Predictive Analytics

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

The first sign of spring is the beginning of the conference season and it kicked off for me this week when Omniture came to town hosting their European Summit in London. Around a 1,000 people from across Europe gathered together last Tuesday to listen to what one of the largest marketing technologies companies had to say. Read more…

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

I have just been reading a booked called “Super Crunchers” by Ian Ayres. It’s an interesting book on how the use of data mining and predictive analytics is becoming more widespread across all aspects of our societies, and is increasingly shaping our lives. He cites a number of different examples where these empirical approaches are able to outperform human experts in their ability to accurately predict the likely outcomes.

I particularly liked his story of an econometrician who was able to predict the expected quality of Bordeaux wine based on a simple regression analysis of weather data. He was able to predict the expected quality of a particular vintage based on just three variables; the amount of rainfall in the winter, the amount of rainfall during the harvest and the average temperature during the growing season. What was interesting for me was not the fact that he was able to make these predictions, but the accounts of the resistance and even hostility that he got from the “wine establishment” for his predictions. The wine experts of the time were very threatened and affronted by the fact that their “art” and “expertise” could be reduced to a simple equation.

Ayers goes on to give a number of other examples in various industries where the growth of data and technology has allowed data mining and predictive analytical techniques to change the rules of the game, from baseball scouting to social policy development and medicine. Quite often in each of these fields there has been resistance to the ascendency to the use of these techniques from the established experts in that field, such as baseball scouts, policy makers, doctors and so on. They would not, or could not accept that such empirical methods could be better than the expertise they had developed over years of training and experience. However numerous studies cited by Ayers have shown that predictive analytics outperforms “experts” in the ability to predict an outcome correctly. That doesn’t mean that predictive techniques always get it right just that they get it right more often than the experts.

In the digital marketing field Ayers uses the example of A/B and Multi-Variate Testing (MVT). The point he makes is that the volume of data and the technology, now allows people to run repeated tests and trials to predict which versions of which element on a page is most likely to be successful in driving the desired outcome. Those of you familiar with the MVT technologies will know that the marketing stance behind them is often that they eliminate the need for subjectivity in the design process. You just come up with some alternative versions and see which one works best. It’s the ultimate tool for overcoming bias and subjectivity of the various stakeholders involved in site development. Who needs usability testing, right?

Ayers’ background is not as a statistician or an analyst but as a lawyer. You don’t immediately think of lawyers as being masters of the empirical universe and why would a lawyer be an expert in number crunching? The interesting point being a lawyer could be similar to being an analyst. Often you are trying to prove or disprove a hypothesis and looking for the appropriate evidence to support your theory or disproves somebody else’s and, for me, this gives rise to one of the fallacies about econometrics and predictive analytics that it is purely a scientific discipline.

Predictive analytics is often as much about art as it is about science. To build a good model you need to have a good understanding of the way that the “system” you are trying to model works. More often than not, at the beginning of the model building process, there is some subjective opinion about what are going to be the likely factors influencing the thing that you are trying to predict. So where do these opinions come from? They usually come from the people who are knowledgeable or experts in that particular field. We sometimes called this the “domain expertise”. If we take the example of the econometrician predicting the quality of wine, the econometrician was also a wine buff so he had some previous knowledge about what the likely factors were that could potentially affect the quality of a particular vintage. His skill was in quantifying it.

In the same way, some domain expertise is needed in the development of good tests. If we look at MVT then the technology can help you determine which the best page design to use is. If you test 4 different versions of an element (say a call to action), then you will get a winner. That “winner” may be the one that you started out with, but it’s still the winner. It doesn’t mean though that it’s the best one, it’s just the one that was best out of the various options that you looked at. There may be a much better option out there which you haven’t tested. Usability experts can potentially provide better insights into what versions are the best ones to test in the first place, and also help to understand why the results have come out the way that they have.

So we need the experts to help us build better models. That expertise may come from years of experience or knowledge gained from understanding the effectiveness of previous models. In either case, there’s room for both the science and the art.

This post originally appeared on Applied Insights’ blog. Foviance acquired Applied Insights in November 2008, with Neil Mason joining us as Director of Analytical Consulting. As part of this acquisition, we’ve incorporated Applied Insights’ blog into our own.

It’s been a busy couple of weeks! Over the past few days we have been completing the transaction by which Foviance has acquired the business assets and brand of Applied Insights. I have joined Foviance as Director of Analytical Consulting and will be taking a seat on the Foviance Board. John is pursuing his own consultancy activities and will continue to work with us in the future. You can see the official press release here.

So what’s the background and what does all this mean?

