Occam’s Razor by Avinash Kaushik

Path Analysis: A process of determining a sequence of pages visited in a visitor session prior to some desired outcome (a purchase, a sign up, visiting a certain part of site etc). The desired end goal is to get a sequence of pages, each of whom form a path, that lead to a desired outcome. Usually these paths are ranked by frequency.

Is doing Path Analysis a good use of time? In my humble opinion the answer is a rather emphatic no, except for one exception (which I’ll discuss below). Almost always Path Analysis tends to be a sub optimal use of our time, resources and any money that is expended on buying tools that do “great” Path Analysis.

We usually strive to do Path Analysis in a quest to find this magic pill that will tell us exactly what “paths” our visitors are following on our website. If they “follow” the path we intended we celebrate.

If as usually it turns out that our visitors don’t “follow” the path that WE want them to follow then it back to the drawing board to redesign the site structure / architecture to get them to “follow” the path or at times, worse, hours of “analysis” on: what the heck were they thinking when they click on this button or go to that page (bad customers, bad customers!).

Challenges with Path Analysis are:

• Imagine a website with five pages. Page one Start, Page five Finish. With a simple visualization in your mind you can imagine the number of paths that a visitor could take. Now imagine a website with 100 pages, now one with 5,000 pages. The number of possible paths quickly becomes infinity (well not really but you get the point).
  
• Most of our tools do a terrible job of representing this path: click forward, back to home, click forward, reverse to three pages ago, hit buy. In a world of linear path representation at a page level this is really hard to compute, even harder to depict. Yet this is exactly how our customers browse our websites.
• On most websites the most common path is usually followed by less than five percent of visitors, usually 1%. As responsible analysts could we make any decision on something such a small fraction of site traffic is doing?
• Even if the most common path is followed by 90% of the visitors current Path Analysis has two fatal flaws:
• It can’t show / say which page in a series was most influential in convincing a customer to move on.
• Current tools aggregate traffic into one bucket, when in reality each segment of traffic behaves differently (say DM traffic vs SEM vs “bookmarks” vs Print Ads). Segmentation is always key.

All of the above combine to make it quite sub optimal to glean any actionable insights that will lead to making our websites more endearing to our customers.

There is one exception to this rule. For structured experiences such as a Checkout or a Closed-off DM Landing Page experience (no navigation, just Next – Next – Next – Submit) Path Analysis can identify where the “fall off” can occur. Once that is identified we will still not know the Why (see Qualitative Metrics Post) but Path Analysis is helpful.

Here is example of new way of thinking about “Path Analysis” that I think is heading in the right direction. (Please see Disclaimers - Disclosures first.) There are atleast three more things I would like to see fixed in this version but ClickTracks address some of the usual fatal flaws here.

• It is possible to break down a linear process into one in which we can group a bunch of related pages (say all product pages) into “groups”. This helps fix the problem of linearity because customers can go from A to B to C or C to A to B and it does not matter for related content.
• It is possible for Visitors to show up in any stage at any point (this is actual behavior now with SEO influencing where people land). Google Analytics also has this feature(please correct me if others do as well).
• Perhaps the cutest thing is that it shows which page in the “Path” is most influential in moving people to the next stage. This is awesome because one can simply look at the “darker shaded” pages and know, for example, that no one cares about system requirements but rather the page on our 10 year no questions asked return policy is the most important one in convincing people to add to cart.
• It is also quite easy to view how different segments are influenced by different content, in my unreadable screen shot you can see All Visitors vs Visitors from Google. Imagine this intelligence then turned around and applied to personalization (!).

This is not perfect but getting there and I think all the vendors will soon coalesce around this innovation and we will all be greatly empowered. 

Path Analysis as it is practiced currently ultimately is like communism (with sincerest apologies to anyone in my audience who might be offended). There are overt/covert  intentions to control things, to try to regulate, to say that we know better than you what you want, to push out a certain way of thinking. I know this sounds extreme, and it is but simply for shock value and not to offend anyone.

The web on the other hand is the ultimate personal medium and one in which we all like different things, we all have specific preferences and opinions and a certain way we want to accomplish something. The beauty of the web is that all that is possible and cheaply with easily accessible technology. So why do typical Path Analysis and why try to “push” a certain way of navigation / browsing / buying? Why not get a deep and rich understanding of our customers and then provide them various different options to browse our website they want to and get to the end goal the way they want to.

