The long answer:

One of the activities that I have been exposed to recently in the internet marketing area is buying paid links.

For anyone that isn’t sure what a paid link is, it’s a hypertext link that is purchased and placed as opposed to being written specifically for the website users and no money changing hands.

When I started out buying links one of the first questions I had was how much should I pay for a link. This is a very complex quesition and the answers are equally complex.

Basically what you are doing when purchasing a link is you are asking the web site owner how much they think their site is worth. This is often a dangerous question as you might get the people who just make websites for fun and will accept anything they get, whereas some people are equally uninitiated in the ways of internet marketing and think that 1 link per month is worth more than any average person earns in a day.

It used to be a little bit simpler thanks to good old pagerank, where people would say I have a page with a pagerank of 5 so a link on this page is worth £10 per month. This was the time when SEOs (Search Engine Optimisers) knew little of in-context links.

Alas, Google has taken that little measuring stick away with their pagerank crash last year so now people are even more confused. Some site owners think that they had a PR of 5 last year so just because it has a PR of 0 now it is worth the same. The answer to this is yes and no. Yes because really a links worth is determind more by the relevance of the page, the linking text and the destination page than any page rank.

But no because if I see that a site has gone from PR 5 to PR 0 then obviously Google’s algorithm is looking specifically at that site for paid links.

So in conclusion the best type of link to get is an in-context link surrounded by words in the main body of the page text. But if you think about it those types of links with maybe one or two words of anchor text are not going to be attractive to the average website user to click on as they are not very descriptive. From experience, you don’t get a lot of traffic through those types of links unless you really build up the hype in the surrounding text which is very unlikely in these situations. So we can assume that you will get minimal traffic from the link and the only real value is through the potential to manipulate your site’s position in the SERPs (Search Engine Ranking Pages).

In my experience I would suggest paying between £1 and £5 per link depending upon a number of factors.

1. How much is your product/service worth? So, how much can you afford to spend on advertising?
2. How often is the site you are purchasing from updated? The more the better.
3. What is the backlink profile of the site you are purchasing from? You are looking for a wide variety, from directory links, articles, blogs, real sites as well as scraper sites. Diversity is key.
4. How much will the site owner accept? If they ask for £35 for one link on one page per month then don’t be afraid to say no. There are a lot of websites out there.

Anyway, that is my view on buying paid links. It is a neccessary evil but it works and will continue to do so, no matter what new algorithm changes Google decides on.

Let me know if you agree with my take on paid links in the comments below.

Now I know that SEO techniques and news can happen in a heartbeat, which is why I still use Google RSS reader for keeping on top of whats going on day by day. But sometimes it’s just nice to be able to sit on the couch and read a magazine about a topic I enjoy.

In case you’re interested my favourite blogs that I have subscribed to are:-

• http://www.seobook.com
• http://www.leemccoy.co.uk/default.php
• http://www.bitesize-marketing-nlp.com
• http://www.digg.com
• http://www.fathomseo.com/blog
• http://www.wolf-howl.com
• http://www.gregboser.com
• http://www.marketingpiranha.com/blog
• http://www.mattcutts.com/blog
• http://www.searchmarketingstandard.com
• http://www.pronetadvertising.com
• http://www.sclanalytics.com
• http://www.searchenginejournal.com
• http://www.seomoz.org/blog
• http://sethgodin.typepad.com/seths_blog
• http://www.shoemoney.com
• http://www.smmguru.com
• http://www.techmeme.com
• http://www.webanalyticmatt.com

The Subscription Offer
Anyway, Boris from Search Marketing Standard emailed me a few days ago and told me that as a promotion they are doing at the moment, I could offer the subscription at 67% discount.

This means that a 1 year U.S. subscription would be $4.95 (International - $6.60), and as the $ is really rubbish at the moment that means people in the UK can get a yearly subscription for about the price of a cheap McDonalds meal.

To get the offer… just use the coupon code: HOLIDAY67 and go to their subscription page (https://www.searchmarketingstandard.com/subscribe.html).

The offer is good until 10th Dec 2007 and as a bonus, Boris has promised that they will donate $1 to a charity of my choice (Cancer Research Fund) for every subscriber that used the coupon code during registration.

I hope you found this anouncement useful and remember with Christmas coming up that it’s a really easy Christmas present for all the SEOers out there.

Nearly all have the basic reports like keywords used by people coming from search engines, a list of referring sites that drive traffic to your site, the browsers people have used etc. Then there are the tools that allow testing via A/B analysis, bid managment, engagement scoring and multi-dimensional visualization of data.

So web analytics tools provide a mass of data and sometimes nice ways of visualising that data. But what can you do with this data that makes it worth while spending a large amount of money and effort on such a tool? After all specific tasks can be scripted to provide information so you need to ensure that you make the best use as possible from your web analytics tool.

The Basics
The first thing to do with any new web analytics installation is to track your advertising spend and make sure you are spending money in the right place. This is really easy to set up, it can be as simple as adding an extra parameter of data to a landing page, for example.

Original: http://www.abc.co.uk/landingpage
After Tracking: http://www.abc.co.uk/landingpage?keyword={keyword}

The above example will take the dynamic keyword generated by a Google Adwords ad and place it on the landing page allowing you to compare organic keywords with paid keywords to find keywords that convert visitors and make your Google PPC ads more effective.

