When attempting to profile and group visitors you want as much information as possible about them to make profiling easier but sometimes getting this information can come at a cost of interrupting the users flow are such techniques ultimately worth it?
From the moment a visitor enters a site a wealth of information is provided by them including hopefully where they have come from, their browser, their physical location (of their ISP at least), their language all of this can and is faked by a small minority but for the vast majority this information can be treated as reasonably accurate. Even with this limited information we can make educated guesses about a user for example we can guess if the user is at work or not.
Once the visitor starts to interact with the site we gain even more information for example once a suitable number of clicks have been recorded we can start to use behavioral models to attempt to estimate gender and age See Post notes for details. Return visitors provide even more information how do they return direct or through the original referrer? All of this builds up a picture which helps to determine how to present the site to the visitor and change them from a visitor to a “user” but this sort of profiling requires the user to stay on the site long enough to profile the visitor. 10 clicks may not sound much but that could easily be a completed transaction or a lost sale before passive profiling has had a chance to determine the best route for the visitor.See Post notes for details
Active profiling in this context is confronting the visitor into a decision making process rather then allowing them to wander around the site on their own. This sort of profiling is not without risk people baulk at being told what to do and especially when a site does not operate in preconceived boundaries of how a site should behave. For many people the website asking questions just isn’t cricket!
The key to active profiling it to force the user into making a decision which can then be profiled this is usually done by removing navigations or hiding content behind some sort of form. By giving the user no real choice (other then to bail) but to tell us something we can then use to show them the next step in our profiling. Let’s take a really simple example if I am selling software I may want to identify larger corporate customers from small businesses I therefore present visitors with a screen with two options one for small businesses and one for corporate customers. Each leads to a different landing page selling the same software but highlighting different features of the software simple and pretty un-invasive we are adding a step between getting the information and this will increase the number of exits at that point but if those that stay convert higher percentage it’s worth losing a few visitors to gain the information needed to improve conversions.
Pros of Active Profiling
- Gather information that you just couldn’t gather through other means
- Confirm information gathered through passive profiling
- Can be introduced directly into visitors funneling process
- Much quicker and more reliable data then passive profiling
Cons of Active Profiling
- Higher bounce and exit rates
- Can cause confusion to visitors
The best method is of course to combine the two methods to gather as much information as possible while keeping the active profiling limited and filling only vital gaps.
Landing Pages – Case Study
Lets take an example of a site selling laptops to households it’s target demographic is 18-30yrs olds in the UK.
On arrival to the site notices the top of the site has a loading icon in reality the site is well optimised however the site is generating the new arrivals profile to put them initially into one of 6 groups. Male/Female/Neutral UK/Not UK to do this the page is pulling the IP address to confirm country if not able to identify assume not UK, and using css history to determine gender (if this fails pesky firefox user! Then gender neutral)
Once the initial profiling is generated the assets are loaded a “British male” is presented with a female “Kirsty” , “British female” would get “Craig” while other would get “Barry” each have certain charms designed to entice and more importantly distract the visitor similar but more generic characters appear for the other 3. These characters then ask a question with four choices (this is our active profiling) Once loaded the characters have a hover element track on them to help determine how distracting the characters are being so that on future pages they can be brought to the fold or are pushed back into the background. The only two pages where the visitor is not determining the character position (though of course the visitor has no idea they are or it would ruin the effect) are this initial page and the last checkout page where they are always at the front almost egging the user on.
Once the user has “answered” the characters question they are further subdivided into groups from this point the wording, colours and location of buttons are determined by the profile they are in. In effect it determines if “Kirsty” talks tech to you or blue is your colour!
This sort of segmentation is highly effective if you already have a tight demographic you are targeting.
Preventing Comment Spam and Payment Fraud – Case Study
Something we have been working on for a little while is the way to identify users that are most likely to be spammers prior to them actually leaving the comment rather then just relying on identifying the comment as spam. For truly automated spam this is pretty easy to do, for human spammers (those people being paid through systems like amazon turk to leave comments) it’s a little harder to identify but not much. By using a first past post point scoring system so no one issue will cause the visitor to be considered a problem you can build up a passive profile and compare it to a typical spammer who will have a specific click pattern, hover over search words and many using blocks of known IP, or indeed from a certain country in some blog cases. Once the passive profile has been matched the active profiling is engaged and forces the user into a simple question “Are you a spammer?” ok so not quite however when the visitor makes a comment rather then an immediate submission the user is presented with a logic puzzle or simply a question this is not to prove they are human as we actually know that already! But to see if they have engaged with the site or the post. If they pass through this active profiling then the normal spam prevention kicks in, if they don’t then they can be subjected to what ever torments the webmaster has in store for them (a java applet is always cruel).
Similar techniques can be used to identify potential fraudulent transactions where users passive profiling might indicate their behavior is “suspicious” the active aspect would be used to reiterate part of the transaction process.
Over using Active Profiling
This post was inspired when my friend Andy Beard pointed me to a marketing tool which uses active profiling (though being marketers they added 400 additional buzz words) via a quiz to generate sales pages in what you could consider to be traditional quizes. When he initially pointed me to the program I was presented with a quiz asking quite leading and obvious questions before I could “see the video” after the second question I simply started randomly clicking until it went away it was only then did I realise the thing that was irritating and annoying was in fact what Andy wanted to show me!
So why did it fail? Well over use of active profiling results in “oh get out of the way” mentality where the user blindly clicks or feeds false information to just get rid or past the profiling system. This is a triple disaster you not only haven’t gathered useless information, you don’t know you have gathered duff information (unless you are confirming passive profiling and are double checking for errors) and you have an upset visitor more likely to bail. The solution is to use active profiling sparingly and only as part of a funnel sales process.
Do you use any of these techniques? If so have they helped?
If you have found this article interesting you might also like to take a look at my recent introduction to this type of user profiling.