On The Trail

There has been a ton of discussion on the Yahoo group about Tealeaf, particularly why and how it is different from traditional Web Analytics apps. Since I’m familiar with both, I thought I’d give my perspective.

Tealeaf collects everything. I mean everything. Every cookie, every image request, every bit of information entered in forms, everything. Their bread and butter is allowing you to replay single sessions to see exactly what happened. It is an amazing tool in this regard. It has extremely powerful search capabilities that can sift through millions of requests and turn up the few that have the exact characteristics you’re looking for. Do you want to see all the sessions for people with customer numbers between 55550 and 55562? Tealeaf is your tool. Do you want to see what happened at 6:10 last night? No problem.

It also has very nice monitoring capabilities. You can fire an “event” if a particular sequence of actions take place on your site. We use it to monitor for a few rare but serious errors that crop up from time to time. Some use it to monitor for fraudulent activities or hacking attempts. The event can send an email or just flag the session so it is easy to find. I use events to find pages that do not have analytics tags on them. Tealeaf has fairly rudimentary reports that show how many and when events occur.

We also use it for ad hoc web analytics requests that would otherwise require a tag change. It’s not made for operational reporting, but if we want to figure out a particular question without going through the whole IT rigamarole Tealeaf is often ideally suited to do this.

Tealeaf also has a module called cxConnect which allows you to export all this information to a database. Every day or every hour or whatever it will spit it all out into a SQL Server database. At first glance this seems like a killer web analytics application  — just imagine, every little detail of all activity on your site all organized nicely for you in a database!

That is great until you give it about 30 seconds of thought. Sifting through this data is a herculean task. There is no way you have enough disk space to keep it all, so right away you need to write some sort of ETL to pick out what you need and compact the rest.  Then you need to replicate all the reports that a web analytics platform has out of the box. Will you end up with something better than you’d get from Omniture or WebTrends? Yes, you probably will, if you have smart data warehouse architects and good technical resources. If you don’t have both these you’ll end up with a large pile of useless crap. Will you end up spending way more money and time creating and maintaining this system than you would by buying and implementing Omniture or WebTrends? Absolutely, probably many times more.  Will it be worth it? Who knows. If it works it would be awesome. If it doesn’t… well, there are a lot of web analytics jobs out there, right?

The strength of the traditional web analytics applications is what they don’t show you. They sift out all the junk that you don’t need to see and they’ve created a bunch of reports that present the information that is useful. Someone else worries about the data storage/retention problem. It’s all built into your very predictable monthly fee. They may not be perfect, but they are pretty good, and buying one of these is much safer than embarking on a huge data warehousing project. As we all know there is a ton of detail in web data that is totally useless 99.9% of the time. Tealeaf lets you efficiently find that 0.1% – and that alone is more than enough to allow it to pay for itself.