• New improved interface
• Custom reporting
• Event goal type
• Tag cloud visualisations for keywords
• Custom dashboards

New Improved Interface

A number of enhancements have been made to both the administration and reporting interfaces, in an effort to make them easier to use and navigate. The menu navigation has been revised and reports are now grouped together in a more intuitive fashion. A new expandable menu means that you no longer have to wait for the screen to load when switching between reports – a big plus! 

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Custom Reporting

The Custom Reporting interface has seen further improvements too. An update to the reporting template makes it easier for users to quickly add dimensions and metrics to their reports. An autocomplete list is now used instead of the drag and drop interface. Filters are now standard within the Custom Reporting interface allowing you to better segment data. 

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Unfortunately you still cannot specify which column the report is sorted by, hopefully this feature will be included in a future release. 

Event Goal Type available when setting up Goals

This is one enhancement which I know will please a lot of my clients; the ability to finally define your goals using events. Previously, we’ve ended up using virtual page views instead of events when tagging up on-site activities just because of the requirement for setting up a goal. Now you can select ‘Event’ as the goal type and choose which events result in a goal conversion, based on a number of conditions.Non-ecommerce site owners should find this feature of particular benefit when assigning goal values to these events and making use of the $Index. 

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 However, as with other non “URL Destination” goal types (e.g. time on site, Page/Visit) you can’t associate a funnel visualisation with the new event goals. In this instance you will still need to use virtual page views when wanting to look at dropout routes for path to goal. 

Tag Cloud Visualisations for Keywords 

The introduction of the “Term Cloud” view, will display keyword data as a tag cloud visualisation which will be a great little time saver. Whilst not as visually appealing as other tools commonly used, such as Wordle, the ability to quickly see at a glance which keywords are performing within GA rather than having to export the data into another tool will be welcomed by many analysts. 

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Custom Dashboards

The dashboard functionality has been completely overhauled in the new release. It now allows users greater flexibility and more control over the presentation of data. The use of a widget-based editor provides users with further customisation and flexibility. Users can pick between four visualisations to best represent the data:

• Metric,
• Pie chart
• Timeline
• Tables 

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The ability to create multiple dashboards ensures they are tailored for different audiences and aspects of the site. 

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The new version is currently in closed beta and will be rolled out in phases to current users in the near future. 

Anyone who would like to be considered for testing the new version can sign-up here for the beta testing program

I don’t know whether the number is right or not but a while back I heard that sophisticated marketing companies such as the world’s leading brands spent about 10% of their marketing budget on research and measurement. Irrespective whether the number is accurate or not, it’s a good benchmark I think – 10% feels about right. These leading companies have been marketing brands for over a 100 years and so over that time they have come to understand the importance and relevance to their business in investing in understanding the effectiveness of their activities.

I wonder what the equivalent proportion is for leading online businesses? How much do online businesses invest in measuring and tracking the effectiveness of their online activities? I don’t know the answer to that question but my suspicion is that the answer is generally “too little, too late”. We all know of companies that have a reputation for using analytics as part of their strategic armoury and have invested heavily in analytical technologies and also have built up formidable analytic teams. These are the companies that people travel to see and hear from at events like Emetrics and Exchange. However these companies are the exception rather than the norm.

What I write in these articles is often triggered by recent events in my consulting activities with clients. Customers and potential customers are a rich source of content! I went to visit one company last week where they had recently appointed a user experience manager and given him responsibility for web analytics and site optimisation. The client had been busy over the past six months implementing a solid and robust web measurement tracking programme. This had involved completely re-implementing their web analytics tool, hiring in a web analyst, revisiting all the business requirements and producing new reports and dashboards. He had also hired someone to specifically focus on site optimisation and to run their testing and experimentation programme. They had been busy laying the foundations and investments had been made in people, processes and technology. I could see how quickly they would begin to reap the rewards.

