DSC00115 small1The post on questions to ask WA Vendors started with a observation that it is perhaps more important that you ask yourself a few questions before you get into the Web Analytics tools selection process. These questions would help you understand your company needs in a very unique way which would help you pick the right tool.

The core point of that argument is simple: Most tools selection processes have very little self reflection built in, they might even be cookie cutter processes that might be from some book (or worse from some random blogger!! :)). This is not optimal.

Each company is unique and your approach to picking the right tool should be preceded with a lot of self reflection to ensure you understand who you really are and what you really need. (The “radical” selection process recommended in a earlier post forces this self reflection.)

This post covers three questions that should prompt the kind of critical self reflection that should increase the possibility that you’ll pick the right web analytics tool for yourself.


    # 1: Do you want reporting or analysis?

    # 2: Do you have IT strength or Business strength? Or Both?

    # 3: Are you solving for the Trinity or Clickstream reporting / analysis?

Now the questions, context and an attempt at providing some guidance…..

Do you want reporting or analysis?

    This is a very difficult question to answer because most organizations have a very hard time being honest about what they need, humans are also poor at being self critical.

    The other reason this is hard is that its like asking if you like a $0.99 Hershey chocolate bar or a piece of L'Artisan du Chocolat. It would be a sin not to say L'Artisan du Chocolat.

    Everyone wants analysis, yet few organizations (especially ones that are greater than 100 people in total size) actually want analysis. They want reporting.

    There are numerous reasons for this, including:

    • Decentralized decision making.
    • Company cultures (consensus, “cover your back”, layers of management, matrixed, paperwork driven and so on and so forth).
    • Availability of tools / features. History.
    • Propensity of risk (as in no propensity to take risk and risk taking actually harmful for career).
    • Distribution of knowledge in people / teams.
    • Availability of raw analytical brain power.
    • And more….. (suggest your own in comments below).

    measurementThe bottom line is that while everyone actually says that they want analysis. Admitting that you simply want reporting would be a sacrilege. Yet most companies simply want reporting. They want a web analytics tool and a web analytics team that simply facilitates reporting that is requested from Marketers, Business Leaders, VP’s, CMO’s and others.

    The web analytics team might be told that they should provide analysis (remember given a free choice no one will opt for the Hershey’s bar), but they are not set up to have time or knowledge to provide analysis and if by their free will they do provide analysis then it rarely translates into acceptance and action. Success of the web analytics tool implementation is measured by the number of reports it provides, the number of KPI's it is pushing out, the number of Marketers who say they are getting reports.

    If you are deciding on what web analytics tool to choose you should take a really hard self critical look at your company, its decision making structure, its needs and then be honest and decide if you want reporting or analysis. Then decide on what tools in your selection criteria are good at reporting and what tools are good at analysis. Ignore the category you are not interested in (usually analysis).

    This is a really hard choice to make, even harder to justify (because everyone thinks they want analysis). But having the tough conversation will ensure that your company will be happy with the choice that it makes, it will in all probability save money (reporting tools are much cheaper) and it is highly likely that on the long run you will be successful.

    You choose the wrong tool (say a true analysis tool), it will only turn choice smallpeople off the tool and using data (because it will suck at reporting) and on the long run hurt you a lot more. You choose the right tool for your company (say that is really powerful at reporting) and you will glean a lot more traction since atleast they will look at something and your web analytics people will know what they are getting into. Over time your company, if the culture and org structure and risk taking are all lining up, will get smarter and maybe you’ll be ready to move to a analytical tool.

    I am going out on a limb here but currently there are potentially only two true analysis tools: ClickTracks and VisualSciences. They come at massively different price points and have a very differentiated set of features and performance (speed, complexity, depth and breadth, sexiness). They are both right for the right kind of organizations, in case you decide you are it, and both need a deep self reflection on your part before you send a chq.

