In the video interview, Helen introduces the key new features of Google Analytics and the services Foviance provide in helping you better understand conversion and user journeys on your website. We are well into the New Year and it’s a great time to carry out an Implementation Healthcheck, Helen describes some of the features and processes that will validate your customer data ensuring it is accurate and correct. Finally, the overview of our bespoke Analytics Training courses explains what benefits and learning’s your business will be able to take away and carry out on a daily basis.

www.youtube.com/watch?v=WWdlHP9SHfI

Mike holds a PhD in Systems engineering and has also completed post-doctoral work in various places using a wide range of data analysis methods – time-series, computer-based video analysis and other complex mathematical modelling – to study neural changes in fruit flies or how T-cells’ response to an antigen expresses itself genetically over time. He is now going to apply similar methods to the analysis of online behaviour – the links people click on.

In fact Mike is particularly interested in predictive analysis  (which link a user will click on next) and characterising human behaviour against that of robots. It turns out that before you analyse all the clicks on bit.ly URLs to make sense out of them, you need to be sure they were “genuine interest” clicks. It could after all have been some random bot scraping around, or a specific attempt at boosting clicks for affiliate purposes. There are in fact companies whose mission it is to sort out this human vs robot issue – pay per click is big business after all, and no one wants to pay for clicks made by code.

What I find interesting, though, is that Bitly’s service allows the company to collect a wealth of information on the content being shared across the web, and therefore gathers great insights from the social web: millions of people use the service to shorten links they share on Twitter for instance. The company has a team of computer scientists engaged in quasi-academic mathematical research to create models of user behaviour that predict what they will be interested in and therefore what they are likely to click on. This could be used for example to help users discover new content by making more intelligent suggestions. The end result would be an enhanced user experience when consuming content online. There is also, of course, an underlying commercial logic: predictive analytics wizardry is being used by online businesses to better target different segments of users, to try and optimise response rates on email campaigns, among other things. This is one of the many areas Foviance’s analytics team combines its expertise with that of our user experience team to bring added value to our clients.

Serendipity was clearly at work: what started as a quick informal chat turned into an hour long conversation during which I learnt that fruit flies carry out a sophisticated courtship song and dance (who knew?) and we discussed the challenges of data visualisation, a topic I am particularly interested in.

Mike – thanks for the chat!

A good analyst has the capacity to analyse data and generate insight. Let’s have a look at those words in a bit more detail. An analysis represents a “detailed examination of the elements or structure of something” and insight is defined as “the capacity to gain an accurate and deep understanding of someone or something.” On that basis, the analyst needs to be able to look at data in detail and understand it. But it depends also on what you mean by “understand.” In addition to understanding the data, an analyst must also understand and communicate what it means for the organisation. So here are five things to look for in an analyst:

Data Dexterity

A good analyst must be able to handle data – any data. While analysts may have a functional speciality, such as a web analyst or a customer insight, they have to be comfortable in handling any data sources they encounter. In the data world, two and two really does equal five. That’s because the value of data from one source increases when it is integrated with other data sources. Web analytics data is great, but it becomes even more valuable when it’s analysed alongside voice-of-the-customer data, customer experience data, and other customer data.

Pattern Recognition

For me, analysis is a blend of the creative and the deterministic. A good analyst can look at a set of data and begin to see what the data is telling her. Data tells stories and the analyst is there to interpret the data and make sense out of what the data is saying. It’s all about extracting signals from the noise.

Attention to Detail

On the other hand though, an analyst must have strong attention to detail. Data can be very nuanced at times; it might look like it’s saying one thing when in fact it’s saying something else. Or the data may be wrong. A good analyst must be able to spot problems with data that just doesn’t look right.

Commercial Awareness

An analyst must be aware of the ramifications of the what the data is saying. She needs to add value to the analysis by not only explaining, “This is what’s happening and why” but by also elaborating on “This is what I think the impact is” and “This is what needs to be done about it.” The latter analysis tends to come with experience, but any analyst at any level needs to interpret outcomes and not just outputs of their work.

Positive Presence

All the above counts for nothing if the analyst cannot get her message across within the business. She must articulate and communicate what the business needs to know. So good analysts need to have good verbal and written communication skills, possess the ability to construct an argument based on evidence, and tell stories.