You can track any paid advert as long as you can give it a unique landing page. If you think this tracked landing page looks ugly then simply create a vanity landing page like http://www.abc.co.uk/promo which will 301 redirect to http://www.abc.co.uk/landingpage?keyword={keyword} or vice versa.

Improving the effectiveness of your ad campaigns may save between 10% and 20% of your ad spend if you did some sort of optimisation, more if this is the first time.

However, unless you’re selling expensive products or services then this saving alone will not help much when convincing your boss to get an analytics package.

Newsletters are the next thing to optimise. If you can capture email addresses and send an opt-in email newsletter then you can do some amazing stuff that will increase your traffic and conversion rates. This is done by using behavioural targetting and the tracking as shown before.

Scenario Time
Imagine the scenario, you go to an online computer retailer and look at some graphics cards, maybe some hard disks and some computer games. You then proceed to sign up for a newsletter with the latest deals from the retailer.

Next week you receive your first email from the retailer and at the top they maybe review or have deals on the latest graohics cards and computer games, maybe a bundle deal that is for a limited period.

The reason they knew what to include in the newsletter is based on the onsite content you ahev consumed on your visit to the website. If the retailer expanded this technique to all their customers then it is likely that as the emails are targetted towards the specific interest of the user, traffic and increased conversion will follow.

Now this scale of behavioural targetting isn’t for everyone as it can take some effort to implement but it will certainly pay for the analytics many times over.

Going along a similar line of though, what if you knew that when someone comes to your site using a specific keyword they normally head for specific areas of your site. Why not make those areas more prominent for these users and make it easier for them to convert in a way that they want to. For example, if you had a stock photography site and someone came from Google using the search term ‘flower’. If you knew that 8 times out of 10, people end up purchasing a picture of a yellow rose when coming via the ‘flower’ keyword, it makes sense to put that picture at the top of the list and so on.

It makes logical sense that doing this will reduce bounce ratre and increase conversion rate. Most importantly the user will have a good online experience and hopefully come back for future stock photography purchases.

In conclusion I guess the real way I see of making the most of your web analytics tool is to use the information it provides to feed your website with the most optimal content in an automated way. Second to this would be to drive the website content creators in which content converts and to make more of it.

If you have any other ideas for using web analytics then please post a comment.

1. The first is that while at work I managed to prove that our SEM strategy is less than optimal but that to fix it on such a large scale would require immense automation.
2. The second was an article I read about a day later reviewing Yield Software which hypes itself as a Google optimizing service

Now, the review is highly critical and pessimistic about the service and I have also read similarly negative reviews of the concept of automating SEO.

However I think that everything to do with optimizing your rankings in Google is possible to automate given a very skilled programmer and a lot of time.

A few years ago when I first came into contact with the theory of online marketing, as a programmer I thought, “why is all this SEO stuff not automated?”. I then later found that much of it is using software like WebCEO and IBP, together with bid automation tools for SEM, would it be much of a stretch to combine these tools, along with behavioural targeting and page optimization tools like Google Optimizer to make a people and search engine optimized site? I don’t think so.

But what about when Google changes it’s algorithm?
As that question states, we know that Google mainly works off one or more algorithms, so surely you can write an algorithm to optimize for Google’s?

SEOmoz wrote a great example of how to test a search engine algorithm on a simple scale. Basically it uses a random domain name with random text and random links, you then modify the elements that you wish to test and as a result you see how well each of the pages perform in the SERPs (search engine result pages). So, if you had a number of these tests up running there is no reason why you could not use the resulting information to feed your ‘worker’ algorithms that optimize your sites.

The only thing that cannot be automatically optimized is written content. Now, you can certainly have huge database driven websites and optimize them quite automatically but if you have a marketing site then chances are you will have to write some content that will appeal to your visitors. You could get an algorithm to write your optimized content first using a complex Markov chain which would be ok for search engines but you would need to ‘fix’ it to make it human readable.

Some more examples of similar things being done by less than white hat SEOs are control pannels where you enter your domain and some scripts create content, link to it from other sites like social bookmarking, blogs and other domains owned by the user. Personally I think that without looking at Yield Software it is difficult to tell exactly how their system works but I imagine its probably a paid version of one of these control pannels fed by testing domains.

So is it black hat?
I don’t know if their methods are black hat, but i’m sure that if it works then the search engines will make using the software non-compliant with their T&Cs, thus making it black hat.

In conclusion
It’s an ambicious idea and I like it, if they have pulled it off then fair play and anyone that doesn’t use them will dissapear from the SERPs, and it will make SEOs very unhappy and very poor.

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.

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.

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.

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.

Another thing to mention is that there is currently a web analytics job survey happening which is organised by Anil Batra. I think this is a great idea so we can all learn about how this market is maturing and allows career planning for the future in terms of the skills required.

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!

What Makes a Good Web Analytics Consultant?
In my opinion a good consultant needs the following skills:

• Be able to listen - this is a key skill that will save you many hours or back tracking, just listen to what the customer wants, not what you think they want. Assumptions are the root of all evil.
• Take into account other people’s suggestions - being thrust into a company that you don’t know means that you will need to take other suggestions on board. you may know best practises, but company employees know their business and are more likely to understand the ramifications of major process changes.
• Be able to take control - as a consultant people look to you to lead and so you must be able to manage projects and small teams of people when the time calls for it.
• Communication to all levels of people - being able to speak to someone on their wavelength is a great ability, whether they be top level management or at the day to day operations level.
• Present - web analytics consultants must always be able to present themselves, their company and most importantly their solution in a manner that is well understood by the entire audience. Rarely simple task.

