Web Analytic Matt

Managing Social Media using Web Analytics0
Matt Hopkins posted in Web Analytics, Social Media on September 27th, 2007

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It’s quite amazing what you do with web analytics because it is basically your portal into understanding your online presence. This means that you can look at the effect of social media, your revenue metrics and even your more subtle engagement metrics.

So what is social media?
Social media is news or content that is created by every-day people, this could be a bookmark of some useful content, a blog like this made of one person’s thoughts or even a video. Really it can be any piece of content that is generated by a user of the internet rather than a regular publisher.

And this social media is good because…?
It comes down to the search engines, they want to serve their customers by providing the most relevant content at the relevant time. To do this they constantly look for new ways in which the internet is changing and new ways of identifying relevant content. And what could be more relevant than what individual people are saying.

For example if the Sun newspaper (a tabloid newspaper in England) wrote about a new form of cheap and renewable energy you might not believe it entirely as it is only one publisher and may possibly not be as trusted as other publishers. But then you have 50 individuals that are blogging and making videos about this new form of cheap renewable energy. Who would you believe?

Personally I would go for the 50 individuals as the news is likely to be up to date, a blog can be updated any time whereas a newspaper only comes out once a day. Also there is safety in numbers and 50 publishers saying the same thing is probably more accurate than 1 publisher.

We know that more and more people are reading blogs for niche information and so the big search engines must do the same. This means that people interested in their online presence need to be looking at using social media to their best advantage as every-day people trust it as do the search engines.

But how do you measure social media?
There are a couple of trains of thought when it comes to measuring social media, some people use things called buzz monitors to track particular keywords or keyphrases that are appearing in certain mainstream blogs or aggregation channels. Some just use their keyword and referrer reports of their web analytics applications to measure the increase or decrease of interest. Obviously you would need to add relevant metrics like engagement or interactivity or time on site etc. to find out if your social buzz translates into the desired on site behaviour.

Another way is to actually use a tool provided by the search engine Google. It is their trends application and this week they made what I think is a major change by having daily updates as opposed to monthly or weekly updates so you can measure the buzz of your project using the search engines. You can see below that social media is a particularly hot topic at the moment, one of the reasons I’m writing about it is it’s relevance at the moment.

So what am I using social media for at the moment?
At the moment I’m creating a bit of buzz around a website I’ve created by using social bookmarking sites, writing relevant quality content blogs around issues my new product can address, creating social groups on relevant topics in Facebook and Yahoo groups, answering relevant questions on Yahoo answers and some other good stuff.

And to measure this buzz i’m using my install of Buzz monitor as well as Google trends and of course my onsite analytics. This way I can see at what stage my buzz has reached and where I need to create buzz in order to generate more quality traffic and in the end more sales.

But remember that social buzz is not the only thing on the internet and your website does not exist in a social vacuum, it relies on other interaction from the usual places.

If you’re doing any fun internet marketing with social media and don’t mind sharing your experiences then please add a comment.

Using packet Sniffing for Web Analytics3
Matt Hopkins posted in Web Log Files, Web Analytics on September 4th, 2007

Firstly a packet sniffer is a really simple application that passively listens to any network traffic that runs through or past a network card. When it ’sniffs’ the network it picks up all the packets for every protocol such as tcp/ip and ARP, it also picks up encrypted SSL packets.

This all sounds very technical and worlds away from anything related to marketing or web analytics so how does it fit in?

Well, using a packet sniffer you can pick up all the packets contained within a HTTP or HTTPS request. If it is HTTPS traffic then you can provide the SSL certificate to the packet sniffer and access the requests in their unencrypted form.

Once the packet sniffer has recreated the HTTP and HTTPS traffic it can then create a log file, similar to one created by a web server. From this you can use your favourite web log analyzer to process the log files and provide you with website visitor data.

So where does packet sniffing fit into the data collection methodologies?

You might already know that the main difference between page tags and log files is that page tag data is collection on the client side whereas log files are generated on the web server. Packet sniffing also resides on the web server or at least the Local Area Network (LAN). This means it has the same problems as log files with proxy caching and so is likely to be less accurate than page tags.

But there are advantages, packet sniffers pick up every piece of tcp traffic including form data that has been sent using the POST method and all packet sniffer applications will output that data. For technically minded web analysts there are loads of performance statistics about the network that are also output to the log files.

Another extremely useful aspect of packet sniffers is te ability to amalgamate data from multiple web servers into one log file. For example, lets say that a large content provider has 20 servers that are load balanced and in front of them there are 10 proxy servers. If we use standard log files then we need to either use the proxy logs assuming the proxy servers are all on the same platforms and can be configured correctly to output the required information, or cluster the 20 server log files during analysis. Using a packet sniffer in front of the proxies we can pick up all of the data from one point and because it uses passive sniffing it will not slow down the network traffic.

In any other situation I would suggest page tags or log files depending upon your preference. If you are currently using a packet sniffer(like Clipen) in your analytics environment I would be interested to hear of your experiences which you can detail in a comment below.