But, anyway, I’m doing the usual start-up learning ritual of grabbing books, collecting resources, finding blogs, and even listening to analytics podcasts. (The last is pretty jarring. I’ve gone from mellifluous NPR hosts and sexy jazz voices in my podcasts to high-pitched, nasal, mouth-breathing hosts – not to indulge in stereotypes or anything.) Two items I came across were pretty funny at first, but might actually be the start of something new.

From Statistical Analysis with R (on OReilly’s awesome Safari Books Online), the conceit is that you are a military advisor to the Shu Army in 207 C.E. and, like the people at Harrahs, the marketers at WalMart, and baseball coaches looking for an edge, you are trying to bring data to their decision-making.

This tickled me, though the reviews on Amazon seem to indicate that it’s still a dry book.

Today, I see Harvard Business Press, has a class available where you can teach yourself quantitative methods at your own pace. In this example, you are the manager of a Hawaii resort, looking to boost your business.

The pub date is 2004, so this migh be and older idea or a recent edition – I won’t know until I take the class.

If I had more time, I would teach myself R, some stats, though not business analytics with Baseball Hacks, an OReilly book that helps you generate your own stats, with sample code in R.

Despite the cheese factor, there’s something to this approach. A lot of analytics instincts and savvy come from moving around the big picture. Connecting factors in one place to another to get a handle on a third issue, or coming up with an index or metrics from triangulating with other metrics is part of the creativity of the space. While many books will use stand-alone examples to demonstrate techniques, they tend to teach only the technique and the single metric – leaving you on your own to develop that exploratory sense. By having more comprehensive case studies, with a supporting and (hopefully) sufficiently rich data set, you can learn the techniques and the craft.

Cheesy but kinda cool.

I work at a bit of a remove from my company’s M&A group. I evaluate capabilities, creative, and the non-financial value of a company’s offering (ie, are they solving a big problem? how urgent is the need for a solution and who might have that need? is it a valuable experience?). The question of whether Instagram is worth a billion dollars strikes me as hard to assess financially – especially as we try to get our heads around whether Facebook is worth $100 billion. At The Media Kitchen Venture Capital Conference, Terence Kajawa praised the deal, arguing that, as FB goes public, one of its biggest weaknesses is mobile and Instagram gives a good answer to prospective investors. Albert Wenger, of Union Square Ventures, questions whether $30 per user is the right way to value Instagram, but acknowledges that similar solid deals have been made at this amount.

Both reasons make sense to me, and there are a couple other benefits from Instagram:

I don’t know how to value this financially, but as an experience designer, looking at what’s missing or sub-par or even annoying with Facebook, I can easily see the improvements to Facebook from all of the above easily being worth 1% of their capital.

From Nivea:

From TNT:

Will be interesting to see if there are more . . . not sure how you measure. For the TNT “spot”, several hundred people probably saw it, there was no doubt some press coverage, maybe some tweets and phone video… + 23 million views. Nivea’s spot seems te be around a half million.

Over the last 11 years, I’ve had some hand in designing dozens of commerce experiences. One of the most important post-launch calls to re-design action is “cart abandonment.” Your customer has spent time on your site, liked things enough to put them in a cart, but then they don’t check-out – they leave the site. Massive design #fail. The instinct is to graph drop-off rates throughout the checkout process, look for spikes and tweak-and-test those sections.

But, recent data, shows that “cart abandonment” isn’t so much a failure as an emerging customer behavior – especially in the case of busy working moms. The customers are leaving the check-out process because something else came up that pulled their attention away.

In a study conducted by See Why, and reported in Clickz, it appears that shopping cart abandoners should be treated as prospects. People don’t mind the reminders that a cart has been abandoned – especially if it’s done with the light, humorous touch of Zappos (shown above in a correspondence to me). For busy moms, it’s possible that the purchase was a chore on the to-do list, so a reminder (done right) to finish the transaction, might actually be helpful.

Too often, we see data and rush to design fixes. Especially at agencies, teams almost reflexively rush to banish the bad number, without questioning them or looking more deeply at it. In the See Why study, the smart move here was to look hard enough at the data to see that shoppers abandon carts regularly (2.4 times a week). That look beyond the success of the single session was enough to discover a new behavior and inspire new responses.