These are my thoughts on what it takes to be a web analytics consultant, but for general consultancy take a look at another great article on how to be a consultant.

Now, I receive a number of magazines on a monthly basis about online marketing and computing in general but this one stood out for me. Where all the other magazines would comment on whats happening in the industry and basically take a ’sitting on the fence’ view, Search Marketing Standard actually contains real content. I’m talking about articles like ‘Think before you link…bait’ which talked about link baiting (the process of writing content with the aim of lots of people linking to it), but there was an actually methodology in there not just someone saying “Yeah, link baiting is good because blah blah blah”. The article on optimising your pay-per-click campaign was equally informative, giving real information that you could take away and use instantly to improve your PPC marketing efforts.

And its because of this great content that I think they deserve a special mention in this post. However I did notice that there is no section on Web Analytics, which I think is becoming an integral part of any online marketing strategy. So maybe I might be able to write a column for them on Web Analytics in an upcoming issue???

Either way I think it’s certainly worth getting hold of a copy.

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.

The first thing is that a guy called Eric Peterson has put out a survey to the industry and the industry has responded. Luckily for us the results of the survey have been published.

Points of interest in this suvery are:

• 82 percent of respondents say web analytics is poorly understood in
  their organizations and that the majority of people interacting with web
  data do not understand what the data means
• 56 percent say web analytics is difficult, despite the majority of
  respondents having at least two years of experience with these technologies
  and 23 percent having more than five years of experience
• 50 percent of respondents report having considered looking for a new
  job in the last six months

The next interesting thing is the release of the long awaited web analytic book by Avinash Kaushik which you can purchase from all good online book shops or through my Amazon link.

The final thing of note is the new wiki which has been set up especially for web analytics. I’m not too sure about this as we seem to be splitting off web analytics from other Search Engine Marketing technologies more and more, not too sure if this is the right thing to do but this wiki may well become a source of good information on the topic.

Thats it for now except that there is a new girl in town calling herself the Web Analytics Guru, feel free to share your thoughts regarding this new wiki, is it the right thing to do???

Click Fraud is when someone increases the number of clicks you get on your advert through fraudulent means such as creating a robot script or just getting lots of people to click the advert. The idea being that it can generate revenue for the website that is hosting your advert and/or cause the advertiser a fraudulent loss of income.

How to Stop Click Fraud
Below is a list of how you can identify when you are a victim of click fraud.

1. Install a web analytics package to monitor the traffic through your PPC campaigns
2. Track your PPC campaigns accurately in order to identify which ones are being abused
3. Look for spikes of traffic coming from each of your campaigns
4. Analyse the geographic location of our PPC traffic ensuring it is coming from the countries specified by your PPC campaign
5. Look at the bounce rate of your PPC campaigns, if you receive lots of traffic that mostly bounces then either your landing page needs work or you’re a victim of click fraud
6. Look at other measures of quality for your PPC traffic including total time on site and the page views : visits ratio

If you have an opinion on click fraud and how you identify it, please share your thoughts by adding a comment below.

Lets take the example of this blog. I measure the number of visits, unique visitors, RSS subscribers, internal search keywords, external keywords and referrers. From this data I can calculate the number of visits via my RSS feed as another metric and a KPI as the number of RSS visits per RSS subscriber.

The main purpose of my site is to provide educational information to people interested in web analytics, to achieve this purpose my main objective is to increase the readership of my site. So my new KPI will effectively let me know how one aspect of my readership is doing.

So, I have identified my site purpose, objective to achieve my site purpose, a method for measuring my site objective and based a KPI on this method. Over time I would hope that my KPI of RSS readership per subscriber will increase.

How Many KPIs Do I Need?

How many KPIs can you handle? 5? 6? 20? It is said that people can only handle a maximum of 7 pieces of information at any one time, so with this in mind I would suggest no more than 7 KPIs on a dashboard per person.

You should use the rule that if you have a KPI that someone could not make a direct business decision based upon then that KPI is useless and should not exist.

Who Needs KPIs?

The only people that need to know the value of KPIs are those people that can act upon them, this is reiterated in the table from the previous part of this methodology.

What is a Tracking Plan?

To be honest this is just a glorified name for taking the above table and populating it. To achieve a goal you normally need a plan to get there, be it in business, in life or with your website. This table is my version of a plan for achieving your website objectives. The idea being that you fill it out once when you design your website, but it is not just left, instead it should be a living document that grows and changes just as your business changes. Set a quarterly review cycle for looking at the table and seeing if the KPIs set are still relevant to your business, or has the market/technologies changed in a way that you need to meausre success in a different way. For instance if you initiate an RSS feed on your site then you will need further KPIs to meausre the success of this RSS feed.

Part 3 will cover capturing your web analytics data, picking the right tool and hiring a web analyst.

Catch up on other parts of the web analytics methodology and subscribe to my RSS feed by clicking the orange logo at the top right hand side of this window.

Firstly, it was hosted in the trendy Leicester Sq. Ruby Blue bar which was a great improvement in my eyes as we had our own room with its own bar. Unfortunately it was raining so the numbers appeared to be a little down on the last event despite more people registering this time, but alas we can´t control the weather.

