1. Over time will departmentalised/silo-d analytics areas become part of a larger research and analytics function reporting directly to the Financial Director or chief executive officer? Presenting completed analysis or recommendations to executives can be far less effective on an on-going basis than the continuous, informal questioning and answering between managers and analysis. I think you need both, on-going silo-d analytics which really drills down into specific issues and centralised strategic analytics to align web analytics recommendations and objectives with overall company objectives on a strategic level (so there one number of how many customer’s you actually have rather than a politicised struggle between marketing and customer services departments for example).

2. Analytics is hard. Analytics takes resources. It takes effort for a company to create and assimilate learnings from analytics. Focus your analytics at the key leverage points of the business, for example in the case of a lead generation site such as rightmove your lead conversion rate. Focus analytics where it will have most impact to potentially help and change the business

3. Getting to a culture of fact/data driven decision making, requires your business to have real solid wins using analytics that will make people care from the top to bottom in the company. Once it is have been shown/proven that the eg the company’s conversion rate has increased due to multi-variate testing and changes to the form process or that PPC is generating a higher conversion rate or whatever the wins might be, a process of “yes analytics is important to me – it will help me – it could even help me get the bonus that I want” begins from people all over the company. I love multi-variate testing as well as the ultimate measurable way to prove to senior management.

4. The analysts that you hire are extremely intelligent, humble, versative and political creatures that are in constant communication and debate with key decision makers and are at home with numbers and all the advantages and pitfalls of various analytics solutions, but most importantly are able to move beyond creating key performance indicators to aligning strategic business objectives of the website to the company’s business.

5. Well thought-out metrics that everyone in the business understands. The challenge is creating a shared understanding of the right metrics and what they mean.

6. Don’t rely on one proven and tested way to get insight. Try usability testing, try feedback forms and survey, try sophisticated metrics, try scoring systems, try multi-variate testing, digging into the data to understand root causes and opportunities.

7. The most important thing with analytics is to get started. It is a journey not a competition. And each company’s journey will be different. Good analytics is an evolution of thinking and deciding.

Social networks online, such as Facebook and Myspace are becoming more and more important. Increasingly, marketing through these online social networks will become ever more prevalent. For example, web apps / application onto Facebook’s open API (which means external programmers can add programs and applications to facebook – not just facebook employees). Another example might be someone with a lot of social capital (ie contacts and influence online), in turn influencing their friends, contacts and others exponentially in theory due to the fluid nature of a social network to buy a product or service. Related to this but slightly different, Blogvertise is a service which pays bloggers to promote a product or service related to the blogger’s field of expertise.

Onanalytica does online buzz monitoring. Measurement of influence is key!
Influence is the “weight” of each voice. Alternatives: Treat all voices equally, use gut-feeling or equate popularity and influence – all are really bad. Onanalytica’s methodology has been used in the academic community for more than 30 years to measure the influence of academic journals and is a huge mathematical challenge known as an input-output model in econometrics.

You get the gist. This is all seriously fascinating marketing.

The 2 things that absolutely fascinate me are:

1. The major challenge facing marketing strategists in how to increase the effectiveness of social network based marketing strategies.
2. The future marrying of web analytics and social network analysis and resulting improved marketing effectiveness and business intelligence.

Measuring the influence of myspace visitors
MIT Media Lab / Social Media Lab designed a flexible tool for the content driven exploration and visualization of a social network. Building upon a traditional force-directed network layout consisting of nodes (profiles) and ties (friend-links), the system shows the activity and the information exchange (postings in the comment box) between nodes, taking the sequence and age of the messages into account.

In the myspace service network-only visualization methods are no longer sufficient to meaningfully represent the community structure. Numerous commercial profiles, fake/spam/celebrity profiles and tools such as automated friend adders result in a huge numbers of connections, many of which carry little information about a person’s actual social ties and behavior. The average myspace user has more than 130 friends, but there are also profiles with over a million “friends”. By going beyond the “skeleton” of network connectivity and looking at the flow of information between the individual actors, the authors hope to create a far more accurate portrait of online social life.

What is social networking analysis:
Social network analysis has emerged as a key technique over the last century in modern sociology, anthropology (good thing I am a qualified anthropologist), sociolinguistics, geography, social psychology, information science to measure what individuals do and the many types of relationships between one another. And now social network analysis becomes important in web analytics. Social network analysis sees social relationships in terms of nodes and ties. Nodes are the individuals (visitors) within the networks, and ties are the many types of relationships between the individuals.

Two Social networking analysis metrics (an introduction merely):
Read Judah’s thought provoking post for more social networking analysis metrics and opinions.
Betweenness:
Degree an individual lies between other individuals in the network i.e it’s the number of people who a person is connected to indirectly through their direct links.
Centrality Closeness:
The degree an individual is near all other individuals in a network (directly or indirectly). It reflects the ability to access information through the “grapevine” of network members. Thus, closeness is the inverse of the sum of the shortest distances between each individual and every other person in the network.