It’s a common experience for people who come up digital and are digital change agents to encounter deeply held beliefs about how things should be done in a particular industry. Trying to bring new ideas, new processes, new approaches to ideation, digital change agents (for lack of a better phrase) frequently encounter one of two reactions: 1) “no, no that’s not how we work” to reject the new ideas; or 2) “well, yes we can do that, but it’s still in the service of _______” (insert some long-held truth about the business or industry).

One of the skills that has been forced on digital practitioners of all stripes is the ability to change mental models year to year, hold them simultaneously, or swap them out within the course of a day. Since 1994, there have been very few “truths” that have held primacy or even sway for more than 18 – 24 months. Technology standards and languages change – remember when we are all scrambling to learn Flash, or some version of SQL was the norm for data? That was only 5 years ago, and today we’re scrambling to re-embrace HTML and unstructured noSQL data.

The test of a first-rate intelligence is the ability to hold two opposing ideas in mind at the same time and still retain the ability to function.
- F Scott Fitzgerald

This isn’t a question of intellectual character, so much as a necessity – you just do it, cuz you have to, you adjust your habits, pick up new rhythms, stretch different muscles in your brain, and it’s something you suddenly how to do. As my piano teacher says to me: “practice doesn’t make, practice makes permanent.”

Personal computers and the internet are upending industries, challenging old assumptions, creating new possibilities, and forcing us to revisit fundamentals over and over again. Trying to apply what I knew about the internet and how people use computers in 2005 – before Facebook, while Encyclopedia Britannica was still being published, while we were still awaiting equipment that could do augmented reality, geo-location, instant web searches from a phone, the dominance of Flash, the prevalence of Windows as the interface to computing – would be disastrous.

So far, when it comes to the internet and personal computing, there are no lasting truths – it’s a state of constant exploration, questioning, iteration, and response to the new. While there are still lessons from the past that can be applied – they no longer constitute ‘truths’ or tenets. They are now tools in my ever-growing toolbox.

A lot of professions are already well-suited to this. In law, precedents and decisions are constantly introducing new conceptual frameworks. In science and medicine, there is a constant stream of research, new techniques, equipment and drugs, and deeper understanding of the field. But, some professions have traditionally had longer arcs of permanence and refinement – and in those industries, adapting to change is harder.

In my industry, there are some hard-earned, powerful, and hard-to-shake truths that constitute a firm, even rigid mental model. For the last 60 years, the thirty second spot has been the center of marketing arts and sciences and marketers’ most powerful weapon. Many of the most significant advances and models in the industry are based on what practitioners have learned doing TV – digital briefs tend to be derived from TV briefs, story and magic and big ideas are the metric and baseline for evaluating the value of a digital idea, and emotionally-driven messaging is the default goal of most work. It’s so refined and so ingrained that it constitutes the mental model in large parts of the industry. So ingrained can a mental model be that it makes it nearly impossible to see things in a different light, or their own light.

The Fitzgerald quote above is a bit provocative in that it’s a judgement on intelligence. But it should be recast as a skill that we need to have. Personal computing, the internet, technological change are going to present new challenges and new possibilities to us at an unprecedented and ever faster rate – being able to hold several mental models in your head, simultaneously or serially as the situation changes – is going to be a key to survival and success.

The most exciting phrase to hear in science, the one that heralds new discoveries, is not ‘Eureka!’ (I found it!) but ‘That’s funny”

You could probably swap in design for science and have a good description of where better comes from. A lot of great design work – from the iPod to Nike+ to OXO – comes from “hmm” moments. Unlike the divine inspiration of a muse, these moments come from humbler places: “I hate having to bend down or hold up the measuring cup to see if it’s the right amount”, “Why do I have to go to my computer to type in the running results I have on my racing watch?” “It sucks having to go to three different places to maintain my MP3 player and get songs for it.” Or even the simpler, “hmmmm, there’s got to be a better way”, or “do we still have to do it the way we have for the last five years.”

Truth, truth, Ideas, and ideas can come from small, “funny” places.

———–
Quick hits on big ideas:

A post from me about design versus advertising creative.

A post on Luke Sullivan’s blog about big, long, and multi-sized ideas.

One other on my blog about Steve Jobs’s presentation of iCloud: “it just works.”

An artisanal salt sampler. How many choices do most people want to make?