We started the night with a short presentation followed by a disucssion based forum around the subject of Search Engine Optimisation using web analytics. Myself and one of my colleagues (Bob) hosted the presentation and started things rolling with the discussion. However I don´t think the audience expected to have to participate as it seemed a bit of a struggle for them to speak, although I did have some valuable asisstance from
Rufus at Clickstream. This was a whole new area for me as I´ve never done a ´public´ presentation before and there is a lot to learn for me from this event about getting people in the right mood for talking and how to read non-verbal feedback from the audience.

But anyway we will take inspiration from this event and hopefully make the next presentation even more engaging, if you were there and have any suggestions for me (or Bob) then please leave a comment on this post.

Unfortunately I had to leave straight after the presentation due to personal commitments but i am assured that the rest of the evening went well with some interesting people turning up like web analysts from ITV, BT and Channel 4.

So what were people talking about in the discussion?
Well, there was mention of the lack of tracking ability of web 2.0 technologies such as podcasting and videos. Someone mentioned the Comscore cookie deletion rates, personally I think this topic has been done to death and people just need to realise that web analytics is not an exact science and probably never will be.

There was a debate about what the best type of web analytics was, should you investigate erroneous data points in your graphs, just report the data or simply test different campaigns using A/B or multivariate testing. Our argument was that you should do all three but I don´t think there was any sort of concensus with that one.

That´s about all for this WAW summary but if you want some info on when the next one is then go to the SCL Analytics website.

Now 99% of people looking at their web analytics will want to concentrate on analysing visitor traffic rather than what the robots and spiders are doing and looking at. Given this it is important when analysing web server logs that you accurately identify robot and spider activity. With this in mind I have written a short checklist of things to look out for that may indicate a robot or spider.

• User agent, this is the browser that is displayed in your Browser report. Well behaved robots and spiders will identify themselves within their user agent string and as such they can be quickly identified and removed.
• Visitor duration, this can be seen in a visitor report along with the total time online metric. Given this informatoin you should also be able to see for one particular day whether a visitor has viewed over 100 pages in 1 or 2 visits or maybe spent all day on your website. These kinds of behaviour are common of robots and spiders and as such should be removed.

Other ways in which you can clean data represented in your web server logs are listed below:

• Excluding internal IP address, the aim of this is to exclude any internal traffic that may be accessing the website as this would scew the visitor behaviour. If you are running on dynamic IP addresses then you may want to think about tainting your browser’s user agent string to include your company name then exclude internal traffic by user agent. A quick search on google for modifying your user agent should point you in the right direction for this.
• Excluding irrelevant pages, if you have pages live favicon.ico and robots.txt or your /admin/ directory then you may wish to to exclude this data as there will be lots of requests for these pages but they are more like web site resources rather than requested page views. Unless you are monitoring your admin area usage, this data will not be of use to you.

The final thing I am going to mention is really that an analytics package can only ever report on the data that it is given. So if you page report looks a bit cryptic then you may want to consider rewriting your URLs in a user friendly way rather than using dynamic URLs. Also making data available via the querystring in the URL will help when it comes to analysing your web server logs.

If you feel that I have missed any other important items that should be removed from your web logs then please post a comment and let me know.

Thanks

This post is the sequal to Tracking your email campaigns and will build upon the tracking concepts used within that post. The previous post on tracking allows you to identify visitors who read the RSS feed then visit your site through a link in the feed. So that method will go some way to providing a readership metrics for our RSS content.

A readership metric is great, what about subscribers?

We can track the number of subscribers to a RSS feed in a number of ways, but after a few hours of research one method stuck out. This was to taint the feed URL for every visitor with a random value. Then all you have to do is count up the values and that will give you a subscriber count.

Below is an example feed URL that has been tainted.

http://www.webanalyticmatt.com/feed/?ID=1234

In this case we could count the number of ID values to give a subscriber count. Now this is fine but my method is to take this one step further and have the random value as the persistant cookie value for that visitor. By doing this we can actually identify the visitor even more accurately than using cookies because the feed request becomes the visitor identifier. Therefore it is possible to constantly update the visitor persistant cookie, even if it has been deleted to reflect the original cookie value.

Obviously this method is not without its problems, but luckily the negative effects can be minimised.

For instance you cannot let the search engines get hold of the RSS feed URL as search engines seem to favour RSS content over native web content. To ensure this, make sure your robots.txt file denies access to your RSS feeds.

What if someone syndicates your RSS feed on their site? Well your readership metric should hopefully increase but your subscriber metric will not be changed. Not a great thing but I think it’s an acceptable risk.

No more pinging your RSS feeds to RSS search engines. This would obviously defeat the point of counting of counting subscribers as you would be promoting one subscriber ID which may actually represent many people. But if your content is any good and your search engine optimisation is up to scratch then you shouldn’t need to tell the RSS search engines where you are.

Now the finale, I have read a few blog posts on tracking RSS subscriber numbers but the one thing that differentiates this post is that I am confident enough to implement it on my own blog as well as any site I am working on. To see, just subscribe to my RSS feed.

NLP has a number of presuppositions, which are things that may not be true but might be nice to pre-suppose. These include ‘everyone looks at the world using their own map of the world created by their own experiences.’ and ‘everyone tries to pick the best option in any given situation.’.

So what does this have to do with online marketing?

Well, let’s take the situation that you have a website and you track your visitors to the site using a web analytics tool. Your site receives traffic as a result of your SEO and SEM activities. So, you can drive traffic to your site and you can analyse the traffic to learn insights from traffic patterns etc.

