Selecting the right vendor is only half the battle in successfully building a web measurement program for your company. You should also be thinking about dedicating resources to manage, maintain, and evangelize the data throughout your company.
Many companies make the mistake of simply selecting an application and assuming that all of their problems are solved. The notion of the "silver bullet" software or service is surely attractive, but unfortunately, no such bullet exists. Companies who assume that a technical or marketing resource will be able to spend a little time each week poking around in the measurement application when they have spare cycles nearly always fail to take full advantage of their investment in analytics. In other words, the old adage that "you get what you pay for" holds true in staffing, as it does in vendor selection.
Some companies will inevitably not be able to afford to hire a dedicated staffer to manage their measurement program, especially those companies who are spending less than $25,000 on the entire application and implementation. In these cases, it is recommended that companies at least dedicate one-half of a single person's time to managing the measurement program. Empower a motivated employee to make sure the implementation is good and that people at least understand that the information is available.
Most companies need to dedicate at least one full-time resource to their web measurement efforts. One person who has enough technical skills to manage and tweak the application's implementation but enough business savvy to translate the data into something that the entire organization can use [Hack #91] . Larger organizations should plan to hire more than one resource, especially if the initial investment in a measurement package is particularly large or if a significant number of people in the company will likely use the data on a regular basis. The logic is that no one person can support an army—you need to distribute the responsibility and allow a team of data analysts to support the company.
Because very few people have degrees in "web data analysis," it is likely that you'll need to hire someone with relevant skills and adapt them organically into the role of a web data analyst. Some of the characteristics of great data analysts include:
The best web data analysts have a strong interest in the business being successful and understand business and marketing concepts. You don't need to have an MBA to understand concepts like visitor acquisition costs, margins, and return on investment, but you do need to have enough interest and experience to differentiate a good business decision from a bad one.
Much of what a web data analyst does is help people understand the data and its potential impact on the overall business. If the analyst is afraid to present to groups or is otherwise mousey, more often than not she won't be effective. Having an ineffective web data analyst is like not having anyone in the position. The ability to work with multidisciplinary teams and build consensus is also critical.
The "best" web data analysts are people who are able to successfully bridge the gap between business interests and technical resource allocation—essentially, getting marketing and IT to talk to each other in meaningful and productive ways. When your web data analysts are doing their jobs, they should be getting everyone excited about the data and its potential impact on your online business.
Unfortunately, it's not that easy in this day and age to just hang a "Help Wanted: Web Data Analyst" sign in the front window and wait for the resumes to start pouring in. As mentioned previously, nobody is currently producing college graduates with bachelor's degrees in web analytics—at least nobody known to this author. Without a deep pool of talent, at least in 2005, the need for qualified data analysts far exceeds their availability.
So what can you do?
Well, rather than go back to not staffing for measurement success, you can increase your chances of attracting available talent by doing a few simple things.
It's unlikely that the usual path of throwing a listing on Monster.com is going to get the response you're looking for. Likely, you'll get resumes, but experience tells us that most of the candidates will be underqualified and probably didn't even read the posting closely. Consider the following nontraditional avenues for hunting down web data analysts:
Let your vendor know you're looking for help and ask them to keep their ears to the ground for you. Make sure they know you're not trying to steal their people, but you're serious about getting help.
Write to the Web Analytics Association (www.webanalyticsassociation.org) and see if anyone in their membership is currently looking for a job.
Join the Web Analytics Forum (www.webanalyticsdemystified.com/discussion_list.asp), a collective of over a thousand web measurement professionals, some of whom may be interested in coming to work for you.
A common mistake that companies make when trying to hire web data analysts is looking for inexpensive, junior people who don't have enough business experience to really succeed on the job. Look for senior-enough people and be prepared to pay them salary commensurate with their experience, increasing the chances that the "right" person will be interested in your position. Most talented web data analysts are making around $100,000 plus other incentives, depending on where they're located geographically.
If one of the key drivers behind investing in web measurement is increasing your conversion rate or average order value, give serious consideration to offering your web data analyst a cash bonus if he helps you reach goals for improvement.
For example, if by increasing your site-wide order conversion rate by 10 percent, your business will bring in an additional million dollars a quarter, it seems logical that you'd work diligently to try things that will make that goal become reality. While your web data analysts will surely work diligently towards that goal, if you agree to pay them a $10,000 bonus if they drive the business to meet that goal, you're still left with $990,000 per quarter in additional revenue, and you'll see your web data analysts work harder than you thought possible.
Fight the temptation to say "I should not have to pay someone a bonus if she's simply doing her job!" If you don't, your competitors will, and the talented data analysts will be working for them (and against you).
In summary, no web measurement application is good enough to work without someone or a group of people supporting it. Companies don't buy sales force automation or customer relationship management tools without dedicating resources (usually administrators) to their care and feeding; why would you think you could avoid staffing around your investment in web site measurement?