Web Analytic Matt

First Party Cookie Confusion5
Matt Hopkins posted in Web Analytics, Visitor Segmentation on August 1st, 2007

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Cookies in their own right are really simple little things, the idea being that every time you view a web page on a website, you will be given a code to store on your local PC. The next time you come back to that site it can read your stored cookie and so count you as the same visitor who has returned.

So where is the confusion?
Well, the confusion comes when you start talking about first party and third party cookies and how they are treated differently by web browsers.

A first party cookie is a cookie that is given to the website visitor by the same domain (www.domain.com) that the web page resides on. Whereas, a third party cookie is one that is issued to the website visitor by a web server that is not on the same domain as the website. I’ve made a diagram below which shows how the first party cookie and third party cookie differ.

So when might a third party cookie be used?
Generally third party cookies are issued when are third party is interested in tracking your website visitor traffic, this could either be by a banner advertiser who places a number of banners on your site and wants to know how many times it has been requested, or it could be a third party hosted analytics vendor that issues a page tag for each of your pages that forces a cookie on your site.

In the last situation, where an analytics vendor issues a cookie through a page tag the cookie is seen as a third party cookie because it is being generated by the analytics server which is having the tracking 1×1 invisible gif image requested from it by the page tag. It is however possible to have an analytics cookie issued by the third party vendor but still look like a first party cookie.

There are 2 ways of achieving this:-

1. Create a DNS alias for third party analytics server so that it looks like it is actually part of your domain and so anything issued by this server because 1st party (including cookies)
2. Have the Javascript page tag create a cookie at run-time and then pass the cookie value back to the analytics server so the cookie is created within the page and so becomes a 1st party cookie.

The obvious advantage of the DNS alias option is that you can have a smaller page tag which is quicker to load, however the cookie making page tag has an advantage over the DNS alias because no structural changes need to be made to the site’s infrastructure and the implementation of the tag should be more straight forward.

So, in the end you want to aim for a first party cookie as these are typically blocked by fewer browsers than third party cookies. To give you an example, I did a test a few weeks ago using on a site using a third party cookie and measured that over 70% of the cookies were being blocked. After a similar test using first party cookies only 30% were being blocked. This shows that although cookies aren’t as accurate as we might all like, all cookies are not created equal.

My First Engagement0
Matt Hopkins posted in Web Analytics, Visitor Segmentation on July 24th, 2007

No, i’m not getting married just yet.

But I have just released my first white paper which focusses on website visitor engagement and it follows on nicely from my orginial post on engagement scoring.

Let me know what you think.

What is Visitor Segmentation and How Will it Help Me?0
Matt Hopkins posted in Web Analytics, Visitor Segmentation on July 8th, 2007

When looking at the topic of web analytics you will no doubt run into something called visitor segmentation. This is really just looking at different behaviours of the visitors that come to your website.

I’ll explain it a bit further by using the analogy of a TV programme we have here in the UK called Big Brother (BB). Personally I’m not a great fan of the show but hopefully it’s something that people can relate to.

In BB there are a number of people that live in a house for a period of 8 weeks or so, this house is covered with cameras so that everything that happens in the house can be monitored. In the same way a website can record everything that happens when someone is on the site using page tags or web server log files.

Within the BB house people move from room to room, they chat to each other and group together, they might swim in the pool or eat some food. All of this behaviour is tracked by the house cameras and then analysed later by psychologists and the public. On your website you can identify which pages people go to, whether they fill out a form or even if they play a Flash game and get the highest score. This site activity is then later analysed to identify behaviour patterns, the most popular types of content among other things.

So what’s the point of this analysis?
The result of BB is that Endemol, the programme creators earn money from a variety of sources including public phone voting, advertising and television appearances. Also the main purpose of commercial websites is to generate revenue by interacting with website visitors and getting them to part with their cash in a variety of ways including purchasing products, services or clicking on advertising.

And where does visitor segmentation come into it?
Well, for BB they need to identify people within the house that do similar activities be that talking on the sofa or eating all the time. Then after grouping these people they can identify which behaviours are the most popular with the public and cause Endemol to generate the most amount of money. Once this has been achieved they can plan what type of people they need to recruit for next year’s show. We are now on BB 8 and we can see that the housemates have become more and more irritating with each iteration of the show, but maybe that’s what generates interest in the show and so creates more revenue.

And on your website you can group visitors by their online behaviour like which content types they consume, whether they comment on articles or come back to the site on a regular basis. Once you have identified these groups of people you can then see which generate the most revenue for you and attract more visitors like this via your marketing campaigns, or maybe create more content that satisfies your revenue generating groups.

So in essence visitor segmentation is about group people who act in similar ways and then if you can make one person in each group happier then you can hopefully please most of the people in each group and ultimately generate more revenue/interest/brand awareness. Of course it is never that simple as people are notoriously unpredictable but habits do form over time and so it is possible to capitalise on these.

Happy segmenting!

Web Analytics as a Marketing Tool: Scorecards0
Matt Hopkins posted in Web Analytics, Visitor Segmentation on June 16th, 2007

We should all know that to do web analytics for web analytics’ sake is not a good thing, all those numbers, a few words, but without meaning they are pretty useless.

As a web analytics consultant I like to find ways in which web analytics data can be used in new and interesting ways to assist in making better business decisions.

This is where I introduce the concept of scorecards, banks and lending institutions use a method called credit scoring to identify people who they consider to be eligible for receiving credit. The way this scoring works is to take a number of factors about each person, such as their gender, age, employment status and where they live. They then apply a value to each factor, so if the person is below 25 years old then they get a score of 1 for age. If they are employed and have a salary of over 30K pounds then they may get a score of 15 for employment status. Add all these scores together and you get a scorecard per person.

Each person’s scorecard then has an overall score which determines how eligible they are for credit and how much credit. Now, currently in web analytics we have the concept of visitor segmentation which takes different visitor behaviours as differentiating factors but I’m not aware of a product that allows scoring of these factors in a similar way to scorecards.

So, what is the benefit of scoring website visitors and what should we score them on?
In my opinion the main thing website visitors do is view pages, or on web 2.0 sites they may trigger events. So let’s say that we apply a score to certain pages or events. If we use the example of an e-commerce site where books are sold, a search result page could have a score of 1, a book description page may have a score of 2 and the sign up page for the latest books email newsletter can have a score of 5.

Now when we take a site visit that includes 2 searches, a view of a book description page and a sign up for the newsletter the total score for this visit is 9. If a visit consists of only 4 searches then the total score is 4.

In this example the same number of page views were present but because we score each of the page views, we know that the initial visit was worth more than the latter visit. This also means that we can group visits together by their score and find out commonalities between high scoring visits and also low scoring visits.

Also there is no reason why we can’t use this technique to filter out website spiders when using log file analysis, because spiders will want to visit every page so they will have outrageously high scores.

Whatever you decide to use this technique for, you will need to decide which pages to score, what the scores will be for each page and the thresholds for visit/visitor scores you are interested in.