Now up until this point you will have been looking at various metrics and KPIs but have you lost sight of the fact that these numbers actually represent real people. It is often very easy to fall into the trap of forgetting that your not trying to attract more numbers but in fact you’re trying to reach out to more ‘people’. This is where NLP falls into place in online marketing as it emphasises the ‘people’ aspect and makes you think about how it is best to communicate with your website visitors.

This all ties up nicely with visitor segmentation, this is taking your website visitors and splitting them up into groups based on commonalities. These common aspects may be geographical location, age, gender, job title etc. or they may actually be based up the communication style of your visitors.

A neat way of looking at this is to create personas of your target market segments. Personas are example people within your target segments and are a good way of ensuring that your marketing activities are aimed at the right sort of people. So, you might have a persona called Sam who is a marketing bod in a small company in England who is given a small marketing budget to work with. Sam enjoys playing basketball and socialises regularly with his colleagues from work. With the added NLP edge we might add that Sam is a very visual type of person who learns and understands best when concepts are explained using pictures. This aspect may be common within that one particular market segment and will allow you to communicate better and ultimately sell more to that group of people.

You can test to see which type of communication method works best with a market segment using standard A/B testing, maybe with an email containing images and one that only has text. But remember that communication methods are not always about visual, auditory and kinaesthetic ways of looking at the world, preferred tone of voice and style of writing can be different between market segments.

In conclusion, I just wanted to open up your minds a little bit to another aspect of online marketing rather than pure metrics and numbers. Remember that you are selling your products and services to people and where ever people are involved you have a psychology aspect which can prove to be extremely useful in increasing conversion rates!

If you want to hear more about how psychology fits in with web analytics and online marketing then leave a comment below and I will come up with some more examples of where I’ve used NLP to improve websites.

• What’s all this ‘web analytics‘ stuff then?
• What’s the difference between your product and Google Analytics?
• What information can web analytics tell me?

But its not just passers-by that ask that last one, no, its some of our new cusomters aswell.

One of the things that we ask at the beginning of any web analytics implementation is “What information do you need from your shinny new web analytics solution?”. Sometimes i’m suprised when the customer brings out a long list of required reports and KPIs (Which is great!), but most say “What information can I have?”.

So in preparation for that moment when you need to pull out that list of reports and KPIs I have prepared a few questions that a good web analytics application should be able to answer. Have a think over these questions which should hopefully get your brain cells in the mood for coming up with your own specific list of requirements.

Lets start off with the basics :-

• Which sites are my visitors coming from?
• What is the most popular keyword people are using to find my site in the search engines?
• Is the number of visitors to my site going up?
• What is the most/least popular path through my site?
• Where do most people leave my site?
• What is the most/least popular page on my site?

For the content writers :-

• How long do people read each article?
• What is the most popular topic?
• What content causes people to go on and convert on the site?
• What topic should I stop writing about?

For the marketers :-

• What is the best converting keyword/page/referrer/landing page/marketing campaign/path etc..?
• Where do people drop off my sales funnel?
• At what point do people stop filling in my sign-up form?
• What is the return-on-investment of my marketing campaigns?
• Which converts better, paid or organic search traffic? (Clue: Organic mostly!)

For the web developers :-

• Which part of the website is broken today?
• Which web browsers should I adapt the website for?
• If I create a new Flash demo what percentage of our visitors won’t be able to see it?

For the boss :-

• Is the web site making me more money than it is costing to maintain?
• Which member of the web team should I promote/fire?

There we have it, a basic and general list of questions that your web analytics system should be able to provide for you. For more contextualised information either look inwards for the questions or ask your local web analytics consultant.

Of course I am talking about web analytics, but what is this technical term that you hear spoken about at marketing conferences?

Well, web analytics is simply looking at where people go on your website and how they interact with your site. The reason you might want to peer into the world of your website visitors is simple, to learn from their actions so that you can improve your website conversion rates.

This is achieved in many ways, for instance you can find the paths through your website that convert the most visitors, or you could find out what content is attracting your target market segment. You may think that the answers to these questions are obvious to you, but there are always lessons to be learned from your visitor’s behaviour on your website.

Once you have made the decision to proceed with web analytics there are a few things you should know.

1. A web analytics implementation is not a 1 hour process, in fact to do it properly a project should be created to ensure that the process is properly managed from start to finish.
2. Web analytics is an ongoing task and not just a one time fix for all your marketing woes. Web analytics may start at just one hour a day but in my experience I have found that once you start providing detailed web information, people in your company will sniff the coffee and wake up to the realisation that this is real and actionable information. At that time the web analyst becomes the provider of information and becomes worth their weight in gold. We have seen this happen in America where web analysts with only a few years experience are being hired for $100,000 a year. The UK is following suit with a growing market in web analytics.
3. The other important thing to know before you embark on your web analytics voyage of discovery is to outline your desired outcomes.

Outlining your desired outcomes means that you have to write down somewhere what you want to do with your web analytics information. Do you want people to interact more with your brand? Buy more of your products? Do you want to grow your website traffic?

You should create these outcomes and put them in a table with three columns as shown below.

In the first column you should define your overall objectives for your web presence.

In the second column you should put all your desired outcomes in order to reach your objectives.

In the third column you should match up the desired outcomes with the person who cares about that outcome. Let’s say your outcome is “Write content that attracts your target market share.” I would imagine that the marketing department and especially the person/people who write your website content would like to know what content is attracting the ‘right’ traffic.

