Analytics

Yet again Google has been busy releasing new Google Analytics features. This time it is related to speed and their quest to make the web faster! So what is the Site Speed report?

The report provides you with access to two additional metrics:

Average Page Load Time – The average amount of time it takes from clicking on a link to the page loading.
Page Load Sample – The actual number of page views that were sampled to calculate the average page load time.

Why is page load time (latency) important?

Slow site speeds can frustrate users resulting in them having a bad experience online or even worse, with them deciding to go elsewhere. By measuring and improving page load time it keeps your customers happy and in turn aids conversions. In addition Google take account of the metrics in their search results and PPC Quality Scores. Which in turn enables your adverts to feature in a higher position at a lower cost-per-click.

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Where do I find the Site Speed Report?

The Site Speed report is found in the new beta version of Google Analytics which is currently available to all users. After clicking on “New Version” in the top right you can then access the report from the Content menu.

How do I setup the Site Speed Report?

When you access the report, you will be probably be presented with lots and lots of zeros! In order for the site speed reports to work you need to add an additional method to the tracking code.

Asynchronous: _gaq.push(['_trackPageLoadTime']);

Traditional: pageTracker._trackPageLoadTime();

Why are we excited?

Here at Foviance we are really keen to explore the possibilities of combining these two new metrics with others dimensions or custom reports. This would help you answer questions such as: How do load times vary between country, region or city? Do certain browsers load faster than others? Which landing pages are the slowest to load? Should I be concerned about my site performance? So have a play and lets us know your thoughts.

When is retention not retention? When it’s just reacquisition! More and more companies are paying attention to customer lifetime value and how they can build on their investments in winning new customers. This applies equally to consumer organisations, business to business organisations, and membership organisations. All the heavy lifting has been done getting that new customer on board, but how can we generate more value and how does customer data analysis help do that?

The role of customer data analysis in retention is to increase the propensity that a customer will do business with you again at a lower cost than the first time they did business with you. There are two things going on here: increasing propensity and lowering costs. Increasing propensity is about making yourself more relevant by getting the value proposition message across. The more relevant you are, the more likely that someone will come back again, and by analysing your customers and their preferences, has the potential to make you more relevant.

In the digital world, we’re seeing a lot more use of classic offline retention strategies such as RFM (recency, frequency, monetary) analysis. RFM is a type of behavioural segmentation approach whereby customers (or visitors, or members…) are categorized on three dimensions:

•Recency – how recently someone transacted

•Frequency – how frequently someone has transacted in the past

•Monetary – the value of those transactions

The idea is that you can develop different strategies for different segments depending on where they are on each dimension of the RFM model. If someone is high on all three dimensions, then they are the most valuable customers that the company has and the retention strategy is to keep trust. There may not be a need for masses of activity as they probably have a strong affinity to the organisation or brand. However, they need nurturing and looking after, but you don’t need to “re-acquire” them. Customers who have low recency but high frequency are ones that are slipping away. Some kind of reactivation strategy is going to be needed to bring them back and it’s possible that that might require some kind of incentive.

Customers who are high on the recency axis but low on the frequency axis are new customers and they are a particularly interesting case. The main challenge for an organisation is to get them to buy again, and what customer buying theory shows is that recency is the strongest predictor in this model of whether someone will transact again at some point in the future. So if someone has just transacted with you, then that’s the best time to try and get them to transact with you again. That’s why in the retail catalogue world if you buy something you tend to get a new catalogue with your order.

Completely new customers are a special case because they generally require the most effort to get them to buy again. Once someone has transacted three or four times, it doesn’t take so much effort to get them to transact again. So getting someone who has bought for the first time to buy for a second time is incredibly valuable. In some of the work that we’ve done and I’ve seen others talk about, there is a strong correlation between someone’s propensity to transact again and the time that they receive some form of marketing communication. Again, this is really relevant for new customers; the quicker you can get some form of relevant message to them, the more likely they are to buy again.

This article was originally published by ClickZ

Note: Google Analytics has informed us that this feature, Multi-Channel Funnels, is a limited pilot. They are testing the feature and its usefulness to a small group of trusted testers; they have not made any plans or a timeline for a full launch.