At the other end of scale I’ve also been working with a client who is developing a brand new site. New sites don’t come cheaply but all the way through the senior stakeholders in the business have been reluctant to invest in the appropriate measurement and analytics. The new site is close to launch and we’re now trying to shoe horn in the analytics requirements into the tail end of the development process. They use one of the free tools which can cope with most of their needs but not all of them and despite the significant investment in the new site itself, getting a relatively modest budget released to develop the data collection specification and the reporting configuration has been difficult. For me these two experiences highlight the difference between companies that “get it” and those that don’t.

For those companies that struggle to recognise the value of investing in decent measurement and analytics, I’m reminded of one of my favourite quote from A C Nielsen. Arthur Nielsen used to say that “The price of light is less than the cost of darkness”. The point is elegantly made – it’s not a question of whether you can afford to invest in measurement, it’s a question of whether you can afford not to. For me the point of measurement and analytics is to increase the effectiveness and efficiency of decision making and to reduce the risk of failure. It also leads to better accountability, which is possibly why sometimes it’s not welcomed with open arms!

Determining or justifying the return on investment in analytics can be hard. In some cases, like multi-variate testing, the ROI can be very explicit and indeed that’s how the technologies are often sold. However, working out the ROI on an analytics team and general analytics technologies can be harder, particularly in non-transactional environments. But there is always “a cost of darkness” and the trick is to try and work out what that cost might be. For transactional environments it might be not knowing how to improve the conversion ratio, for media environments it might be around not understanding how to monetise the traffic more effectively and for service environments it might be about not understanding which content is helping to deflect calls from the contact centre.

Although hard to prove I believe that even small investments in measurement and analytics can return a significant ROI particularly in the early days of adoption. Perhaps “The price of light is less than the cost of darkness” should be in the footer for every business case for investment funds for measurement and analytics.

Figures corroborate this: predictions see app market turnover rocketing to a whopping $17.5 billion in 2012, against $6 billion this year. The number of app downloads should also reach new highs with an estimated $50 billion in 2012 against $7 billion this year. But interestingly, it seems that apps haven’t reached their full potential yet. What the stats also tell us is that gaming and social networking dominate the app market whereas retail apps trail at the rear of the wagon. However, despite mobile retail apps trailing slightly right now, they have a huge power to unleash.

It’s small wonder that retail apps are lagging behind. The whole app concept is fairly recent and most of us are not yet fully ready to embrace mobile shopping: security and payments on handheld devices remain a concern, we’re not yet so keen on purchasing on the go, and we want to feel we’re making informed mature decisions. In the end, why would we use a small device when we’ve got laptops and computers available most of the day? This trend, though, is about to change.

A recent study conducted by miBuys indicated that 85 percent of surveyed women used the mobile internet daily, and 95 percent of them browsed the mobile web at home when they could potentially access computers. Also, 67 percent were interested in receiving mobile vouchers or coupons, whilst 57 percent had already clicked on mobile advertising. Another study from Deloitte revealed that one-in-five consumers plan to mobile shop in the future, 25 percent of whom intend to make a purchase through their phone. The explosion of mobile commerce is therefore scheduled – now how can big e-commerce firms ensure they make the most of mobile apps?

The power of retail apps is two fold: not only do they boost online sales; they also leverage offline sales. In the former case, the added value of apps is clearer. Online revenue is not only limited to the download cost of the app but is also generated by in-app content. Apps can indeed be used as a portal to access product listings or ad hoc services, which can ultimately lead to online transactions. The Ocado app is an interesting success story. Available on multiple platforms including iPhone and Android, the free-to-download app yielded a turnover of more than £15 million in Q1 2010 (five percent of Ocado’s total sales), by enabling users to go food shopping on their phones. Another example is the Sky Sports Live Football app. The app gives football results in real time as games are being played, for free. But if they register within the app for an extra £4 a month service, users can get video clips of the goals on their phone.