Marketing in social networks
Jason Ethier has written a good paper on social networks. He tells us that the main questions for researchers in social network theory are which types of social networks can be used as a basis for marketing strategy, how to identify and measure social networks, how to mobilise and manage social networks, and which marketing decisions can benefit the most from social network concepts and methods? Researchers have found that consumer networks that are not under the control of a corporation work best for marketing purposes which is why networks such as facebook and myspace are so successful. Corporations identify and measure social networks by collecting information from their customers. One method of doing this is by distributing loyalty/discount cards (large retailers do this) in exchange for customer information.

To conclude:
Social network theory and analysis and their marrying with web analytics is certain to become ever more prevalent as more companies learn of the marketing potential of social networks. And hopefully will become more mainstreamed into web analytics as a whole and into the web analytics solutions themselves. (hopefully anyway)
I welcome your feedback, thoughts or complete disagreement – so please share your thoughts and most importantly, THANKS FOR READING!

Index tools goes free – I had the pleasure of using indextools on a couple of websites last year – and can honestly say that it does favourably compete with other much more expensive tools. So, going free with Yahoo is very good news for business (and for Dennis Mortensen – congrats). Lots of talk of whether indextools (yahoo) analytics will provide serious competition for google, depends on how seriously yahoo take their new web analytics solution.

The founder of venture capitalism in America,Georges Doriot (aged 21, Doriot sailed by steamship to the US from his native France and went on to become a brigadier general in the second world war, one of the most influential professors at Harvard Business School and founder of Insead, Europe’s first business school. But his main achievement was to pioneer the US venture capital industry in 1946 by setting up American Research & Development (ARD), which backed one of the first blockbuster technology start-ups, Digital Equipment Corporation).

George Doriot famously said, his strategy relied on backing talent, not technology.

“An average idea in the hands of an able man is worth much more than an outstanding idea in the possession of a person with only average ability,” he said.Not that google analytics or index tools are average, as there is alot of vested interest, and subtle bad PR in this industry, in fact in the hands of a good web analyst, there are both powerful tools – Brian Clifton’s new book on advanced web metrics with google analytics is an example (I am going to his book launch party tonight so I am sure, I will see lots of googlers.) So we will how this one pans out over time, I imagine (with Dennis at the helm, I am sure Yahoo analytics will be a big success). The point being it is the people, the team behind the product that make it or break it (apologies for the cliche).

In the interest of web analytics and my passion for it, I am always, vendor neutral. My passion is in better understanding and improving online behaviour.

Thanks so much for reading and apologies for my recent (infrequent) blog posts, which I very much intend to change.

Segmentation and personas are areas of interest to traditional marketing departments. But now with web analytics, consumer segments can be set up and analysed real time and/or historically with many of the standard web analytics tools such as Google Analytics, Omniture’s Site Catalyst or Discover, Clicktracks or Webtrends.

If you look at the average conversion rate for your whole website, on it’s own although useful, would considerably more insightful if you could filter the effectiveness of different segments / people / campaigns – see the conversion rate of .
What do I mean by a consumer segment?

It could be PPC (pay per click) campaign traffic, or seo traffic, or email campaign traffic. Or a segment where people clicked on a banner or landing page on the website.

You can then easily compare the average conversion rates of these different segments and also bear in mind actual amount of traffic from each segment. For example, email campaigns might have a conversion rate of 4.2% compared to PPC traffic with a 2.6% but there might be significantly more PPC traffic than email traffic in which case, better to spend one’s time and efforts optimising PPC than email campaigns.

I’ll post some more on segmentation later this week. Thanks so much for reading!

Today is Web Analytics Wednesday (WAW) in London, on a Monday and Eric Petersen, the original founder of WAW will be talking about the future of web analytics.

Today at econsultancy’s digital cream, digital marketers, social media – ites, search – ites, and web analytics ites thronged together and debated. It was actually fascinating and informative so a big thank you to econsultancy for organising it and to all the staff for being so helpful. ( I just got back from just over two weeks holiday in Playacar and in the yucatan in Mexico – the photo is Tulum).

I went to the web analytics roundtable in the morning and the social media roundtable in the afternoon. At each, there were 7 senior marketers and a moderator all talking out their strategy, sharing ideas and revealing what they want to do. To the extent that competitors were even opening up and talking quite honestly about plans and site features that hadn’t even been launched yet.

As web analytics continues to shift into marketing optimisation, the big solutions like omniture and web trends differentiate by offering integrated multi-variate testing, behavioural targeting and integration in and out with external email solutions or databases so you only need one place to your fully integrated picture of what’s going on with your company,
Buy a web analytics tool first or hire the skilled web analytics person? Better to hire the right person first and use a free tool than spend the money on the tool without having the right person to get the analysis and insights out of it.

Social media is so fast moving. Yet for many companies there is still caution and worries about security, brand awareness and even how to measure it’s impact.

I know I’ve missed things out so get in touch if you have any thoughts about the event.

A little bit techy today. I know. But really useful stuff.

With Google Analytics, you have the ability to track how many products are bought on your website, with it’s ecommerce tracking. You can also use this for your website, even if you don’t actually sell products but to categorise your lead generation, pdf downloads or whatever the call to actions are on your website.

