Why is there a certain 'voodoo' associated with web metrics and analysis? I would think most business owners and marketers when asked the question "do you need better analysis tools to measure your campaign effectiveness?" would immediately raise their hands.
We all want better measurement of our budget dollar's performance but are averse to understanding the data mechanics or even how to go about generating an insightful report.
Simply, no one wants to own the metrics data or be held responsible for reporting it.
The Wikipedia explanation of the phrase origin "Lies, damned lies, and statistics" states the following: "the use of statistics to bolster weak arguments, and the tendency of people to disparage statistics that do not support their positions.
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There lies our second issue; the numbers are accurate but the interpretation and usage by the individual can sometimes be suspect.
In this three part series, it is my intention to dispel this voodoo with web metrics and to provide a methodology for evaluating and measuring the success of your online program .
Part 1: Keep it simple - Too much data is just that - too much data! By 1969 in Vietnam, the kill ratio for American jets during dog fights was plummeting.
At one time, 20 to 30 enemy planes were shot down for every one US jet.
By the end of the decade the ratio was one to three.
American jets and their technology were far superior to the Russian Mig Jets but a disturbing trend was happening.
When they interviewed the pilots that were highly successful in air to air combat, they found something in common.
As fighter information technology advanced, so did the pilot's dashboard and instruments.
The successful pilots identified and focused on a few instruments; ignoring the rest.
One successful pilot had even taped over redundant instruments.
In the engagement of the air enemy, life or death decisions were based on key critical information.
Most web analytics software programs, Omniture, Google, etc.
offer the user so MUCH information in their web marketing dashboard to send the user screaming down the hall in frustration.
Try to keep it simple because too much data is just that - too much data.
Part 2: Where do I begin to start analyzing web data? Knowing that you have so much data available to you can be both enlightening and daunting.
The question you need to ask is where I begin.
Start with your company goals for the year.
If you don't have any, well that's a blog topic for another day.
From your company goals, you can create specific marketing objectives that transcend to your website.
From these marketing objectives, you will identify and measure key performance indicators (KPIs).
Your KPIs are key web activities or actions that you want to focus on.
It is unrealistic to state "I want to increase web traffic to your website".
It is more useful, for example, to define a goal of increasing web traffic by 10% to support a product launch in September.
Let's consider the following company example: Company Goal: Acme Company sells consumer widgets and one of their 2009 business goals is to improve customer loyalty.
Web Marketing Objectives: Benchmark, measure and improve online customer satisfaction KPIs for the 1st quarter of 2009.
Key Performance Indicators (KPIs) Retention KPI = Ratio of "Returning visitors"/"All visitors" What it measures: determines how you are doing at retaining visitors Metric: increase by 10% How: promote webinar and product announcements Action: First determine your KPI benchmark to identify a % goal increase.
I usually lean towards measuring the same period before.
Since we are measuring performance for the 1st qtr of 2009, I would recommend you compare metrics to December Qtr 2008.
Use your judgment here; if your company has strong cyclical sales you may want to measure the same period from the year before.
Part 3: What do my Key Performance Indicator (KPI) measurements mean? Congratulations! After reading Part 1 and 2, the challenging part of web metrics is done.
There is still ongoing work required but the methodology of identifying clear goals and assigning applicable Key Performance Indicators (KPIs) is a sound business practice.
In addition, make good use of a continued improvement process.
Realize that company objectives will change and therefore your web objectives and KPIs may need to be modified.
Changing objectives and KPIs may seem a daunting task to manage but they are not.
If you focus your web site around a small number of changes, your web metric program will become more manageable.
In a previous position, I was managing Symantec's enterprise online marketing worldwide.
During the crazy days of the Dotcom boom, quarterly web objectives were set and then changed within the first month.
With rampant growth in new markets, "changing the tires while driving" was our company's modus operandi.
But this should not be the case with you...
hopefully.
Using actual numbers, let's look at the example I used in "Part 2 - Where do I begin to start analyzing web data?" Our company objective was to improve online customer retention for the 1st quarter of 2009.
We will measure this objective by using the following KPI, with a target goal to increase by 10%: Results: % Returning Visitors Dec Qtr: 50% Mar Qtr: 45% % Change: 10% At first glance, we failed on meeting our objective of improving customer retention.
However, you should be more interested in understanding what could contribute to a lower website customer satisfaction level - therefore further research into the data is required.
We soon learned that a national marketing launch occurred in January.
As a result, there was a huge spike in new visitor traffic to the website.
Marketing and public relations were successful in driving new visitors to the site but was the cause for the drop in % returning customers.
During hard times, there is great pressure to justify every marketing dollar that is spent.
A web analytics program that binds company objectives with measurable KPIs, is now expected by Senior Management.