brings in over $160,000
per month in online revenue from a little over 1700 people that did complete a
purchase. That means by doing a little mathematics it’s easy to work out the
potential. It’s well over $1 million a year in lost revenue.
|
HitLens is a much more affordable real-time tracking
web analytic solution for your site.
|
Summary
It’s easy to worry about the cost of a web analytics system. They are
expensive and with everything that most businesses have going on they aren’t easy
to get the most from. What you really need is an in house expert looking at the
systems to pin point the problems or outsourcing to a consultancy to get the most
from the systems. However to not use web analytics is like throwing away money –
a frustrating and expensive waste of time.
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02-17-2010
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