The offline value of mobile apps is less obvious yet it is still there. Apps can boost offline sales by acting as a promotional medium. One way to exploit this opportunity is to create a catalogue app, just like Ikea recently did. The app allows users to browse the latest Ikea store catalogue. One of its main strengths is that the catalogue is offline and can therefore be accessed regardless of network signal. Another option is to create an app that sends periodical push alerts to users (e.g. about new clothes collections, promotional vouchers and so on). Desktop websites would then finish the job started by the apps and convert visitors into buyers. US venture company Shopkick is taking mobile retail to a new level by merging mobile and offline shopping. Its app, to be released at some point this summer, will work across a certain number of stores (including Macy’s and Best Buy for a start) and will provide augmented product information. While strolling down the aisles of brick-and-mortar stores, users will be able to use the cameras on their phones to scan items in order to get additional information (such as reviews).

So the power of retail apps is still to be realised. If well thought and well designed, this channel can become another consistent stream of online revenue. If you’re considering designing an app for your e-business, here are a few tips to ensure you make the most of it:

• Know you audience – What type of phones are your customers using? If they use smartphones, think ‘apps’. If they use more primitive phones, think ‘mobile friendly website’
• Track your traffic – Knowing the share of your visitors that access your site via their phones will help you plan your online strategy
• Establish you goal(s) – Do you want to use your app as a sales channel, showcase window or interactive in-store guide?
• Engage with your customers – Apps are different from the traditional web, demanding new marketing strategies
• Make payments easy – Should you decide to implement a checkout process in your app, make sure it is quick, user-friendly and secure. Think Google Checkout, PayPal or similar
• Most importantly, make sure your app is usable – Don’t skip user testing while arguing your app won’t generate enough revenue to justify user-centred research.

This post was written by Xavier Klingenfus

This article was written as part of the Foviance July/August Newsletter

On the contrary,  it is the belief of both my team and I that we must try, that sees Foviance opening for business in China this quarter, with a new office in Shanghai.

Our plan is a fairly simple one. Foviance is pretty good at international work and as a result we do a lot of it, mostly for western clients that want to test things in Asia. As a result we have gained quite a bit of knowledge and a fair few relationships in the Chinese market. If we could also generate some business in the local market for Chinese companies looking to market to the west, we should have a nice little business plan. Sounds simple doesn’t it? I thought so and yet the planning has taken nearly 18 months and we are only just ready now.

Initially we are focusing our efforts on core user experience services in web and mobile, which is where we believe the largest initial opportunity is. Usability is a growing discipline in China with a large and expanding UPA membership and an ever-increasing acceptance of the benefits. If everything I have read about the Chinese market is true, I believe that we will soon be providing our measurement strategy, customer insight and strategic customer experience capabilities. Initially though, we are staying focused to ensure we keep a handle on the quality of delivery and the market differences.

We know there will be plenty to learn. We have experienced the differences first hand testing various web and mobile services in China for western clients. There are differences in the way people use devices and the web of course but most startling are the cultural variations. It is little wonder that the field of usability is dominated by behavioural psychologists given the need to match interaction design with user behaviour.

International culture differences will add a completely new dimension to the work we conduct developing personas to help organisations design with their audience in mind. Some years ago we carried out work for a gaming company that was looking to launch a Mandarin website. One of the most surprising findings was that there was no translation for ‘lucky dip’. The term simply doesn’t exist and is a perfect illustration of the challenges western organisations face going to China. The reverse is true of course for Chinese businesses wishing to market their services in the west.

In the Star Wars film ‘The Empire Strike Back’, the character Yoda tells Luke Skywalker after he has tried and failed to move an impossibly heavy object (his space ship), “Try not. Do, or do not. There is no try”. I think his point was that if you approach something in a half-hearted way you stand a fairly good chance of failing. At Foviance we trust that our planning and steady execution will enable us to be successful in China but we are not naïve. It will be hard and we will have some success and some failure, but we will do it, because we believe it is important to the future of Foviance.

This article was written as part of our February newsletter

In my last column I reflected on 10 years in digital analytics and how far the industry had developed in decade in some ways and how there was still room to grow in others. I commented that I thought that one of the issues was that the online marketing world had been “data rich and analytically poor” and this week I want to explore some of the areas where I think there is work to be done to enhance the quality of insight that digital marketers get from their investments in data capture and reporting technologies.

