Online Visitor Behavior, Offline Purchases and the Brand

Hello everyone, it's been a while since my last posting. Today I want to talk about online behavior towards offline purchases for the luxury watch maker, Rolex. Check it out, it's one of the most beautifully branded experiences on the Web. Please note that I'm not trying to promote the site as I no longer with for the agency that manages it.

Every month or so there would be a new watch promoted on the home page. For instance, today you'll see the Date Just 31 MM. We could not understand why women's watches weren't generating significant traffic...even when those that where promoted on the home page. My 1st conclusion was that not a lot of women were buying Rolex watches for themselves or that men weren't buying them as gifts. Was it the brand? Rolex is worn by successful BUSINESSMEN and men seem to covet their Rolex watches more than women. Or do they?

What we discovered via some due diligence with the Rolex dealers and social media was that women love Rolex watches and buy plenty of them. But they're purchasing the men's models for THEMSELVES! It turned out that women liked the larger dials on the men's watches and therefore did not purchase the watches meant made for them. See how the brand can sometimes poison/determine our conclusions? Thus, the visitor behavior (in this case) accurately represented offline purchases. Please share your experience and input to this article!

Authenticated UserID vs. Unique Visitor

Many applications require end-users to login in order to access there content. As such, we decided to pass the Authenticated UserID, e.g. aberlinger, of each visitor via sProp1 in Omniture. EVERY (yes every) user must login to access these sites. We started to notice a significant difference between unique visitors and authenticated userID's. Check out the stats below for March 2007:

• 30,710 unique visitors
• 19,708 authenticated userID's

How is this possible? What are the reasons driving the discrepancies in the data? We first need to understand how our analytics solution determines unique visitors as each package has its own proprietary method to calculate unique visitors:

SiteCatalyst determines unique visitor information using several technologies. The primary method of calculating unique visitors is by setting a persistent cookie on the visitor’s browser to uniquely identify the visitor. Cookie technology helps to avoid common pitfalls, for example, IP Pooling, caching, or tracking visitors behind a firewall, when counting unique visitors. If the visitor has disabled cookies on their browser, or if the visitor’s browser does not support persistent cookies, Omniture uses a combination of the IP address and the user agent string to determine if a visitor is unique or not. SiteCatalyst reports a small percentage (usually 1-2%) of visitors who do not support cookies.

Did you notice "cookies" in Omniture's definition above? Perhaps we should research cookies and their impact on analytics data. ComScore and many industry experts have found that cookie deletion can be as high as 40%! Have I totally ruined your day? Are you questioning the sanctity of your reports, especially the ones that end up on your CEO's desk? Wait, it gets worse. I ran some reports which illustrated users logging into our sites from multiple machines, IP addresses and with different browsers, yikes!!! Not to worry, there is a solution!

What we did was implement what Omniture refers to as "Visitor Optimization" where Omniture's proprietary/cookie-dependent visitor ID is replaced with our unique authenticated UserID. Once a visitor logs into the site, their authenticated userID gets recorded as a unique visitor. This takes IP addresses, cookies, and user-agent strings out of the equation, woo-hoo! The trick is to make sure that the authenticated UserID's are passed to each page viewed by each visitor. Guess what? It's working! The numbers match!

Ask your analytics vendor if they can implement the same type of solution. However, the fact that your tool might indicate that your site attracted 1,000,000 visitors when it was actually 750,000 should not matter. Why? Because the percentages of your KPI's will not change. Remember, KPI's are a ratio of visitors to success events/conversion rates over a period of time. In other words, if 3% of your visitors purchase a product, generate a lead or apply for a job...the 3% is what you should be focused on improving in context of the total visitors. While 3% of 750,000 is obviously less than 3% of 1,000,000...the patterns you notice on your site remain the same. I hope this helps, Adam.