Well, I’ve known the guys at Foviance for some time. We have and have had many common clients. Foviance is an excellent company and has a strong reputation in the market for customer experience consulting. They have been aware for some time that data, analytics and insight are critical to understanding the user experience and getting it right. The acquisition of an analytics consultancy like Applied Insights is a natural move in terms of developing the overall proposition. I’m delighted to be joining them and although it’s been less than a week, it feels good. One of the reasons why the fit with Foviance feels right is because we have common values and beliefs about what “good” looks like.

I’m heading up the analytics consulting team which is called Foviance Applied Insights. Maybe not a totally original name but “it does what it says on the tin”! In the team I will be bringing together the existing analytical capabilities of Foviance and Applied Insights and will be scaling and expanding our services over the coming months. In addition to Applied Insights core competencies in strategic analytics consulting, customer analytics, predictive analytics and optimisation we will be growing the existing capabilities within the Foviance team in web analytics consulting and developing our services around some of the core technologies out there such as Omniture, Google Analytics and others. It’s going to remain busy!

For me this is a really exciting move. With a core team in place and with the Foviance infrastructure behind us I’m looking forward to extending our capabilities, developing our ideas and continuing to offer quality consulting services and products. Look out for news either on this blog or on the main Foviance site.

This post originally appeared on Applied Insights’ blog. Foviance acquired Applied Insights in November 2008, with Neil Mason joining us as Director of Analytical Consulting. As part of this acquisition, we’ve incorporated Applied Insights’ blog into our own.

London, UK, 6 November 2008 – Foviance, the expert in digital customer experience, today announced the completion of its acquisition of Applied Insights, a leading provider of analytical consulting solutions to blue chip businesses. The acquisition will accelerate the development of Foviance’s technology agnostic analytics division and supports Foviance’s strategy to provide a comprehensive customer experience solution to its global customer base.

The acquisition brings Applied Insight’s director and co-founder Neil Mason to the Foviance team as director of analytical consulting. With his vast experience, he will serve on Foviance’s board of directors and lead the company’s new initiative and analytical consulting practice. Mr. Mason is a renowned industry figure and brings Applied Insights best practices of predictive analytics, optimisation and measuring digital marketing effectiveness to Foviance. He also brings with him Applied Insights existing blue chip client base which includes Barclays, BP and Total Jobs and he will have a pivotal role in developing further Foviance’s strategic partners such as Omniture and Google.

Neil Mason joins Foviance with 25 years of in-depth industry experience in marketing analytics and strategy. Prior to founding Applied Insights, Mr. Mason has worked in a number of senior leadership roles for many major companies including QXL ricardo and Research International UK. He also currently serves on the board of directors of the Web Analytics Association, the global industry body for digital analytics professionals.

“The combination of Foviance’s expertise in delivering seamless cross-channel experiences with Applied Insight’s leadership in understanding data analytics, is ideal for our customers, both in providing innovative services and optimising usability and conversion rates” said Paul Blunden, CEO, Foviance. “Our combined global customer base now has a partner with proven expertise to deliver a strong blend of business, analytical and technology consulting capabilities.”

“Many e-businesses are looking to improve their online performance but are not clear about what they should be measuring or how to measure it effectively, our merger with Foviance presents us with an incredible opportunity to improve the digital usability experience for businesses globally,” said Neil Mason, director of analytical consulting, Foviance.

About Foviance

Foviance is a leading customer experience consultancy that works globally with some of the world’s best known brands to deliver measurable improvements in performance. .

Founded in 2001 and with a heritage in website usability and data analytics, Foviance delivers consultancy to its clients about the effectiveness of their individual channels, such as mobile, web and call centre and how they combine in a cross-channel environment. For many clients, insight is provided not only in their home market, but also internationally through Foviance extensive alliance network.

Foviance engages with its customers wherever they are in their product lifecycle, and provides insight so they understand how to improve, create and deliver excellent customer experiences.

Foviance boasts 43 of the UK FTSE 100 companies among its client roster, including Barclays, BSkyB, and Sainsbury’s. In addition Foviance works with International brands such as Astra Zeneca, Dell and Nokia. For further information please visit: www.foviance.com

For further information:

Melanie Hesketh / Becky Cheers

Prompt Communications for Foviance

+44 208 8996 1638 / +44 208 8996 1636

Foviance@prompt-communications.com

Foviance, the expert in digital customer experience, today announced the completion of its acquisition of Applied Insights, a leading provider of analytical consulting solutions to blue chip businesses. The acquisition will accelerate the development of Foviance’s technology agnostic analytics division and supports Foviance’s strategy to provide a comprehensive customer experience solution to its global customer base.

Neil Mason joins Foviance as director of analytical consulting.

The acquisition brings Applied Insight’s director and co-founder Neil Mason to the Foviance team as director of analytical consulting. With his vast experience, he will serve on Foviance’s board of directors and lead the company’s new initiative and analytical consulting practice. Mr. Mason is a renowned industry figure and brings Applied Insights best practices of predictive analytics, optimisation and measuring digital marketing effectiveness to Foviance. He also brings with him Applied Insights existing blue chip client base which includes Barclays, BP and Total Jobs and he will have a pivotal role in developing further Foviance’s strategic partners such as Omniture and Google.