This table will be useful when customising your web analytics solution to your business and sending the right information to the right people, as in the people who can take action.

The way in which this information reaches people is vital.

If your content writer is sent the number of views, visits, visitors, bounce rate and view:visit ratio then they may get overwhelmed with the technical jargon. However if they are sent the number of readers, the reader to comment ratio and the article relevance numbers then they might mean something a little more obvious to the content writer.

So information is near useless unless it is given some context, this is where Key Performance Indicators come in. They allow information to be presented in a way that is familiar to the business. Importantly, these metrics should be ‘key’ to the business and provide an ‘indication’ as to whether the website is ‘performing’.

Part 2 of the web analytics methodology will continue with how to define KPIs for your business along with the next steps of your web analytics journey.

A quick note to remind you that no matter what type of website you have, be it Flash, AJAX, dynamically driven using Coldfusion, all website traffic can be tracked its all about how much effort you wish to put in to tracking.

I have compiled a short list of what I see as the most trackable types of site with the least amount of effort required.

1. Flat file html web page sites with really clear directory structures and page names, the kind your SEO (Search Engine Optimisation) company would/should create.
2. Dynamic websites in PHP, Coldfusion, ASP, .NET etc. where all user entered values are output to the URL. Eg. http://www.bookassist.com
3. Dynamic websites that use one page like index.aspx and pageid values for every single page.
4. AJAX websites.
5. Flash websites.
6. Websites that mix any number of AJAX, Flash, flat file and dynamic elements.

Most of these types of websites you can use page tags or log files as your data capture method of choice however it is only possible to capture data for the following site types using page tags. Be aware that when implementing a page tagging solution that you should plan what data and where it should be captured very carefully to avoid misinterpreting your web analytics data.

• Flash
• AJAX

So why are flat file web sites easier to track than Flash files?

Well data from Flash files has to be collected by specifying the user events to track, this is done using page tags. Flat file websites store all their data automatically in web server log files by default.

That is not to say that page tags cannot be used for flat file websites, there are advantages and disadvantages for both page tags and log files.

In conclusion not all websites are created equal but they can all be equally tracked with varying degrees of effort.

But this idea of taking our plain web 1.0 metrics and turning them in to something funky and web 2.0 like got me thinking about other useful web 2.0 metrics or KPI (Key Performance Indicators) I can think of.

So we have:

• Attention - time online for an average visit
• Visitor participation rate - a conversion type metric used to measure if a visitor participates in web 2.0 activities such as posting a comment or submitting an article to Digg.com
• Visitor consumption - how much content a visitor consumers which could be like the number of page views they see, but obviously it could also equate to AJAX/Flash events
• Feedback rate - the rate at which a piece of content receives feedback via user participation, for example this could be based on average comments per blog post
• Subscription rate - the rate at which content is subscribed to via RSS/Podcast/etc based on the total number of views of that content
• Activity rate - the average time a visitor moves from page to page or event to event during their visit
• Consume -> participate rate - a value based on the number of times a piece of content has been consumed which has led to visitor participation
• Content loyalty - a rate based on the number of types of content a visitor consumes over the visitor lifetime

With any good web analytics package all these metrics are fully achievable, obviously given the data to analyse. But the questions are:

• “Are they any good as web 2.0 metrics?”
• “Do they hold enough meaning to base business decisions on?”
• “Can you think of any better web 2.0 metrics?”

Go on, post a comment and in a few days i’ll update this post with my “consumer -> participate rate” based on your activity.

Update: after 14 days this post has 0 comments, I would say that the consumer -> participate rate is 0%, I guess no more talking about Compete metrics then

Once you scratch the surface of web analytics you will find that its a big subject with lots of facets. As such I have split this methodology into managable parts that will be posted on my blog over the coming weeks.

The contents of the methodology looks like this:-
Part 1

• What is web analytics and why do I need it?
• Defining your desired outcomes
• Measuring your outcomes with KPIs

Part 2

• Defining your KPIs
• Who wants what information?
• Your tracking plan

Part 3

• Defining your data capture plan
• Picking a web analytics tool
• Hiring a web analyst

Part 4

• Implementing your web analytics solution
• Monitoring using your analytics
• Turning analytics insights in to actions

Subscribe to the RSS feed now to avoid missing any of the 4 parts.

Read part one of the web analytics methodology
Read part two of the web analytics methodology

It was definately not like the other events such as TFM, Adtech and SES. There were I think no more than 200 people in what appeared to be a well organised networking event. As well as the opportunity to swap stories about how your company deals with web analaytics challenges, there were seminars throughout the event.

The seminars ranged from competitive analysis to behavioural targeting and some of the topics were really very indepth like the web analytics methodology presented by the web analytics team for Nokia.

Personally I found it good to put some faces to the names I have previously heard in the web analytics market such as Jim Sterne, Avinash Kaushik and Miles Bennett.

The main things that I learned from the event were about the behavioural targeting space. With Touch Clarity just being bought by Omniture it was suggested to me that Omniture had just taken the one partner in the market that everyone wanted to partner with, leaving a gaping hole in the market. It was also suggested that the people to take the place of Touch Clarity are the multivariate analysis outfits such as Optimost seeing as Touch Clarity were doing behaviour targeting combined with multivariate analysis.

