The Visitors You Can’t Track: Untrackables and Analytics Blind Spots

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Analytics programs such as Google Analytics often fail to track various type of users, these may include:

1. visitors that erase cookies after each session or at some other interval
2. visitors that block cookies outright
3. visitors that rewrite cookies for fun
4. visitors that arrive via a proxy service
5. visitors that click on your link or are referred to your site some other way and then leave your page before your analytics code can load and capture information or open their cookie (assuming there is one); Google has come up with a good antidote for this with their asynchronous tracking JavaScript, which is now available in a beta release.
6. visitors that arrive via multiple redirects
7. visitors that randomly visit your site from home, the office, on any other extra computers, their phones, ipads, game consoles
8. visitors that share their computers with two or more household members that all happen to visit your site and similarly multi user such as those at internet cafes and any jumping point where a new or different cookie must be used and where cookies might be shared between two or more people on the same computer who all happen to visit your site
9. visitors who proxy code for themselves, rewriting JavaScript and other parts of a sites code to meet their desires.
10. visitors that spoof their referrers or any other means that will derail validity

Surely there are more scenarios, but these alone are reason to believe that clickstream analytics is handicapped out of the gate. The multi user per computer or multi computer per user scenarios are in particular the most troublesome. These certainly account for a substantial portion of the visitor mix (or mix up as it were). I use at least 4 different devices to surf. I often visit the same site from multiple machines, but I tend to convert (if I buy or trigger the appropriate event) on one of two computers, so there are situations where I know that I appear to be about 4 different users on varying IP addresses (even on the same device), and only one of us/me will ever convert. What does that do to my conversion rate if I’m the site in this case?

This prevalent type of scenario is and will be a fundamental flaw in analytics for the near term at the very least.

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Analytics Tool: ClickTale Reconstructs User Experience

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I was a bit surprised when I first came across this analytics tool, because I had always imagined that a visual replay of user experience could only be achieved with a packet sniffing platform. Interestingly, it appears as though JavaScript can accomplish the same. Why did it take so long for such a tool to arrive, one must wonder.

The pricing is quite reasonable, though this is no Tea Leaf, or a maybe something like a poor man’s Tea Leaf. Nevertheless, I was extremely pleased to stumble across this gem.

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Some Usability Rules for Forms

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  • if a password requires a number or case variation, make it obvious
  • username should be the email address if possible
  • require confirmation of email and password
  • always use highlighting or an asterisk to represent required fields and optional fields
  • build your email reputation and deliverability so you can send confirmation emails effectively
  • send confirmation emails ASAP
  • collect the least amount of information necessary to facilitate the signup or form goal
  • don’t collect credit card information until it is needed
  • forgo asking for the user’s address until it is needed
  • don’t default email opt-ins to being on – present the option and only send email with permission
  • use form text areas to provide extra information about form requirements and clear them on focus
  • make sure tabbing flows logically through the form
  • pre-focus the cursor in the first form area
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