How does Twitter, Search, Direct Traffic or Social Media each impact on the sales journey?  Let’s find out! As a Google Analytics Partner, last week we were lucky enough to attend the launch of an exciting new feature in Google Analytics – ‘Multi-Channel Funnels’.  It follows shortly after the release of the Version 5, allowing users to analyse the performance of marketing channels and how customers interact with them in a much more detailed way.  This new feature, will help our clients understand the sales impact of different marketing channels, and answer the age old question, where should those marketing dollars be spent?

This video best describes the new functionality

Looking at a typical user journey there are often many interactions that lead to a conversion.

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Traditionally conversions are assigned to the last click. So what was the last campaign, referral or search term that was seen? But don’t you want to know how the prior role interacted in the conversion? How do marketing channels work together in order to create sales? How much time was there between the initial and final interaction? How much money should be invested in social media compared to online advertising?

Multi-Channel Funnels brings all this data together so you can understand the impact of each visit to the website.  So now you will know the impact of a visit, even if it didn’t lead to an immediate conversion.  If your customer visits your site a few times, just to browse products before returning later to purchase, you will now be able to understand this journey. 

The funnels will consist of five reports:

1. Assisted conversions
2. Assist interactions
3. Top paths
4. Time lag
5. Path length

Let’s take a quick look at some of the reports. As you know understanding customer purchasing behaviour is one of the most important insights you can have. Using the path length report you can analyse the interactions that lead to a conversion.

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This is essentially an extension of the ‘Visit to Transaction’ report but now includes the ability to segment using either goal conversions or ecommerce transactions.

After gaining insight into the typical time between the first and last interaction, you may ask what the path actually looks like. Accessing the ‘Top Paths’ report, Google has grouped traffic into the following types:

1. Organic
2. Referral
3. Direct
4. Paid Advertising
5. Social Network
6. Email

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This video gives a detailed walkthrough of the Multi-Channel Funnel report.

Having had a play, the first iteration of Multi-Channel Funnels is very impressive and sets itself apart from many other analytics solutions currently on the market. Even a lot of the paid-for web analytics solutions cannot compete with this and I am pretty excited about implementing this and helping clients solve a problem they have debated for a long time.
Multi-Channel Funnels currently is only available to a limited number of users but expect a wider roll out to follow shortly.  Foviance is working with some our clients already to get them involved in the trial, so look out for more news from us when we get more results and feedback.

This article was originally published by Anna Richardson, NMA.

As the EU e-privacy directive is tightened in May, brands will have to be more open about the cookies they deliver to site users. This exclusive data explores which sectors will be most affected.

Tracking user behaviour across a website can provide invaluable data for companies looking to optimise customers’ experiences. But this May, the updated EU e-privacy directive comes into affect, requiring (among other things) site owners to provide visitors with information about how cookies are used on the site and give them the opportunity to refuse their data being collected.

Many site owners are still confused about which types of cookies will be affected by the new rules, and to what extent. Here at Foviance, we have been conducting cookie audits for media clients since the end of last year. Using a new cookie audit analytics tool to scan Hitwise’s most visited UK websites and gauge what types of cookies they use, in particular which ones might cause concern when the regulation rolls out.

Scanning more than 500 pages of each site, we extracted cookies that were sent to a user’s computer. Collecting these into a single database, we then analysed the information they were trying to store. They were segmented by function and by the type of data collected, to find out which sites and sectors are more likely to be exposed to the imminent regulation. The web pages were also scanned for known items that might set cookies, such as third-party software and plug-ins.

We then created an Exposure Index, which rated the likely impact of the new legislation on companies’ on-going ability to use the data collected by these cookies. Exposure was analysed both by the type of data being collected by cookies and consumer attitudes to brands using this type of data. Consumers are less likely to give explicit or informed consent to the use of cookies if they can’t see a link between sharing their data and any benefits to them.

There’s still a lot of uncertainty about which cookies might be excluded from the new rules, and the impact of functional cookies is particularly complex. Using a cookie to set a preferred weather forecast location on the BBC home page, for example, won’t be affected, as it’s useful for the user and isn’t used by a third party for further targeting. But other cookies that might personalise the user experience by targeting content or other products aren’t excluded.

Analytics providers, media organisations and the Government are still working to assess the impact of the legislation. It feels like the Government is prepared for the fact it will take a bit of time to understand how this legislation affects brand, adding that there certainly won’t be a crackdown immediately. But over the next year or so, the industry needs to show it’s making strides towards giving consumers the opportunity to refuse brands collecting data on them.