Neil Mason joins Foviance with 25 years of in-depth industry experience in marketing analytics and strategy. Prior to founding Applied Insights, Mr. Mason has worked in a number of senior leadership roles for many major companies including QXL ricardo and Research International UK. He also currently serves on the board of directors of the Web Analytics Association, the global industry body for digital analytics professionals.

“The combination of Foviance’s expertise in delivering seamless cross-channel experiences with Applied Insight’s leadership in understanding data analytics, is ideal for our customers, both in providing innovative services and optimising usability and conversion rates” said Paul Blunden, CEO, Foviance. “Our combined global customer base now has a partner with proven expertise to deliver a strong blend of business, analytical and technology consulting capabilities.”

“Many e-businesses are looking to improve their online performance but are not clear about what they should be measuring or how to measure it effectively, our merger with Foviance presents us with an incredible opportunity to improve the digital usability experience for businesses globally”, said Neil Mason, director of analytical consulting, Foviance.

Execs & Accounts UK & EU: IAB U.K., MySpace, Foviance
By Jack Marshall , November 10, 2008

Miles Bennett: Applied Insights joins Foviance
By Miles Bennett, November 8, 2008

NetImperative.com Foviance snaps up consulting solutions firm
By Net Imperative, November 07, 2008

M&Adeals.co.uk Foviance gains Applied Insights
By Ryan Daff, November 07 2008

Liesdamedlies.com Applied Insights falls into the gaping Foviance maw
By Ian Thomas, November 07,2008

Research-live.com Usability consultancy Foviance acquites Applied Insights. By James Verrinder, November 06, 2008

Mrweb.com Foviance Buys Applied Insights.
By www.drno.org – Daily Research News Online, part of www.mrweb.com, November 06, 2008

Growthbusiness.co.uk Foviance Acquires Applied Insights
By Growth Business, November 06, 2008

This article, written by Neil Mason, was originally published on Clickz.com and is republished here with permission.

Here in the UK recent statistics have confirmed that the economy has stopped expanding and that it’s possible that we may head into recession. We have had continuous economic growth for the last 16 years or so and so for many people operating in a recessionary environment is going to be new. If it’s like the last recession we had in 1991/1992 then it could be tough. So, when it comes to marketing there’s probably two ways that organisations and businesses might react.

The dumb way to react will be to slash sales and marketing costs across the board, batten down the hatches and hope to ride out the storm. Marketing services costs like investments in measurement, analytics and research will be some of the first causalities as they are seen as “discretionary” costs and not core to the business operations. Also each channel or division will take a similar hit.

The smart way to react will also be to reduce sales and marketing costs. After all, if you are selling less, you have to react accordingly to maintain profitability. However, the smart organisation will look at how they can significantly increase the efficiency and effectiveness of their marketing expenditure and what are the important activities and tools they need to be able to do that.

In a recessionary environment it may be that the online channel is a winner. Smart organisations will look to see how they can acquire or service customers more cheaply through the e-channel than through other channels. Even with the digital channels, I believe the marketing emphasis is likely to shift with three possible trends:

• An increased focus on multi-channel acquisition optimisation
• Greater deployment of conversion optimisation tools and applications
• Development of more robust and sophisticated retention marketing programmes

As acquisition budgets come under pressure, digital marketers will need to focus on how they get more bang for their buck. Classic single channel optimisation techniques such as PPC bid optimisation will only work to a certain extent as all organisations will be looking to improve channel productivity. However single channel optimisation will essentially remain sub-optimal. Smart organisations will allow investment into the tools and analytics necessary to understand how to optimise budgets across digital acquisition channels such as display, affiliates and PPC. They will ensure that they have improved attribution models that enable them to understand how channels work alongside each other (or not) and which channels are delivering value. They will also ensure that they are able to reduce the costs of Cost Per Acquisition (CPA) programmes not only through better channel optimisation but also through correct attribution of sales or conversions to the correct channel. To do this, organisations will need to look at how they collect, manage and analyse their campaign related data. Joined up marketing is difficult to achieve without joined up data. They will also need to have the right tools and skills sets to allow them to analyse that data to understand that data. Improved effectiveness will come from improved analytics.

