From April 7th – April 10th, I’ll be attending and speaking at the eMetrics Marketing Optimization conference in Toronto. These are my thoughts, feelings, and (hopefully) epiphanies from interacting with the world’s best and brightest in the world of digital measurement.

WEDNESDAY – APRIL 7TH – 9:35 PM

eMetrics day one. First off, the conference director Andrea Hadley did an awesome job putting things together. As with any conference, the true direction of thought leadership happens over dinner (not on stage), and sadly my inbox had to take priority this evening. So at this point, all I can offer is a quick rundown and a few opinions from the first sessions of the day.

Kickoff

After Andrea gave a quick intro, Alex Langshur, President of the Web Analytics Association, talked a bit about the WAA. A good summary highlighting the emphasis on community beyond Web Analytics Wednesday, legislation of privacy information, and education. I’m a big supporter of the WAA’s agenda, so it was a great way to start.

NHL.COM

Theresa Locklear, the director of Web Analytics & Customer Insight talked extensively about the reporting practices of the NHL. I was impressed by their degree of transparency – sharing numbers, talking about real case studies (albeit, mostly wins), and highlighting a few examples of real life optimization success. She also showcased an analyst team bigger than many (five to be exact). Clearly the NHL sees value in data driven decision making.

But at the same time, something kept popping into my head. There were quite a few examples of web optimization in the presentation, and when I asked about testing, they said they did none. In my mind, that means the decisions are largely left up to heuristics. Can’t black box that.

Qualitative vs. Quantitative panel

I’ll be honest – I caught what I could of the panel. But I’m trying to buy a house right now in Toronto, and in this market when the phone rings, you answer. But I did see enough to have a few observations.

A. I’m not sure I fully understand the logic behind having five people with (or formerly with) “Analyst” or “Consultant” in their title debating the merits or uses of qualitative data. I think we lost an important perspective by having no pure qualitative researchers representing their field. Back in my old web days, I used to think anyone could do qualitative research. When you work with PHD’s in the subject, people trained in observing and interpreting human behaviour, you recognize that there’s a difference. A few discussions at the WAA Mixer after the session reinforced my thinking.

B. When did “Quantitative” and “Business” become interchangeable? As the discussion progressed, it felt like a bit of a B-School / D-School discussion – not in terms of one versus the other, but in terms of purpose. Research is used for a lot of reasons, and yes, in some situations one is preferred over the other. Tonight felt rigid, like every situation was an either/or but not a both. Marko Hurst was the exception who I thought represented both disciplines well.

So tonight was largely a technology, mathematics, and alienation free evening. A positive in my eMetrics journey. Looking forward to a big day tomorrow.

WEDNESDAY – APRIL 7TH – 7:54 AM.

Today is my start of the eMetrics Marketing Optimization conference in Toronto, an event I am simultaneously looking forward to and dreading. On the “looking forward to” side, there are many, many awesome speakers presenting. From Avinash Kaushik to Jim Novo (a hero in the space) to my always entertaining former co-conspirator Christopher Berry, it’s an all star lineup.  I’ll also be presenting the numbers behind the Aviva Community Fund, a marquee project for Idea Couture in the social innovation and cause marketing space.

On the “dread” side, I can’t help but feel this conference is going to be the end of my formal association with the digital measurement community.I’ve been a practicing Web Analytics analyst for about 6 years now – an old guy in digital terms. But even in that space, I always felt a bit like an outsider as a user experience strategist (researcher) first and an analytics practitioner second – a divide that is becoming an argument of validation versus prediction.

Meanwhile, many of the dominant conversations are distant and foreign. As Web Analysts, we focus our efforts on what will derivate the largest impact. Usually that means optimizing the user experience around the highest revenue-generating opportunities. Rather than focus our efforts on any one individual, we analyze patterns because it’s a better use of our time. But it seems as though we’ve lost our own way – now focusing in on technologies and methods designed to derive actionable results around strategies that most clients can’t afford to build in the first place.

Over the past six years, I’ve seen an industry migrate technologies, define definitions, formalize education, and find its way onto the book shelves of many of my friends (a big win when you feel you’re in a niche space). Our current direction has me concerned that everything’s about to get effed up.

For the rich few, yes, these new methods and technologies can (and will) create a competitive advantage. But for the poor greater, this only further creates barriers to entry – introducing alienating languages, foreign skills, and high costs. I’ve heard many people in this industry talk about how wonderful Web analytics is because it’s accessible to marketers and (with a little help), it can be understood all the way to the top. Because of this, there is power in our recommendations.

While I can’t be certain yet, I get the sense that digital measurement is going the way of the great black box – a fifedome for a chosen few to understand. It’s also focusing on things most clients simply can’t resource against. While, yes, the decision support may push us towards greater accuracy, we can’t forget the politics behind all of this. I’ve been in enough Marketing Business Intelligence briefings to know (whether right or wrong) who makes the final decisions. In the world of mixed quantitative and qualitative data, whoever tells the best story usually gets the most attention. Black boxes don’t make for good stories.

If you ever visit MIT, you’ll see that their floors look antiquated and cracked. It’s because, in many cases, the hallways of MIT were  where the building materials and construction methods were first developed, and they want every student to now, and remember the origins.

Evolution and revolution are both needed, but that doesn’t mean we should ignore where we came from. I’m hoping as the conference moves forward I see a little humanization in the midst of our attempts to automate human behaviour.