For example, considering that web analytics and campaign data is often used to make resource and budget allocation decisions around online marketing spend, the continued use of the “last click attribution model” seems to me to be bizarre. I recognise that many organisations are seemingly locked into this approach through the measurement and reporting technologies that they use but it seems to me that this is an area where little “analytical” progress has been made over the years. Many businesses and their agencies know that this model is a sub-optimal solution to managing marketing spend but have limited options given the systems available to them. Some work has been done by some agencies to improve the way that campaigns are measured and optimised but it’s seemingly required large investments to get the position where the influence and impact of different channels can be tracked and measured properly. What I would like to see is the web analytics providers providing greater analytical horsepower in the area of campaign analysis by providing more flexibility in defining attribution models and windows and also the ability to look at the impact on multiple campaigns on conversion.

Another area where it would be great to see some more progress is in the development and application of econometric and predictive techniques to understand online marketing effectiveness and particularly the interaction between online and offline activity. These sort of techniques have been used for years in brand and consumer marketing to assess the impact of TV campaigns and the like and there is probably the role for these types of analytical approaches to supplement or enhance the direct measurement techniques that are most often used in the digital space. Again, some work is being done in this area by some businesses or their agencies but i feel we see to see more debate about the use of these techniques in the online space and the type of problems they can help to solve.

This leads me on to my final point and that is I would hope to see the development of more “science” in online marketing. For me marketing as blend of art and science, a combination of left-brained and right brained approaches. That’s not to say that there isn’t any science in online marketing analytics. Multi-variate testing is a good example where analytical and statistical techniques are used to predict the best probable outcome from a series of experiments. There are other examples as well in behavioural targeting. However I think that there are many other areas where there are the opportunities for a more scientific and statistical approach to understanding online behaviour in the same way that marketing scientists developed theories and models to explain such things as TV viewing behaviour, shopping behaviour and purchasing behaviour 20 to 30 years ago. One of the earliest marketing texts sitting on my bookshelf is called “Marketing Decision Making: A Model-Building Approach” and it was published in 1983! For this to happen I guess there will have to be a greater interaction between academia and commerce. I’m sure there is some really interesting research in this area being done in instructions around the world but I’m not sure about how much of it is reaching the commercial world in a consumable format. One good initiative in this area is that the Web Analytics Association has secured access to 5 leading marketing journals for its members to provide an opportunity for industry analysts to connect with the work being done by marketing academics and researchers. It’s one step along what I hope will be the road to making web analytics more analytical.

The core task of the testing required the participants to simulate a loan application process. They were asked to apply for a £25k loan in order to finance the purchase of a car. The feedback from the task revealed that the current process was found text-heavy, long-winded and of moderate length, whereas the new process was deemed more user-friendly, shorter and quicker. But surprisingly, more than half of the participants commented that they preferred the current process. The principal reason highlighted, was that going for a £25k loan was a big financial commitment that should slowly mature in the users’ mind, as they go along the application process. Participants did not expect/want to be able to take out a loan online as easily as they would pay bills or transfer money.

This shows that, even if some fundamental usability principles should always be respected, the best way to achieve a goal is not always the easiest.

This post was originally posted by Xavier Klingenfus

It has been 14 years since I first surfed the web using a PC, so it is no surprise that it is increasingly rare for us to observe novice users of the Internet (yes, while they do exist, they are becoming fewer in number, and are less likely to volunteer to take part in research involving Internet use than more experienced Internet users). However, the same cannot be said for mobile Internet users.

Figures that ComScore released this summer highlight the increase in UK mobile Internet use: there has been a 26% increase in mobile Internet subscribers over the past year (they now make up one fifth of all UK mobile subscribers). This suggests that there are a lot of people who have been accessing mobile Internet for less than a year – and this trend is likely to continue with the announcement this week of both Orange and Vodafone both gaining the rights to sell the iPhone.