Why not let democracy flourish? On our websites and in our customer experiences?

Agree? Disagree? Does Path Analysis work for you? Please share your feedback via comments.

Second in a series that aims to share some guidance on how to move from the world of Web Analytics to the world of Web Insights.

By now it is fairly well established that absolute numbers (KPI’s) that represent one data point are fairly useless. Example: what was the conversion number in May. Just by itself it is not useful.

A while back we all moved to measuring trends which gave a bit more context to our metrics. Example: what is the trend for my conversion rate from January to May (or even better from May last year to May this year). Gives nice context on if we are up or down over a time period and over same time last year.

New Nirvana Rule: Never report a metric (even God’s favorite KPI) without segmenting it to give deep insights into what that metric is really hiding behind it.

The power of segmenting a metric is that you peek behind the curtain and find out more about the metric. These are the benefits that you will gain:

1. It is impossible to segment any metric without putting in the effort to understand what we are reporting and the business value that the metric represents. This is hard work but what does not kill you makes you stronger. :~)
2. Segmenting allows you to quickly hone in on areas of deeper dive from which will emerge key insights that will drive real and meaningful action.
3. Our senior executives and decision makers don’t understand all the complexity and magic that is a web experience, showing them segmented trends is a extremely effective communication tool (and the best part is you barely have to talk, the picture will tell the story).
4. You will earn a big fat bonus and promotion.

Leaving you now would be lame, here is my attempt at providing examples that illustrate this recommendation.

We have established that this is not very useful:

I have recently come to believe that if a visitor does not stay on the site for atleast five seconds then that is an unqualified visitor (or that we never had a chance with them). Because even the most compelling websites need atleast five seconds to sell you on anything (not just products but even ideas). So application of a simple segmentation to me on this website is how many people are in the game.

This simple segmentation tells me that just 48% of all the traffic stayed for more than five seconds, I never had a chance with the others. Let’s say your traffic this month was up, instead of getting credit you’ll be prompted to dig deeper into what happened, what were the reasons for 52% of the traffic leaving so quickly. Were we running wrong campaigns, are our meta tags wrong? It might prompt questions about what the number was for prior months.

There is a nice flip side though, if only 48% of the traffic stayed for more than 5 seconds look at what it can do to your conversion rate (it goes up, bonus for you baby!).

Another way I could segment this traffic is by the hottest thing on earth: Search. I got great traffic but how many did I get from Search, and I wonder how may from Google.

Again you have a nice little context for your total traffic that you would not get by just showing total traffic by itself. You can now say we are only getting 18% of our traffic from search engines (is that good or bad? you decide) and 85% from google. There is a recommendation sitting in there about our search strategy and perhaps diversifying to other search engines (per the latest numbers google has 47.8% of overall search traffic). Alternatively your CEO could say: My influence circle is wrong, if search is not “hot” for us then where are people coming from?

But you can go further and stitch the story together with the first example…..

This might be a home run, one picture shows a great story all together. We are getting a good amount of traffic from google but of that only 34% is staying for more than 5 seconds. Since such a unusually high amount of traffic is from google is might be SEM/PPC in which case we are much worse off because we spending money and people are not staying on our site.

Here is a example of how you can analyze segmented data over time and make the story even more powerful….

It is not pretty but I am sure even without any context you can look at these numbers and draw out so many nice insights that could lead to actions.

The “Overall “Benchmark” fm Trend” is simple average of this year’s performance and that gives you a cool way to see how the latest month is doing. Of course you can make it even better if you have pre-set goals.

Hopefully you see the power of segmentation demonstrated even by such a simple example. For your website and business maybe it is not time on site that is important, maybe it is page views, maybe it is conversion rate, maybe it is number of leads, maybe it is DM Campaigns, maybe you only rely on PPC/SEM.

Understand what your business is, what are areas of strategic focus and then segment away.

Please take a vow that today is the last time you have sent a excel dump of Top Pages on Site report to the entire company, change that to Top Pages Viewed by All Visitors by Search Traffic and by Top Affiliate Partners (or whatever).

There is no KPI so insightful all by itself, even in a trend or against a forecast, that it can’t be made more impactful by applying segmentation.

Agree? Disagree? Have examples? Please share your feedback via comments.