The message at the moment to brands is to work with their agencies to understand how they’re using cookies. The digital world is getting its house in order and there’s no reason why there should be a state of panic.

The research found that a single web page will drop anything from 1 to 25 persistent cookies. These may stay on an individual’s computer collecting information for up to 11 years if not deleted. A typical visit to a website saw 90 cookies being delivered.

At Foviance, we noted a huge proliferation of cookies used by brands and a large variance in the type of cookies used by each sector. The dependency of the news and media industry on generating revenue from advertising means there are large numbers of advertising cookies on these sites, that make them a prime target for the new EU legislation.

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Retailers, meanwhile, need to place a high emphasis on tracking consumer behaviour to enable site and content optimisation. The research found 43% of cookies used by these sites were for tracking purposes, which will also be impacted by the legislation.

Entertainment sites that use social media tools to engage consumers use a high number of social and functional cookies. They’ll be the least affected by the legislation. Finance and technology sites were both classed as medium on the Exposure Index. Finance sites had just fewer than 50% of tracking cookies and nearly a fifth of advertising cookies, while a third of technology website cookies were used for tracking.

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You may have noticed the digital world panicking a little in the last month. On May 25th a new piece of EU legislation is coming into force which will limit the way websites collect data about their visitors and will restrict some industries in how they monetise that information. In particular the legislation is focused around website cookies.

Cookies are small snippets of code that sit on your computer and identify you to a particular website or advertising network. Currently cookies are used in a huge variety of ways from remembering what you just put in your shopping basket so that the product is still there when you checkout, through to targeting specific adverts to you based on your previous browsing habits. The new legislation says that website owners should be getting explicit consent from visitors for their data to be collected in this way, used at a later date or even sold on. In effect visitors have to say they are happy for cookies to be dropped on to their computers by websites.

The legislation has its origin in considering how brands and advertisers should be allowed to use data they collect about us consumers as we browse the web. Should brands remember information about the products we browse, news items we read, how we prefer to personalise websites? Should they be able to use that data to sell us other products and services? Should they be able to sell that data to third parties? What is private and how much of our browsing history should remain private?

 Behavioural targeting

The EU legislation is not designed to ruin the user experience of surfers, nor to impact businesses with waffly laws. Simply the EU is trying to get the digital world to be on a similar footing to the rest of commerce, advertising and marketing. The direct marketing industry has been coping well with data privacy issues for many decades and the digital industry needs to be able to say in a similar way that it is responsive around individual’s privacy and reactive to their needs with regards to any data collected about them. The impact of the web on our lives has meant we are much more connected than before but consequently those connections mean we are leaving a trail of activity in a huge variety and number of places. It is this paper trail that the legislation is trying to get to grips with.

The average consumer is happy to have cookies that support their user experience, e.g. remembering that I live in Stoke Newington and providing me with local news and weather. This type of cookie isn’t going to be impacted by the legislation because it can be argued they are required to deliver a specifically requested service. But when cookies are used for behavioural targeting it can be a bit more off-putting for the average person and this is where the legislation will really affect our industry.

Recently I’ve been ‘stalked’ by Clarkes and John Lewis adverts wherever I have been on the internet. This is because when visiting their site some weeks ago they dropped a cookie on my computer and shared that data with a third party advertising network. The network now uses that information to recognise me and fires me adverts for the same products I looked at last month. If these type of cookies are not going to be used it could mean the death of some new digital industries that were expected to drive the development of online advertising. Could this be the end for whole industries such as re-targeting, behavioural targeting or multivariate testing?
 

How did the legislation develop?

During the last 12 months a number of industry insiders have been working with the government to help define how the legislation should be implemented. The government has stated that not all cookies will be subject to the legislation. If they were then it would mean that we would need to be served with a pop-up window asking for cookie consent nearly every time we clicked to a new web page.

This usability nightmare scenario was squashed by the government but with a rather broad statement that the legislation does not apply to cookies that are ‘strictly necessary’ to provide an explicitly requested service. This generated a lot of argument that have not yet been satisfactory resolved debating if automatic settings in your browser would be enough or if sites whose existence that depended solely on advertising could be exempt.

What next?

