The Web Analytics Package Compatibility Test

  |  February 7, 2006   |  Comments

How to determine what Web analytics package your business can live happily ever after with.

Are organizations satisfied with Web analytics systems? A bit of research came out on that topic recently. It reports 62 percent of respondents from large companies were happy enough with their Web analytics package that they would recommend it to others. That seems like a pretty good number to me, but what about the other 38 percent? Aren't they getting what they need from their package? If not, why not?

I've helped a number of companies select and implement analytical software, including Web analytics packages. I went through the painful process myself, implementing a tag-based ASP (define) solution across a dozen sites throughout Europe and integrating it with other information and operational systems. As a result of my work with clients, I've heard lots of stories about why they want to move from their existing packages to different ones.

Common themes I come across include:

  • The system doesn't deliver any value to the business.

  • The system sits in isolation and is difficult to integrate with other data.

  • The system doesn't appear to work properly and deliver what's needed.

  • No one really knows how to use it.

These themes are usually symptoms of a poorly thought-through selection and implementation process for the existing system. The problem may not always lie with the system itself. Often, these issues stem from a lack of clarity about what's really needed in the business and underestimating the associated effort required.

There can be a tendency in selecting analytical systems to be led by the technology and the feature set. As I mentioned last time, funky overlays and pretty dashboards might make the data look good, but you must also ensure you can get at the data you need in the right way.

Here are some thoughts about how to minimize the risk of being among the 38 percent.

Be Clear About Your Goals

Be very clear about what you're trying to do online and the reason for the investment in the Web channel. Everything else flows from this.

Define Your KPIs and Main Tracking Metrics

Once the goals are visible, it's possible to identify what the channel's key performance indicators (KPIs) are. There will also be a number of other important tracking metrics that aren't as strategically important as KPIs. You must recognize KPIs aren't always metrics that come out of a Web analytics package. In fact, they rarely are, in my experience.

Define the Business Processes

As well as defining the important metrics, you must map out and define the important businesses processes. How are campaigns managed? How's the site development process managed? Tools should help the business processes. You shouldn't have to change business processes to fit the tool, unless it's clearly a much better way of doing things.

Write the Business Requirements Document

This is the document sent to potential vendors. The point is to clearly spell out your needs and invite the potential supplier to articulate how her system can meet them. This document should enable the best potential suppliers to shine through, so don't be too prescriptive in approach. A huge document that requires enormous amounts of detail input on every single aspect of the system doesn't help at this stage. You hate writing them, the vendors hate responding to them, then you hate reading those responses. Even then, there's no guarantee you'll be able to distinguish the forest from the trees.

Keep the requirements document concise, clear, and open. Invite vendors to make an effort to differentiate themselves. A vendor once told me the best brief he'd had from a prospect was "This is what we are trying to do, tell me how you can help us do it better." That was it.

Get It Down to Two or Three

From the responses you receive, whittle the list down to two or three potential vendors to pitch the business. Don't invite them all. Look for quality, not quantity, in the response documents you get back. Have they answered the brief? Have they thought about what you asked them to think about? Or have they merely cranked out a document from the proposal machine? Do they demonstrate an understanding of your business and how they can help? Do they appear to want your business more than the next person?

Test It Out If You Can

In an ideal world, you should test at least your preferred system, preferably two systems side by side, to see it in action. Analysis and reporting systems are "experience products." You only really know what you're going to get when you've already got it. Having hands-on experience will be invaluable in helping decide whether this is the one for you, and if you're going to be among the 62 percent of organizations.

Selection, though, is only half the battle. The other half is getting the system in, getting it working properly, and getting used to its potential. Next, I'll share some thoughts on successful implementations.

Till then…

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ABOUT THE AUTHOR

Neil Mason

Neil Mason is SVP, Customer Engagement at iJento. He is responsible for providing iJento clients with the most valuable customer insights and business benefits from iJento's digital and multichannel customer intelligence solutions.

Neil has been at the forefront of marketing analytics for over 25 years. Prior to joining iJento, Neil was Consultancy Director at Foviance, the UK's leading user experience and analytics consultancy, heading up the user experience design, research, and digital analytics practices. For the last 12 years Neil has worked predominantly in digital channels both as a marketer and as a consultant, combining a strong blend of commercial and technical understanding in the application of consumer insight to help major brands improve digital marketing performance. During this time he also served as a Director of the Web Analytics Association (DAA) for two years and currently serves as a Director Emeritus of the DAA. Neil is also a frequent speaker at conferences and events.

Neil's expertise ranges from advanced analytical techniques such as segmentation, predictive analytics, and modelling through to quantitative and qualitative customer research. Neil has a BA in Engineering from Cambridge University and an MBA and a postgraduate diploma in business and economic forecasting.

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