I wonder how long it will be before Google Analytics bring in their behavioural targeting? Especially as they already have the multivariate analysis piece in place with their Google Optimizer.

Anyway, the event was good from what I saw and the food at the Russel Square Hotel was absolutely amazing, the best cake i’ve had in quite some time.

If you went along, let me know what you thought by adding a comment below.

The plugin is a bit heavier in size now but that doesn’t appear to have an impact on page loading times. If you want to test this plugin side by side with its previous version then this is possible and should not cause any conflicts.

You can download the logger2.zip file containing the PHP script at http://www.webanalyticmatt.com/plugins/logger2.zip

As usual just unzip the file into your plugins directory and activate it in your wordpress administration area under plugins. Once activated the screen will go blank but don’t worry about that. If anyone knows how to get round that little bug then please let me know.

Thanks

I’m going to make the bold claim that web analytics can boost the performance of ANY website. But it can also just provide some pretty numbers and graphs that give you no value whatsoever.

In order to achieve the former situation you need a little expertise. Hopefully this post can provide you with some real techniques to start improving your website performance. Importantly, this post assumes that you have a pretty good web analytics application like Google Analytics or Unica NetTracker.

Technique #1 - Conversion Metric
This shoud be the basis of most of your basic web analysis. Your analytics tool should allow you to define a conversion metric for your website.

A conversion is where a visitor to your website has carried out an action on your site which benefits your campany goals. This could be that they have purchased a product online, they have given you their contact information and become a lead, or even that they stayed for longer than 5 minutes.

So a conversion event should be based upon some form of trackable visitor behaviour.

Once you have this conversion metric you can then use it in conjunction with some of your web analytics reports to fine the best converting traits of your website visitors.

Technique #2 - Referrer Report
The referrer report shows you where your website traffic has come from. This is useful information as you can define which web links drive the greatest levels of traffic to your site.

For example, if wikipedia links drive hundreds of visitors to your website then you may wish to add more links on wikipedia or other wiki sites to drive greater levels of traffic to your site.

Quantity is not necessarily quality
This is where your conversion metric can help fine tune your link building. By creating a report of your referrers then applying the conversion metric you can see which referrers give you the most benefit.

It may be that wiki sites give you the most traffic but that directory sites give you the highest levels of conversions.

Then your actions would be to increase the number of links to your site on web directories. This is because a referrer that provides 50% converting traffic is better than one that gives a 2% conversion rate. So build up the levels of the best converting traffic.

This same concept of using conversion rate as a Key Performance Indicator can be used in conjunction with other wb factors such as keyword, page, content area, geographic region of visitor, visitor path and advert landing pages.

Technique #3 - Path Reports
A path report shows the most popular visitor paths through your website.

By using your path report in conjunction with conversion rate you can decide which path you want to drive visitor traffic down.

Another good way of using path reports is to identify the most popular path overall. Once this has been identified you can then use this information to plant calls to action along this path in order to increase your conversion rate.

In my experience I have found that it is often easier to increase the conversion rate of your most popular path than it is to drive more people down a high converting path. This is your ideal path may not be the ideal path of your visitors, and changing their behavioural patterns is often very difficult.

Technique #4 - Scenario Funnels
A scenario funnel or funnel report is one that look at a single path through your website or a website process like a checkout process on an e-commerce website.

Using a scenario funnel you can identify where your visitors are failing to reach each stage of a website process or path. You also get provided with a conversion rate for each stage within that one website process. This can be very useful for finding out what stage of the process is failing at to what extent.

Lets use the checkout process as an example. The diagram below is from Unica NetInsight.

The 3 stages that we want to look at are

1. Entering the checkout
2. Entering credit card and personal details
3. Confirming your delivery address

As we can see from the graph above there is a huge drop in conversions from stage 2 to stage 3.

Using this basic information we can then decide whether to investigate why stage 3 is causing people to drop out of the checkout process. Or you may decide to remove stage 3 entirely which increases your conversion rate immediately from 4.9% to 22.3%. That alone could be a huge jump in website revenue.

There are of course certain limitations to scenario funnels which should be understood when looking at these types of reports. An explanation of these limitation can be found here. Understanding Funnel Reports

Technique #5 - Content Groups
A content group is a way of clustering related website content together. This adds value to your web analytics by creating a form of business context around your website content.

This means that you can compare the content areas that matter to you and your business.

The advantage of this is that it too can be used in conjunction with your conversion metric, showing which area of content contributes the most towards conversions.

Obviously the action to take from this information is to create more of the best converting content. Bare in mind that could be articles, but it could also be product categories, products or even popular downloads.

This post aims to show you how to effectively track your marketing campaigns and more importantly, show you what is possible with this information.

As with all information analysis you need to define up-front why you want information, what its purpose is, what you will do with the information and what information you require. Once you have written down these things, you can then begin to plan your marketing campaign tracking implementation.

Lets take an example of a television advertising campaign which is designed to drive traffic to your website. TV adverts don’t come cheap so you will want to know if web traffic increased as a result of your advert, did the traffic convert into sales and is it worth running TV ad campaigns in the future?

To gain answers to these questions you will need o identify the web traffic as being generated as a direct result of the TV advert. Once the traffic has been identified it can then be tracked through your web analytics tool to find out if it converted into sales which will answer whether the TV campaign is worth repeating. You could also glean the return on investment (ROI) of the ad campaign by then taking those web conversions and seeing how much revenue they generated in comparison to the cost of the ad campaign.