The upshot is a rather sensible wait-and-see policy from the UK government. They have been working with advertising bodies like the IAB, EASE, ASA to review current uses of cookies and support moves by industries such as behavioural targeting to educate consumers and move to an industry standard for behavioural ads. By 2012 expect to see a small icon in any behavioural ad to show that it has used cookie data to target you.

But with the legislation coming into effect in a month what should you do next? Large brands need to get an idea of how pervasive cookies are on their sites and also how third parties which may be advertising on their site are collecting data and subsequently using it. If your advertising or media agencies aren’t able to give a confident response on how they are proposing to react to the legislation then it is probably time to look for another agency.

Since the autumn of 2010 at Foviance we have been researching what impact this legislation is going to have on brands and also how consumer attitudes to data privacy are likely to develop in the next few years. With the legislation in mind we developed a tool that grabs cookies from a website visit, analysing the type of data being collected by the cookie and rating this data in relation to how likely the legislation will impact it.

It has been fascinating and eye-opening to see the huge number of cookies that a typical website uses and the wide array of uses of these cookies. Using this approach we’ve been able to help our clients understand how the new law is likely to impact them across different types of cookies they use such as advertising, functionality and social media. I think it is fair to say that the impact of the legislation on large brands is going to be huge.

What about consumers? Most people think the internet is free and don’t understand that website owners need to generate revenue to support the delivery of content. Consumers also need to be educated in how data is collected, otherwise distrust will set in and people will never be happy to share their data. If that happens then slowly the amount of data and quality of that data that is collected through cookie technology will decrease dramatically. So, time for the digital industry to proactively engage and lead in the privacy debate.

For more about Foviance’s Data Privacy Audit

This article was originally published at My.Customer.com

“Why do you have a website?” I love that question; it tends to focus the mind. Any time you develop measurement frameworks for digital channels, you must be focused. Digital platforms, like websites, often have multiple stakeholders with different goals. There’s always a danger that overall objectives may not be clear. And if the objectives are not clear, then success is next to impossible to measure.

It’s challenging to develop good Key Performance Indicators (KPIs). It’s easy enough to come up with the right metrics, but clarifying robust objectives is more difficult. It’s also easier for e-commerce sites to develop KPIs with strong objectives.

But most sites don’t sell stuff, so why do they exist? They exist for good reasons and those good reasons need to be expressed in clear and definitive terms. That’s the hard part. So, make the objectives clear and measurable, describe what “good looks like,” and select appropriate metrics that measure outputs and outcomes. So once that is done, is that they end of the story? Not really, it’s just the beginning.

Once overall site goals are in place and appropriate KPIs have been defined, the next question is: which sections of the site are working well and which ones aren’t? If we don’t know the answer to this, then how can we focus our efforts properly on site optimisation? This is why we need not just site goals but page goals as well. A page goal defines what that page is trying to achieve. It answers the question, “Why does this page exist?”

Stating clearly why a page exists and its objectives are is a very useful exercise, particularly when you are designing a page. Page goals help you focus what the page is trying to achieve and feed directly into the development of the information architecture of the page – for example, at wireframe stage. Page goals are particularly useful in circumstances when there are multiple stakeholders involved all trying to get a piece of the action on a page; without page goals you can end up with pages that don’t work particularly well for the business or website visitor.

In the same way as for defining overall site goals, page goals should be as clear and precise as possible. Something like “To help users achieve their goals” doesn’t really cut it. Which users? Which goals? In what way? It has to be clearly defined. Once it’s been clearly defined then a measurement framework can be developed for each page that describes how the page’s success can be assessed. Once the measurement framework has been developed, then measurement systems can be configured to include the right kind of metrics in the right kind of way. With page level measurement frameworks,  it also important to consider the context of the page itself. How do people get to the page? How far is it into a customer journey?

Consider the classic product page in an e-commerce site. A product page has a tough job. The primary purpose of a product page is generally to persuade a website visitor to add a product to the basket. To do this it needs to provide all the information required in a clear and concise way. To measure the success of the product, you could look at metrics such as the add-to-basket rate. You could also measure the effectiveness of different components or tools on the page in terms of how they influence the add-to-basket rate. But often a product page on an e-commerce site is also the landing page. Often it’s the first page that a visitor sees on a site. For them it’s also the home page. So, the product page also has the goal of building trust and consideration for new visitors. It doesn’t just have to persuade the potential customer to buy the product; it has to persuade the customer to buy it from you. By identifying these additional page goals, you also identify the need to measure success using additional metrics, such as the bounce rate for new visitors.