So it was with great interest that I recently observed a series of iPhone one-on-one evaluation sessions. It was captivating to observe the range of skill (or lack thereof) when surfing the Internet on an iPhone, especially for new mobile Internet browsers and new iPhone users. Just like in the early days of the Internet for PCs, navigation offered on websites viewed via mobile is not standardised. Nor are the mobile browsers that people are using to access the content. So this makes simple tasks such as moving back, moving forward and searching tricky for some.

In addition to loads of novice users, developers are faced with the difficult task of building mobile sites for multiple browsers, phone capabilities and screen widths. Clearly, the mobile Internet brings its own unique challenges that can only be solved with rigorous user research. But I am glad the UX community is rising to the challenge – and products like the App Sketchbook (if a bit gimmicky) will assist us usability professionals, designers and developers alike.

With 85,000 apps available from the Apple App Store, ultimately it will be the user-friendly and useful apps that become the most popular, and from the wisdom of the crowd, I hope we see some standardisation emerge – for the iPhone anyway!

Multivariate testing, or MVT, is an experimentation process by which a series of possible design variables are tested at once to see what effect, if any, they have on website performance. It’s a complex form of split, or A/B testing, employing algorithm-based software and constant monitoring of web analytics data. Small changes are made to single variables (such as the position of a menu, the colour of a background) and the impact of each change is measured. From series of changes, optimum design configurations can be narrowed down as a result of measurable evidence. With MVT it is also possible to experiment with structural, business rule and database driven elements, as well as cosmetic changes. We can even employ advanced rule-based targeting capabilities, including targeting by geographic location, traffic source (such as search engine versus email campaigns), cookies, and more.

Ultimately of course, MVT is all about converting ‘lookers’ into ‘bookers’ (or buyers, players, subscribers… dependent on the business being conducted).  We want to help our clients make their sites work as hard as possible, increasing transactions by fine-tuning conversion strategy. We can do this by ensuring user experience has both a strategic and data-driven focus, and by conducting an ongoing measurement process that ensures sites are truly customer driven.

One obvious way of doing this is to use experiments that identify which parts of a given site detract from bookings, and which contribute to higher conversion rates. Foviance typically employs three concepts in its multivariate testing: variables, values and combinations. Variables are the actual elements that are tested, eg. buttons or banners. Values refer to the different permutations of those variables, such as colours, or shapes. Combinations refer to a set of variables together, and by using multivariate testing we can discover what particular combination of variables lead to the greatest conversion rates. Simple!

One of our roles as a customer experience consultancy is to add real value to raw methodologies such as MVT. We wrap the technology in many years of knowledge of users, interfaces and best practice to ensure that we deliver better results, more cost-effectively. Because we have in-depth experience to fall back on, we are able to dramatically cut the time and effort invested by our clients, reduce test variables, tie in MVT with real business objectives and actual user behaviour, and apply rule-based targeting, personas and scenarios. Also, because Foviance is technology agnostic, we can cherry-pick technologies that best suit our clients real-world needs, and have often succeeded in unlocking ROIs of 10:1 or more.

Following thorough MVT work, a business can be sure that it is targeting its online marketing budget in line with measurable data, and not simply as a result of opinions or gut feelings. Creative types within organisations may sometimes worry that testing is stifling, but are much happier if they are presented with clear data that helps guide them in their work and saves them duplication of effort. Of course that is also how higher management views such decisions too. MVT testing helps our clients develop seamless online journeys for their customers, and increased conversion is the ultimate measure of their customers’ satisfaction – not with the business’s products and services, but with the digital journey that finally convinced them to make those all-important purchasing decisions.

Back to September newsletter

This is what happens in the absence of good data to guide decision making. It becomes subjective and vulnerable to interests, politics and personal preference. Good optimisation strategies are built on good data, coupled with an ability to drive through change. In the ‘red versus blue’ debate, what better way to find out than to try both of them and see which one works best? That’s the basis of a testing and experimentation programme. A/B testing and its more sophisticated cousin, multivariate testing or MVT, have been around for years as techniques in direct marketing and other analytical disciplines. These techniques allow you to test different versions of a page or different combinations of different elements on a page to see which one works best. Although the analytical techniques have been around for years, it is only relatively recently that they have begun to get adopted and gain traction in online marketing.