On your product bought / lead confirmation page, you will need your programmers to add some code to the page, after the main google analytics tracking tag.

For example, I can track what type of property, the country, the postcode, the specific ID, the number of bedrooms in the property, a fictional value of £10/$10 for each lead, the price that each property is on the market for, – all by getting the programmers to use a “get” for each bit of information I am retrieving from the website. But it could any important information about either your product sales or leads.

Category is really useful because that’s how you sort your products / leads into different buckets.
Product name and Product Sku are where two different fields where you can specify what details about your product or lead you want to be able to see in google analytics as your product details type information.
The others, like price etc, are pretty self-explanatory.

In this instance, I don’t use shipping and tax – because I am using the ecommerce tracking for tracking leads generated.
This is my sample code which goes on the product bought/lead confirmation webpage code:

pageTracker._addTrans(
“$property.getCountryCode() $property.getBranch().getID()”, //Order Id
“10″, //Total
“”, //Tax
“”, //Shipping
);
pageTracker._addItem(
“$property.getCountryCode() $property.getBranch().getID()”, // Order Id
“$property.getPostcode().getArea() $property.getPropertySubTypeName()”, //’SKU’
“$property.getPropertySubTypeName() $property.getBedrooms() beds”, // Product Name
“$selectedTab”, // Category
“$property.getPrice()”, // Price
“1″ // Quantity
);
pageTracker._trackTrans();

And this is what ecommerce categories ends up looking like within the google analytics interface, eg renting:

And here are product details eg 3 bed house.

This is extremely easy to set up, 20 minutes of a programmer's time, and once done, gives a huge benefit and understanding of either ecommerce usage or leads generated in exactly the way that makes sense to you.

Have you tried it out yet?

I have been unbelievably, ridiculously busy. Being a career mother, with a two year old toddler, in a big old city like London, makes for very challenging time management.

Anyway, excuses aside. I have been doing some fun and intense web analytic – ey type things recently.

Recently when doing some multi-variate testing, I noticed that there was a much higher conversion rate on exactly the same form page but for different types of property market. For example, when people were looking to rent, they converted at a significantly higher rate, perhaps a 20% increase in click through rate (CTR) from the property details page to contact the agent form page compared to people looking to buy a house.

So, I went into tealeaf to replay sessions for buying versus renting, conversions and non-conversions.

It was fascinating, because everytime there was a graphic displaying energy efficiency on buying, just above the call to action button, people weren’t clicking on the call to action button. So in other words, a product feature that only sometimes appeared for some products, was distracting attention from the call to action.

This is how I find people’s journeys – I either pick the url within the date I am looking at or free text (or many other search options).

Then I am able to watch, just like a video, exactly what happened on the website.

It’s quite amazing when you begin looking at internal site search.

Recently I started investigating the capabilities of google analytics’ site search and it really has a easy to set up approach with alot of useful metrics that you can define against it.

As long your website uses a url parameter before your internal site search keywords and additionally url parameters in the url to define the categories of internal site search, you can track your site search.
For example, the url parameters of a website might be www.companywebsite.com/searchpage?
search-alias=DVD;field-keywords=harry+potter
where search alias defines the category and field keywords defines the words that were typed into the search box.

You click on your profile, choose Do track site search, add your url parameter that comes up with the keywords that people type into the search box and then the url parameters that define the category on your website, that could be a product type (eg DVD) or a channel (eg rental) or whatever categories apply to your particular website.

Then within a few hours you can begin to what percentage of your visitors use site search, how long they spent looking at the site after a search, what percentage do more that one search (% search refinements), what categories they searched for the most, how did visitor behaviour differ from those that didn’t search.

In essence, there are many ways of really seeing how people are using site search on your site, and this can all be set up in a matter of minutes.

Whether you use tableau, business objects, excel or something else all together, visualisation of data and in essence ideas, is a huge part of web analytics. It is much easier to understand a good graphic than a thousand words and in fact they can be a beautiful and persuasive call to action.

I was inspired by a recent article in the Economist about the best charts ever dating back 200 years, long before the computers and tools that we take for granted today. And these visualisations, so elegant yet functional and powerful, were earthshattering at the time, influencing politics, policy and spend on a nation level.

“Three of history’s best” include… 

1. Florence Nightingale, remembered as the mother of modern nursing, was also a keen statistician (and first female member of the Royal Statistical Society) and her graphic illustrating the key causes of mortality during war contributed towards the improvement in military hospitals as it shows at a glance how many soldiers died from preventable causes ie infections and disease as opposed to infections.

2. Charles Joseph Mindard’s very famous 1861 graphic depicting the Russian campaign of 1812 – has been called the “the best statistical graphic ever drawn” as it illustrates numbers of soldiers by width of the bar, against falling temperature, against distance there and back (very few returned).

3. William Playfair’s (a bit of a swindler admittedly) 1821 chart comparing the “weekly wages of a good mechanic” and the “price of a quarter of wheat” over time attempts to illustrate a decline in buying power for example, which for it’s time was again revolutionary.