Here comes the tracking
Every ad campaign will normally contain at least 2 elements. The first is a marketing message that you wish to convey, something like “My product is the greatest!”.

The second element is a call to action which specifies the viewer to carry out an activity, something like “Go to my website at www.webanalyticmatt.com and buy my stuff!”.

It is this call to action that we are going to focus on. We need to make this call to action unique to all other website traffic and other marketing campaigns. To do this we use a number of name = value pairs in the query string of the URL of your site. A query string is everything after the ? in a URL.

An example tracking URL might be www.webanalyticmatt.com?campaign=salesgeneration&channel=tv
&segment=sky1&advert=3&dateofad=22-march-2007

Now, the first thing I think when I see that URL is “No way is anyone going to type all that in to their web browser!”. Luckily we can do some HTML redirection magic to turn that complicated URL into www.webanalyticmatt.com/free. (Heres a PHP script to get you started.) So on the call to action you just need to tell people to visit the shorter, vanity URL which will automatically redirect into your tracking URL thus making your ad campaign traffic trackable.

Breaking down the tracking code
In the above example I used the following codes in the trackable URL:-

• Campaign
• Channel
• Segment
• Advert
• Date of Ad

These codes should be used across all of your marketing campaigns so that they can be compared on a like by like basis. Consistency is key.

Campaign defines the overall marketing objective for that marketing campaign.

Channel defines the distribution channel for that marketing objective to be realised.

Segment defines the individual marketing message or audience for that message.

Advert is the individual advert shown which has driven the traffic to the website.

Dateofad defines the data on which the advert was released, as the same advert may be released a number of times to difference audiences and on different dates.

Using the above tracking codes and the right web analytics tool you can have the tracking granularity to ask most business questions about the traffic your marketing campaign drives to your website.

These tracking codes are specific to adverts but hopefully you can see how they could be generalised and then used for any marketing campaign that had a web element. Example campaigns include TV ads, pay-per-click advertising, link building, affiliate schemes, banner advertising, email campaigns and offline print adverts.

If you come up with a truely generic set of tracking codes the please share it with your fellow marketers by posting a comment below.

A typical graph shown on a funnel report is shown below.

Elements of a funnel report
Funnel reports are defined by identifying each stage within the funnel. This identification is normally based on profiling your website visitors, possibly by the pages they visit but it could be by any online behaviour.

For example in a checkout process you might have 3 stages:

1. Entering the checkout
2. Entering credit card and personal details
3. Confirming the delivery address

It happens that these 3 stages are based on page views within the checkout process.

Another element of the funnel report is the visitor drop off value. This value is shown for each stage within the funnel and shows how many visitors have dropped out of the process at each stage.

The final element of the basic funnel report is the conversion rate metric. This metric is shown for each stage of the funnel except for the first stage and shows the percentage of visitors that have converted or reached the stage from the previous steps.

Common misunderstandings
Funnel reports are not always as they seem. Lets take the example of analysing a web form with multiple fields. You may wish to know where visitors are dropping off of the form.

The funnel report shows the number of visitors who have completed all stages within the funnel. Importantly there is no explicit order in which these stages have to be completed and the visitor may have gone to other pages within the site between stages of the funnel.

So perhaps a funnel is not the best visualisation for this kind of report. If we use the example of the web form then lets use the data visualisation shown in the Venn diagram below.

The above diagram shows all the people who filled out field 1 of the form in red, visitors who filled out field 2 in green, visitors who filled out field 3 in blue, visitors who filled out field 1 + 2 orange, visitors who filled out field 2 + 3 in grey, visitors who filled out field 1 + 2 + 3 in black.

From this diagram you can see every possibility of the 3 form fields being filled out but the funnel report will only show data in red, orange and black. This is assuming that the funnel is ordered by the field numbers.

So why don’t the web analytics tools show this visualisation? My excuse would be the complications involved if there are over 3 stages as the diagram would have to be in 3D to show all possibilities. A 2D version of a Venn diagram is only ever possible when you have a prime number of stages.

My personal feeling on the best type of visualisation for analysing form fields would be a line graph as shown below.

You can see that there are 9 fields and that people drop off the form at field 2 and 4. If you can think of some better visualisations then please post a comment below.

What are the uses of this funnel report information then?
Despite the downsides to funnel reports you can still get a lot of useful information from them and use that information to make accurate business decisions.

As long as you use funnel reports to track exact paths such as website processes where steps cannot be bypassed the visitor drop off and conversion rate metrics are very useful in working out what steps of the process need improving. From this data you can investigate further to see if there are commonalities with the visitor drop offs and and work out how to improve the offending steps.

So, why would you want to track your email campaigns? What are the benefits?
You need to track your email campaigns so that you can differentiate the email shots that work from the ones that don’t, only then can you attempt to identify why some work and some don’t.

If you know which email campaigns drive traffic to your website, you can then start tracking which links within an email shot drove people and which didn’t. Ideally this means that you can, over time perfect your email campaigns for your market and get the best possible return on investment (ROI).

As well as knowing which email campaign drove traffic, you can also find out which campaign converted the most traffic and so track that all the way to how much money you made as a result of that one email shot. This is a true reflection of marketing ROI.

And how do we do this magical tracking?
Firstly, it isn’t magical. It really is very simple and embarrassingly easy.

Lets take an example of a newsletter sent out to 3000 current registered website users. Importantly you know who each one of those users is,