Not every single page on a site necessarily has to have page goals, but certainly they should be in place for each different type of page or section on a site. Page goals are useful to help define what good looks like at the micro level and to ensure that your measurement frameworks are measuring the right things in the right way.

This article was originally published on ClickZ

In many cases organisations are still struggling to get the return on investment in their digital analytics that they were originally hoping for or could reasonably expect. Ten years on from when web analytics started to go mainstream, why is that still the case? If we look at the possible reasons, they tend to lie in the “triumvirate” of  technology, people and processes.

A lot of organisations have access to web analytics technology and have invested in it heavily over the years. The introduction of free services sparked by Google Analytics over 5 years ago means that it is cheap to acquire web analytics technology. For organisations with more sophisticated requirements such as the ability to integrate web data with other data sources and system, the enterprise market satisfies those needs. The technologies have developed significantly over the past few years and provide richer analytics, particularly in the area of behavioural segmentation, than they did a few years ago. There are still areas that are not addressed well generally by web analytics technologies, notably the attribution of acquisition channels. And while it’s great that the technology provides are adding additional functionality particularly in the social media arena, acquisition attribution is an area that it would be great to see some development in.

It wasn’t that long ago that it was generally recognised that organisations were underinvesting in getting enough of the right type of people into their organisations. Avinash Kaushik’s famous 10/90 rule he posted on his blog made the point admirably. We have seen organisations invest more in people more recently and significant web analytics teams exist in many large advertisers or digital property owners. Investing in people remains a problem naturally for smaller organisations with smaller budgets and resources, but if at least it becomes part of someone’s job, then it signals a degree of commitment.

To some extent, experience and qualifications remains a problem on the people side of things. Web analytics is still a relatively young marketing discipline and even the “veterans” in the industry have less than 15 years or so experience in the field. Again, this is evolving as organisations like the Web Analytics Association continue to develop education and certification programs. This will help to define “what good looks like” when it comes to web analysts and provide a means of reference for organisations to assess the quality of potential staff and suppliers alike.

So whilst there are still opportunities for improvement in the areas of technology and people, I think that process remains the Achilles heel of web analytics in most organisations. Process is really about how the technology and people are applied within the organisation to make a difference about the way the organisation does business. The problem often begins with a lack of process around the setting of goals and objectives so that correct key performance indicators can be set. This not an analytical process, it’s a business process and therefore is one that the business as a whole needs to buy into. This process operates at all levels from setting objectives for the channel as a whole, through to setting objectives for product development or down to individual campaigns. It’s the process that sets the analytical agenda within the organisation.

Processes then need to exist to maintain the quality of the data that is being collected within the organisation. A lot of effort can be spent getting a new technology in or applying an existing technology to a new website but it’s vital to have processes in place to maintain the integrity of the data. Digital channels are never static so continual effort is required to ensure that the data being captured reflects the latest developments. This means plugging analytical and measurement processes into the heart of the product development or campaign development processes and seeing data collection as being a core component of those processes rather than as an aftert thought.

The other important processes required are the ones that embed the data and insight into the decision making process. Optimisation is all about “test, learn and adjust” and the “learn” bit needs to be integral to that process. The challenge here is how to ensure that the analysts and their data are brought into the loop, and the challenge for analysts is to ensure that they can add value to the discussion. Part of the issue here might be about where analytical functions sit within the business and how they interact with their peers and colleagues. There are no easy answers to these organisational questions, but all the investments in technology and people will be undermined without consideration being given the way that the data and insights are capitalised upon.

In many cases, the hard investments in technology and people have been made, but the returns will be realised when the process issues are addressed as well.

This article was originally published on ClickZ

People who run non-transactional websites have a tough job evaluating the success or return on investment. In contrast, if you sell stuff online or have a clearly defined transactional environment, then it’s relatively easy to assess whether things are working or not. You can count the number of transactions or you can use metrics like the conversion ratio to work out how effective the site is in turning opportunity into value. But what about all the cases, like information sites or support sites, where there aren’t any clearly defined transactions? What happens then?

Read more about: Measuring outcomes and not just outputs