Having persuaded someone to visit the website, the trick is to get them to do something of value. Conversion optimisation has come of age in the past couple of years but is still a nascent practice in many organisations. To leverage the investments in acquisition, organisations will need to ensure that conversion rates increase. Site designs need to continue to improve and the customer experience enhanced. To do this will require a greater understanding of what’s working and what isn’t. Good site tracking will be vital not optional. Also testing and experimental tools as well as behavioural targeting platforms can be viewed as investments that have a measurable ROI. Therefore despite a potential squeeze on budgets these types of capabilities can pay for themselves inj a relatively short period of time if they are deployed correctly. Organisations should look to improve the effectiveness and efficiency of their processes and procedures around the tools to save money rather than reduce the investments in the tools themselves.

Finally, the other trend will be the development of more robust and accountable retention marketing programmes. I often think of the digital world as a “world of ones”. Most people who visit your website only ever visit it once. A lot of them only ever look at one page or stay for one minute. If they convert, they only do that once. Most of the challenge in digital marketing seems to be to get people to do something twice. Visit twice; make the second click; place the second order and so on.

The classic saying is that it’s far cheaper to retain a customer than to acquire a new one. In recessionary times it makes sense then to focus on extracting more value from the investments already make in customer acquisition and conversion than spending more on the same. For me the definition of retention marketing is the process of converting someone twice or more without paying the costs of acquisition and conversion twice. At the point of initial conversion there is usually an exchange of value. You sell them something; they tell you their name and address. They download something, you get their email address. You also know what they bought or downloaded and so that insight forms the basis of improving their propensity to transact with you again with relevant communication at the right time. Using tools and techniques such as segmentation and predictive analytics will help with both relevancy and timeliness.

If there are stormy waters ahead what are you going to do? Batten down the hatches and hope for the best? Or invest in the right navigation equipment, learn how to use it and plot the smoothest possible course to keep ahead of the pack?

This post originally appeared on Applied Insights’ blog. Foviance acquired Applied Insights in November 2008, with Neil Mason joining us as Director of Analytical Consulting. As part of this acquisition, we’ve incorporated Applied Insights’ blog into our own.

When we think about how to evaluate a predictive model the first thing we typically think of is how accurately does that model predict against the (unseen) test data. More often than not though when we develop models our business/research customers want more than that. They want to know how the algorithm got to the predictions i.e. they want to understand the model.

The more transparent predictive methods don’t just predict they also reveal the patterns that underlie them. The two main benefits of this are that

1. Subject Matter Experts (SMEs) typically on the business/research side – can assess the model’s validity by viewing these patterns, for example as rules or formulae. This way they can see if the inherent relationships make sense. Do they see any potential anomalies in the data that we didn’t pick up when we previously explored it?
2. And of course the patterns themselves may reveal useful insights. We often find specific segments of interest; demographic groups who have a higher propensity to convert through a given channel, or re-purchasers who have short, but potentially interesting and valuable, buying cycles.

The bottom line is that when we can see what a model is doing we can glean much more from it than the likelihood that the outcome of interest (convert, attrite, default, etc.) will happen.

To be frank most of our projects are like this. This is where Decision Tree methods often win out because the output let’s us visually explore the data to both understand the model and to examine other potential patterns of interest. They may not necessarily give us the most accurate predictions but often the SMEs care more about understanding than predicting. This is a classic trade-off in PA.

There are exceptions to this. The alternative view is that accuracy is paramount and it could be that the winning model is opaque. Neural Network models are a case in point. Depending on the software you are using you might see a ranked list of fields which contribute to the prediction along with the prediction itself and perhaps an associated confidence level. Even if the final network is displayed it doesn’t necessarily explain much more.

For the most part these are the two most typical scenarios however we are currently designing a 3^rd type – where opaqueness is the main objective (together with an acceptable level of predictive accuracy of course). We’re talking to a government department who don’t want to have to send sensitive data out and who don’t want our models to reveal any of that information either. So the gist of our approach is that we’ll develop black-box models on our data and let them deploy them on their database. They’ll give us addresses and predictive scores in return but in so doing we won’t know why a particular address was selected.

Anyone living in the UK will understand the political backdrop to this as there have been various high profile cases of data going AWOL (here is the latest one). We are hoping that a somewhat unorthodox application of Predictive Analytics might help the UK government provide a valuable public service without further compromising the confidentiality of its citizens. There’s many a slip twixt the cup and the lip mind you – we’ll keep you posted…

This post originally appeared on Applied Insights’ blog. Foviance acquired Applied Insights in November 2008, with Neil Mason joining us as Director of Analytical Consulting. As part of this acquisition, we’ve incorporated Applied Insights’ blog into our own.

Applied Insights have launched themselves into the 21^st century and have set up a YouTube channel. You can find it here:

www.youtube.com/appliedinsights

So far we have some video blogs up there from the recent Emetrics conferences in San Francisco and London. Over time we will be adding to that with discussions and video seminars on various topics to do with digital marketing and predictive analytics, or even digital marketing predictive analytics!

Here’s a sample which is Neil catching up with Avinash Kaushik towards the end of Emetrics San Francisco 2008.