We have seen social media take a new and increasing role in the word-of-mouth (WOM) consumer influence paradigm; word of mouth traditionally meant consumers speaking directly to one another and sharing experiences with products or services which have had an impact on their lives (good or bad).  Of course, communication between people (most of which may be potential consumers) is what social media is all about. This is one of the reasons why social media is so interesting for marketers; a consumer hearing a recommendation (or negative comment) from a friend or acquaintance can be so much more powerful and authentic than a company communication.

Not only does social media offer a medium where consumers can share potent product and service experiences, but the range is impressive as well….the definition of ‘friend’ or ‘acquaintance’ has perhaps shifted from years past, meaning we may now be open to receiving advice from a wider range of people.

The challenge is that market research, as an industry, seems to be struggling to keep up with the measurement of the new WOM paradigm. While usage and attitude toward social media can be tracked (such as hours per day, channels used, etc) can be tracked, specific interactions are less easily measured. It can be very difficult for respondents to recall on a survey instrument, when and where they have noticed brand mentions and/or brand communications online, even though these touchpoints may have had an impact on perceptions of the brand.

This means that currently, measurement of the online and social media WOM impact is often left to web analytic firms. It must be said that the approach may also be flawed, in that measurement of web ‘page views’ and social media ‘product mentions’ a) do not take into account touchpoints that are unseen and unsold (such as a poorly placed web ad that is simply not seen), and b) must guess as to what these metrics mean for the brand.

We at Idea Couture have a few ideas as to how to tackle these issues, but feel it would be interesting to hear ideas from the community on how this can be handled.    If there are creative ways to both a) track consumer interaction on social media, and b) measure the impact of this on perceptions of the brand (or, perhaps more importantly, sales of same!),  please let us know your thoughts!

What makes product desirable? What makes them desirable to an extent that people are attached to it (like the Blackberry, iPod or Birkin)? What is the basis of that emotional bonding? Is it based on the brand or the product or a combination of both? If they would go to the extreme to repair it, or even keep it after buying an updated version, it affects multiple ownerships.

To extend the psychological life span of products could be instrumental in reducing the demand for scarce resources and solve many sustainable challenges. Up until now, the role of the product and its design in stimulating the degree of attachment experienced toward this object remains quite obscure. As the product is under the designer’s direct control, understanding these issues is valuable for designers. Industrial designs have strong technical rational and that sometimes limits them to be reflective.

Donald Schön’s book The Reflective Practitioner (1983) discusses the crisis of professional practice. This crisis relates to the fact that professions such as architecture, design, medicine and psychology are strongly dominated by technical rationality and its positivist epistemology (PE) of practice. The problem is that PE cannot solve the dilemma of “rigor versus relevance” that professionals are confronted with. This is because PE is based on analytical, empirical and logical propositions of truth within an objective world. However, professional knowledge involves experiences, feelings and subjective evaluations, which are non-existent in PE.

The “fuzzy front end” is usually what matters and makes the most difference.  This early stage of product development often gets off to the wrong start. Too much emphasis is placed on the cost and volume trade-off and there is not enough thinking around how to turn products into a personal tool. Perhaps a tool to get work done or too to tell other who you are. In the case of a forklift, a cell phone or a toaster, you should not start with how to produce the most number of units for the lowest price while getting them into the hands of the most people.  This should come from the sales people, not the product design team. What people value most is the way that they interact with a product and what meanings it carries. This goes beyond price. The visual form, the way that they handle it, and how it makes them feel and think are all part of the design strategy. In the end, product design is simple:

- Understand the core feature that a user wants and then relentlessly reduce complexity and unnecessary elements until you get a simple user experience.
- Map out the product’s sociability – its affiliation with social groups and any product or, its category and how it is connected to different social groups or product groups.
- Look hard to find memories that are related to the product. Find pleasure that is directly and indirectly associated by using the product. Hire an anthropologist to help.

Image Source: http://www.ubergizmo.com/15/archives/2006/07/ideck_touch_screen_music_player.html; http://www.flickr.com/photos/23703702@N00/378586732/sizes/o/

Innovation doesn’t have to invent new products. It unlocks hidden value in existing ones – thereby reinvigorating a business without completely reinventing it. It is a disciplined process by which an idea is generated and that results in significant economic value creation and improved customer experience. Many of today’s ideas on innovation are about coping with unpredictability rather than understanding the key forces that create it.  There are “predictable elements or pathologies”. Once you know what those pathologies are, the process of creating profitable innovations is not as inherently unpredictable as you once thought. Because of today’s exaggerated sense of uncertainty and foreboding about the future, foresight is in great demand.  The future is much more important than the new, the hip and the cool; we need to develop a deeper understanding of change. Strategy must be created from the future backwards, not from the present forwards. This underlines the short-termism of many of today’s innovations which place too much emphasis on what your market research reported this month. The future is often a mix of revolutionary change and continuous evolution. Management teams must accept the challenge of innovation in a way that is appropriate in context and differentiates them from the competition.

Look at the media industry, we have more media options than ever, except that less and less do they include print newspapers. So what to do with those media options? What opportunities does a newspaper-less future afford? What about the auto industries? We are not seeing a future without cars, just very different kind of cars or different ways to own cars? For those who take seriously the idea of creative destruction—that innovators destroy business structures in order to create something new—how do you envision reassembling the essential parts of a media business? In the future of media, which is now, everybody is a network. In the past, networks were defined by control of content or distribution. But now, you can’t own all distribution and content is controlled where it’s created.  The problem newspapers face isn’t that they didn’t see the internet coming. They saw it but instead putting the energy and resources to preserve the old business model rather than inventing new ones.