    Other tools are also making great progress getting there, empowering true analysis out of the box to complement their far superior strength in being able to do awesome reporting.

    IMPORTANT: Hopefully you’ll see that there is no judgment being made above if reporting is better or analysis is better. Each serves its purpose. The emphasis is on figuring out what you really need and then buying what you really need.

Do you have IT strength or Business strength? Or Both?

    strength smallSome companies are good at IT (technology), others are good at the Business side of things (marketing, analysis, strategic decisions etc etc). A rare few are good at both, or have environments where the two are the same when it comes to Web Analytics.

    Pulling off a successful web analytics implementation is complicated and it is often easy to get it wrong. A professional services company recently shared with me that seven out of ten times they find the tool implementation is wrong (and the client has not known about it for a while, and have been using wrong data).

    If you have solid IT (technology) and Business strength in your company then go at it all by yourself and you’ll be fine (here are Web Analytics Technical Implementation Best Practices).

    If you don’t have strong IT strength (by that I mean IT who knows and gets Web Analytics and not just standard IT) then go with a partner, say my buddy Justin at EpikOne  (Justin let’s talk about my cut of this deal! – all joking aside I have not financial or other ties with EpikOne).

    If you don’t have IT strength and you don’t want (or can’t afford a consultant) please consider following this process: How to Choose a Web Analytics Tool: A Radical Alternative.

    Here is one last reason to assess IT strength: if you want to do in-house and not asp. If you want to consider hosting the data collection and analysis in-house (say with WebTrends, ClickTracks or Unica NetInsight) then you need some serious IT/Technology strengths (in atleast one person) to pull it all off. Ensure that you are covering this important consideration.

    If you don’t have strong Business strength (realize that just by figuring this out honestly and you are already ahead of your peers) consider following this process: Web Analysis: In-house or Out-sourced or Something Else. It provides a great framework for the evolution of a effective and efficient web analytics program.

Are you solving for the Trinity or Clickstream reporting / analysis?

    This is a mind-set question. It is a question that tries to judge what you are solving for. It tries to get to help you understand the level at which you are approaching the solution set. It is all about trying to know if you need to buy a tool that will help you “understand clicks” (which is ok) or do a lot more than that. It tries to help you crystallize what your short term goals are and what your long term goals are.

    trinity web analytics strategy1

    The Trinity mind-set & strategy calls for having a robust Qualitative and Quantitative analysis in your web analytics approach with the goal of: Understanding the customer experience explicitly (via Research), to then influence customer behavior on your site (via Clickstream analysis), leading to win-win Outcomes (via outcomes analysis) for your company.

    Your consideration criteria will be vastly different depending on where you are and what your own point of view and approach is in this context. In one case a simple log parser is fine, in another you need a tool that integrates with other data sources and in yet another case you need a tool will pay ball with your data warehouse.

    See this post: Web Analytics Tool Selection: 10 Questions to ask Vendors. The questions you’ll ask and what you’ll stress with change with the answer to the question above.

That’s it. Three questions.

A bit of my own self reflection & guidance:

I  am on record saying “don’t spend too much time on worrying about web analytics implementation, turn on Google Analytics on your website and follow a simple, but “radical”, process”. Given that I feel a bit embarrassed at publishing two consecutive posts on Web Analytics Tool selection.  Both posts combined I suspect highlight how complex the process of selecting a tool can be. To some of you it might even look scary as to how much thought you need to put into selecting the right tool for your company.

four steps small1To put a nice bow around all this (and to make it easy for all of you), here is how to think about web analytics tool selection & implementation:

It’s that simple.

My apologies if there is any inadvertent confusion. On the bright side regardless of your size and what tools you own now you have a end to end overview of how to go from nothing to something to something awesome. Good Luck!!

What would be your own self-reflection questions? Will the above questions work for you? Am I missing anything obvious? Is this a good use of time? Vendors what else can we ask ourselves before we ask you to bare your soul? Please share your feedback via comments.

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