When Analyzing Your Data, Include the “Why” Factor.

MoreVisibility - November 9, 2009

One of my favorite web sites on the entire planet is Woot.com. They sell one item every single day. There’s no way to predict what the item will be or how many are in stock or how much it will cost – just visit their site at 12 AM CST every day to find out what great sale they will promote next!

Let’s pretend that you are the senior data / web analyst for Woot.com, and my online behavior and interactions with your site(s) were representative of the average, everyday visitor. It wouldn’t be long before you cracked open Google Analytics, WebTrends, Quantcast, or your favorite measurement tool to have the equivalent of a heart-attack. Here’s my personal estimation of my lifetime statistics on Woot.com and its family of sites:

Visits: 1,200
Pageviews: 1,400
Bounce Rate: 99.5%
Average Time on Site: 0:00:20
Abandonment Rate: >99%
Conversion Rate: <0.00%
Revenue: ~$35.00
Average Order Value: ~$17.50
Visits to Purchase: 300+
Revenue Per Visit: ~$0.02

Now I don’t know about you, but I don’t know many folks who wouldn’t frown upon looking at those depressing statistics. I can make it even worse for Woot.com by subscribing to their RSS feed and never actually visiting any of their sites in the first place.

The interesting thing about me is that I don’t visit Woot.com to purchase items. If there is something interesting, something that I need, or some cheap gadget that I have no use for but I really have the itch to spend, then yes, I’ll make a purchase. But if you were to ask me what my top 5 reasons for visiting Woot.com would be, I would tell you that I visit Woot.com to:

1. See (not buy) what the item of the day is
2. View purchasing statistics (Geo and hourly breakdowns)
3. Read the product overview (they are VERY clever and funny!)
4. See what’s on shirt.woot, wine.woot, and sellout.woot (their network of sites)
5. If I am remotely interested in the product, read their message boards to see what people are saying about the product
Bonus Reason #6: To see if they are doing a Woot Off!

So if my usage statistics and reasons for visiting Woot.com are representative of the average, everyday visitor, what happens now? Do you sound the general alarm and have a fire sale? Redesign your entire web site? Drop your prices to a ridiculous level? Use a lifeline and phone a friend?

Or, maybe you start including the “why” factor into your data analysis.

Google Analytics, Omniture SiteCatalyst, and every other web analytics package can give you every usage statistic imaginable, but it can’t directly tell you why people search for what they search for on Google and why they are on your site. To fill in the gaps left behind by your favorite web analytics platform, you’ll need to really think about what your web site has to offer its visitors, and what they can possibly do you on site – other than whatever your site’s main objective is. If you sell products of any kind, they could be coming to your site to simply read reviews, or window-shop, or read your company blog, and not even think about purchasing an item at this time. If you are a B2B company, they could be finding out about the history of your company, your board of directors, or to read client case studies, and not to immediately request an RFP and do business with you. And, if you’re a non-profit organization, they could simply be learning more about your causes and getting fact-sheets, and not visiting with the intention of donating to your cause.

There are some tools and some ways that you can help yourself in including the “why” factor in your daily / weekly data analysis. These include (but are most definitely not limited to):

1. Visitor Loyalty reports in Google Analytics
2. Site Search usage reports (usage on your site’s internal search function)
3. “Voice of Customer” tools (4Q by iPerceptions is an excellent online survey tool)
4. Google Insights for Search and Google Trends for Websites (get a feel for visitor behavior trends)
5. Offline focus groups / user-experience studies

Whether you’re the senior web analyst for Woot.com, the National Football League, CNN.com, or marketing for Jennifer’s local flower shop or Louie’s Pizza Joint, it’s critical to include the “why” factor in your data analysis, or you’ll be working off of faulty assumptions. Always determine why people are visiting your site.

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