A lot of these characteristics can be learned or developed over time. If you are looking to hire talent, be sure she is comfortable with data and has the ability to understand how the data relates to the business. When we look to hire an analyst, we ask candidates to create a presentation from a set of data. We want to know not only that they analyse the data but whether they can make sense of it and then articulate and present that message in a clear and convincing way.

This article was originally published on ClickZ

“All generalisations are false, including this one.”

Here he was talking about segmentation. Generalised metrics such as overall conversion ratios, average time on site, and so on are largely useless. They only make sense when the data is segmented and the underlying patterns and differences can be understood. The same is for survey data as well. Metrics such as NPS can vary wildly among different customer segments and so these segments need to be identified and looked at separately.

“Few things are harder to put up with than the annoyance of a good example.”

A great insight into the power of evidence-based decision making. Solid facts, presented well, are hard to ignore. Twain was probably also thinking about the need to have an approach to testing and experimentation when he said this. There’s no better way to silence the HIPPO (highest paid person’s opinion) than to have concrete evidence from testing about why one approach is better than the other.

“It’s no wonder that truth is stranger than fiction. Fiction has to make sense.”

Sometimes the data doesn’t make sense and the skilled analyst needs to understand why. Is the data telling her something new? Is this real insight or is there a problem with the data? Often, if it doesn’t seem right, then it probably isn’t right, but occasionally there may be something that the business has missed, the competition has missed, and there is real opportunity to be exploited. Just make sure you’ve checked the data thoroughly before you tell the CEO!

Twain also had some great advice for budding analysts:

“The more you explain it, the more I don’t understand it.”

This is a great piece of advice. Basically, keep it simple, but don’t be simplistic. A good analyst will be able to present quite complex notions in ways that are easy for people to understand. This is the art of storytelling. Developing compelling narratives that engage the audience is quite a skill. There’s an important role for data visualisation here as well. It’s harder to create simple charts and graphics than to scatter lines and bars all over a PowerPoint slide. That’s why an analyst also has to be an artist.

“I was gratified to be able to answer promptly, and I did. I said I didn’t know.”

I think it’s OK to say that you don’t know; it’s better than bluffing…

“It is better to keep your mouth closed and let people think you are a fool than to open it and remove all doubt.”

…and being found out later, as long as you say that you’ll find out the answer and come back to them. And then make sure you do.

And finally:

“The most interesting information comes from children, for they tell all they know and then stop.”

Don’t be afraid of silence, particularly if you’re presenting to your audience. Deliver your insight and wait for a response. Maybe ask them a question, and then wait for a response. “Is that something you recognise?” and “Does that fit in with what you know?” are all ways of seeing whether what you’re saying is hitting the mark or missing the mark. It’s better to find out in the course of a conversation that what you’re saying is not falling on fertile ground rather than just to be ignored later. Maybe you need to get more evidence or maybe you need to explain the point in a different way.

So that’s why Mark Twain was an analytics guru!

This article was originally published on Clickz

Optimisation using testing and experimentation technologies (such as Adobe Test and Target, Webtrends Optimize, or Google Website Optimizer) is mainstream for a lot of organisations. Companies such as Dell have built teams and processes to drive testing and experimentation through the business. Those companies have learned – and others are painfully discovering – that successful testing and experimentation is not only about implementing one of the many available technologies. It’s also about the need to harness people, resources, and processes around technology.

It’s similar to web analytics a few years ago. Back then, organisations implemented a system thinking that it would solve their measurement problems but then realised they needed analysts. Likewise, organisations must build structures and processes around testing and experimentation technologies, otherwise the business will not extract the potential from the system.

Testing and experimentation involves a lot of moving parts. Tests must be designed, assets created, technologies configured, and results analysed. Successful testing and experimentation programs require strong project and program management capabilities. Larger organisations typically have dedicated resources for program management, whereas in smaller businesses it might be part of someone’s role. In either case, a central function must identify which tests are planned and then manage them through the system. Workflows must be created to ensure that the assets to be tested are created and deployed onto the system at the right time. Tests must be monitored to ensure that any variants that are adversely impacting the experience can be dealt with.