A/B testing is conceptually very simple but can be difficult to execute. To see whether the blue button would be better than the existing red button, two different versions of the page would be created, one with each different button. As visitors arrive on the website one set of visitors would be shown version A, and the remainder would be shown version B. The effectiveness of each page is measured according to whatever success criteria are the most relevant. Multivariate testing uses a more sophisticated set of algorithms to allow you to test multiple versions of different elements of a page at the same time.

Whichever testing regime is the right one, the challenges historically have been in implementation. It can be technically challenging to manage the process of setting up different versions of pages, splitting the traffic between them, setting up the measurement and then analysing the results. This heavy lifting has now largely been addressed by the availability of specialist testing and experimentation platforms such as Omniture’s Test & Target, Autonomy’s Optimost or Google’s Website Optimiser. Whilst the implementation of these services is not trivial, they manage the whole testing and experimentation process from deployment through to results.

The challenge for organisations then, still remains “What to test” and “How to test”. Analytics, survey data and usability evaluations can all help to identify the priorities for a testing programme. Start at the greatest pain points but also sort out the operational processes around the initial deployment on pages that are not too complex or mission critical. Marketing landing pages are often a good place to start. The question then becomes how should the page be tested? The challenge here is to ensure that you come up with a good test design. In our ‘red versus blue’ debate, are these the best options to test? What about green or orange? You could test those as well but in reality the number of variants that can be tested is limited. It’s important to ensure that you’re testing the right things in the right way. For me, this is where user experience expertise adds value to an analytical testing programme. Customer experience experts can identify which variants are likely to be the most effective and ensure that the test is as efficient and as effective as possible and the analytics experts can run the experiments and do the analysis.

Testing is a powerful tool in the site optimisation toolkit but it’s important to test the right things in the right way.

It is obvious to draw parallels between this theory and how much effort our own industry puts into soft-launching and stress-testing online systems before unleashing them live on the wider community. Is it possible that similar attention to modelling by our investment banks and a reduced emphasis on getting to market as quickly as possible to reap the highest theoretical returns, might have avoided much of the mess we are now in?

In our experience, there are no shortcuts that can replace the benefits of thorough modelling and testing. We are experienced, working with financial service organizations and employ a range of financial modelling systems when creating products for that sector, regardless of the type and scale of banking application. We test, and retest with customers, conduct user surveys, and run real-world modelling. We listened to the top decision-makers from all sectors of global society at the annual Economic Forum in Davos back in January when they warned of just such an oversight, and we learned. Why didn’t the finance institutions and regulators do the same? Is it possible that they got ahead of themselves, bending over to product guys in order to reach a perceived sweet market as rapidly as possible, rather than following a risk-averse approach?

We work with high-profile financial clients like Barclays to ensure their online customers are provided with easy-to-use, highly secure, no risk products. Of course we are somewhat fortunate in that internet service modelling is logical and predictive – thanks to artificial server loading techniques we can run scenarios that see services oversubscribed by 100 percent and so on. But we also run pilot schemes, test groups, live tests, plus continuous testing and modelling post launch. We find real users to test products, and we ensure they are able to deposit and withdraw real funds long before products reach a wider market.

It appears that the investment banks we all rely upon simply skipped all these logical steps, going straight to market with poorly thought through products. Take the US public credit situation – if loans to citizens had been thoroughly modelled, it is probable that the disastrous toxic loan situation could have been avoided altogether. It’s important to ask the difficult questions – what if 20 percent of citizens can’t pay their loans back? What happens then?

Perhaps it is true that if organisations take the time to research, and model critical products and services carefully and thoroughly, they might miss out on early financial opportunities from time to time. But surely these steps should be considered vital, if not mandatory, to ensuring a solid, risk adverse financial landscape?