Two Places Where Right-Brained Creatives Can Assist With Testing

All of this is predominately “left-brain” activity, i.e., managing, coordinating, analysing, testing, and experimenting also needs “right-brain” input, a more qualitative approach incorporating a user experience perspective. This right-brain input is important into two areas:

• Test program development (what to test)
• Test design (how to test)

Test programs are often built on the basis of web analytics reports showing which parts of the site might have problems. An additional input into the test program can come from understanding what’s working and what’s not working from the user experience perspective. The main sources of insight are from voice-of-the-customer survey programs and user experience testing. Many organisations have ongoing survey programs and many elicit user feedback through open-ended questions such as “How else can we improve the site?” User feedback can be a rich source of insight, but it must be mined, contextualised, and interpreted. These are right-brain attributes. This qualitative input helps to define what are the important areas of the site to improve and where to direct testing.

Second, right-brain input is needed for test design. Once a test area has been decided, the next issue is to decide what different elements will be tested. In a test, there will always be a winner even if it’s the existing version. With testing and experimentation technologies, you can cycle through many different combinations until there’s a significant improvement. But the challenge is how do you know that the variants that you’ve decided to test are the best ones? How do you know that the winner is not the best of a mediocre bunch? Optimisation specialists may know that certain things tend to work from the body of tests they’ve seen, but other inputs such as user experience expertise help to improve the quality of testing.

Good testing and experimentation is a combination of art and science, rational approaches and intuitive perspectives, and left-brain and right-brain inputs. It’s time to take a whole-brain approach to testing and experimentation.

This article was originally published by ClickZ

But what are the ingredients of a good story and how is that relevant to analysis?

Stories have a beginning, a middle, and an end. When it comes to delivering results of a project in a presentation, I urge consultants to go by the old adage: “Tell them what you’re going to tell them, tell them, and then tell them what you told them.” In other words, start off by giving key highlights, tell the story, summarise, and close.

In addition to a basic structure, a story needs a good narrative. In our data-driven world it’s easy to get hung up on numbers and to have slide after slide containing tables full of numbers and complex graphs. The storytelling analyst will understand the narrative and will find a way to tell the narrative in an engaging and memorable way. Often, less can be more. Fewer numbers can give greater insight if they are the right numbers. Less precision can lead to more confidence. “67.3% of visitors…” can almost appear to be too precise and can leads to challenges around data accuracy, whereas “two thirds of visitors…” takes the data issues away and the focus is then on what the two-thirds of visitors did or didn’t do or think.

The storytelling analyst will also develop the flow. Stories have a cause-and-effect relationship. There are events and then there are consequences. Otherwise, the narrative is just a series of events and there is nothing for the listener or the reader to take away. In the book ‘Elements of Persuasion‘, Richard Maxwell and Robert Dickman define the elements of a good story as:

• The passion with which the story is told
• A hero to drive the action
• An obstacle or an antagonist to challenge the hero
• A moment of awareness where the hero realises how he can overcome the obstacle
• A transformation in the hero and the world around him

It can be difficult at first take to see how these elements might be incorporated into the delivery of a piece of business analysis or research, but it’s worth thinking about it. Passion is possibly the easiest in a way. A good analyst will be interested in the business and will have empathy for it. He will understand the consequences of the events that he’s describing and the relevance of them to the audience.

The story’s hero could be business customers or a segment of them. One technique might be even to personalise the story around an individual or groups of individuals by using pen portraits or personas. This can help bring the story to life and increase its relevance. The obstacle that the hero needs to overcome would be the point of the research or the analysis. The moment of awareness would be the insight from the research and the transformation would be the consequences from the recommendations accompanying the analysis.

So, next time you send out the weekly report or deliver analysis, ask yourself “What’s the story here?”

This article was originally published by ClickZ

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

Richard Sedley, Commercial Director at Foviance, will be a keynote speaker of this first edition event and will be exploring Multi Channel Customer Experience and Engagement.

Key topics of the day will be:

• Changing customer behaviour in the social era
• Altering media consumption & buying patterns
• Evolutions in the channels people use to interact

A year ago I reflected on the end of my first digital decade. I commented on how things had moved on in that time with respect to analytics and how in some areas there was a way still to go. Another year on and we’re still on the journey, so what are some of the things that I would like to see more of or less of in 2011?

More case studies

I get to go to a number of conferences on both sides of the Atlantic both to speak and also to listen. At conferences like eMetrics I get a chance to hear what’s going on on my industry and to find out more about some of the best thinking in the field. At the last eMetrics in October there were some great presentations from companies like Dell and eBay talking about what it really takes to drive a business through analytics whether that be the people, the processes or the technology. I’d like to see more companies coming forward to tell their story because its only through those stories being shared that its possible for practitioners to build up the business cases for ongoing strategic investment in digital optimisation. We definitely need to hear more often what it takes to become analytically agile and to move from a reporting mentality to an optimisation mentality.

I particularly what to hear more case studies around the challenges and benefits of multi-channel analytics, combining our web data with other customer contact data from call centers, stores, branches or other touch points. I guess great case studies like the one from USAA that I talked about recently are going to be few and far between as its takes time to build up that kind of capability, but once again its important that the industry can show case its capabilities and show what can be done.

Better marketing mix analytics

One of the areas that I think we struggle with as an industry is the understanding how well our marketing budget is working for us. Its over a hundred years since John Wanamaker famously said “Half the money I spend on advertising is wasted; the trouble is I don’t know which half” and you could argue that nothing much has changed even in the digital world. We still have real problems determining which media are working and which aren’t and often have to cling to the simplistic and naive last click attribution view of the world.

Progress is being made in this area and we are seeing new technologies evolving to deal with this problem, however I think that one of the best things to happen would be if Google added some improved attribution functionality to Google Analytics. I don’t think it needs to be analytically complex as one of the great things about Google Analytics is that it can make analysis relatively easy but i do think that “under the hood” they could incorporate some improved ways of looking at all marketing touch points in the path to conversion.

Less data, more stories

Finally, I think it would be great if we saw less data in 2011! I know that might seem like a strange thing for someone like me to say but as digital analytics becomes more mainstream in the business, it also needs to become more user friendly. I feel that in order to do that we need to show less data around the business and tell more stories. This is to some extent about challenging analysts (both in companies and in agencies) to generate more “insights” and to do that by showing fewer numbers. Real insights are often simple stories that are told well, in a way that the business can do something about it. This isn’t easy to do as it requires time (and to some extent different skill sets) but hopefully in 2011 we will see more emphasis on turning our vast amounts of data into powerful and compelling stories.

With that may I wish you all a prosperous and successful year ahead. What would you like to see happen in 2011? Please comment below.

London, UK –15 December, 2010 – Foviance, the UK’s leading customer experience consultancy and usability specialist, has appointed Guy Stephens as senior social customer care consultant, and Richard Sedley as commercial director. Both will be based at Foviance’s London headquarters.

Paul Blunden, CEO of Foviance said: “We’re delighted to have both Guy and Richard on our team here at Foviance. Both appointments are indicative of the company’s growing emphasis on providing more strategic value to all of our clients.”

In his new role as senior social customer care consultant at Foviance, Guy Stephens is already exploring how social media is changing the way companies and customers work and communicate with each other. Fundamental shifts in how customer service is provided over the last two years as a result of social media, are presenting businesses with a new and very different set of challenges. Guy will use his considerable experience and expertise in this field to ensure Foviance is able to help clients undergoing this transformation. Before joining Foviance, Guy was customer knowledge manager for The Carphone Warehouse where he began use of social media within customer service, primarily through Twitter, blogs, YouTube and Facebook.

As Foviance’s new commercial director, Richard Sedley will oversee the expansion of the company’s client development team as well as working to increase the value of the multi-channel services that Foviance already successfully delivers for its clients. Additionally, as course director for social media at the Chartered Institute of Marketing, Richard will ensure that Foviance clients are always best placed to take advantage of developments in the social web. Prior to joining Foviance Richard worked at cScape where he launched its Customer Engagement Unit, creating bespoke customer engagement strategies comprising audience research, metrics, analysis and segmentation, multi-channel engagement campaigns and communication optimisation.

Paul Blunden said: “Foviance is recognised as a leader in the field of customer experience consulting. Guy and Richard’s considerable experience of customer engagement and customer service within social media complements and extends our existing analytics, research and user experience skills to offer our clients an unrivalled customer service offering.”

For further information please contact:

Paul Blunden, CEO

Tel: +44 (0)8450 546 500
Fax: +44 (0)8450 546 501