During a product review meeting, Jobs, bewildered by the array of products under development, asked “which one do I tell my friends to buy.” Crickets. Isaacson tells the story with some Jobsean color:

“This is crazy.” He grabbed a magic marker, padded to a whiteboard, and drew a horizontal and vertical to make a four-squared chart. “Here’s what we need,” he continued. Atop the two columns he wrote “Consumer” and “Pro”; he labeld the two rows “Desktop” and “Portable.” [Apple's] job, he said, was to make four great products, one for each quadrant. “The room was in dumb silence,” Schiller recalled.

There’s a lot of interesting corporate or product development anthropology to do figuring out how Apple got there. John Sculley – the famed maker of sugar water – appears to have been looking for new and different ways to occupy shelf space and meet particular tastes of consumer cohorts. Which is what most marketers do: there’s always been a belief that there is a right message at the right time and that extensions of product lines will reach more people and make them happier with the end result. With Chris Anderson’s The Long Tail, there is a growing conviction that catering to niche needs can be profitable and the key to success in product development and merchandising.

Because of the responsive, real-time nature of digital, you see a rush to personalization and customization in lots of projects where there just isn’t that much to say or do differently for people when you know they like cats, prefer beer to wine, or secretly enjoy paranormal teen romance. But we seem to pursue this anyway. I’m watching a friend design a premium experience to shop a limited line of electronics products right now and trying to turn small differences into enormous ones – with the belief that customization is always good. A lot of it is forced, and it feels like it will be confusing or disappointing for the customer in the end.

But with Apple, we have a singularly beloved brand striking down choice in favor of stability, simplicity, and quality. (This isn’t a new observation about Apple. They have long won in categories by doing and offering less and fewer, but doing it better and with some form feature love.)

No answers come readily to mind, but maybe a reality check on the impulse to personalize everything and let people make it their own. Some things don’t need to come in many flavors.

Google has been in this space for a while: they’ve had a roadshow for advertising 2.0 for several years, along with a variety of events and publications in the “advertising is information” vein. With ZMOT, a vook detailing the Zero Moment of Truth in consumer decision-making, they started to formalize and ground their thinking in a broader marketing framework. The Zero Moment of Truth is a geek-play on P+G’s “First moment of truth” – the point where a consumer who has seen the stimulus (the TV spot typically), is at the store shelf and makes a decision. A. G. Lafley, attempting to focus more effort on the actual experience of the product (and its impact on advocacy, WOM, and reuse/churn) dubbed the at-home use of their goods as the “second moment of truth.”

In a geek numbering gag, Google has numbered the moment between the stimulus and the store shelf decision as the Zero Moment of Truth, or ZMOT. (It’s geeky cuz, in programming and things binary, counting starts at zero rather than one.) The Zero moment is actually a bunch of moments – web searches, price comparisons, talks with friends, lookups on social networks, blog reading. It’s also semi-directed and blurs into the stimulus moment, since many ZMOT activities can spark awareness or put someone in market for something (eg, someone tweets about how much they love their new digital camera and a reader of the tweet says “Hmmmm, maybe it’s time to get a new one?”). In the ZMOT, the user is building a consideration set and forming brand preference, making it critical for marketers to take seriously and try to have an effect on it. But, ZMOT has a down-side that marketers have been wrestling with since the early days of “Skip This”: it’s non-linear, only partly emotional, rather chaotic, and favors non-brand and non-expert content. Two factoids to help orient people to this new shopping reality, the first from ZMOT:

“the average shopper used 10.4 sources of information to make a decision in 2011, up from 5.3 sources in 2010.”
- Google/Shopper Science Survey (commissioned by Google) 2011

The second from the Wall Street Journal:

“it’s well known that consumers research expensive products like electronics online, but coming out of the recession, consumers are more scrupulous about researching their everyday products such as diapers and detergent, too. More than a fifth of them also research food and beverages, nearly a third research pet products and 39% research baby products, even though they ultimately tend to buy those products in stores, according to WSL Strategic Retail, a consulting firm. WSJ April 25, 2011

(It’s worth questioning whether the recession is the main driver for this – the availability of information breeds curiosity, and the transparency the internet forces on brands allows consumers to act on product questions they’ve always had but not been able to pursue.)

Anyone who accepts either of these facts would be hard-pressed to stick to the notion of an emotionally-driven consumer funnel. While we bombard them with 5000+ brand messages a day, customers are accessing hundreds of non-brand, info-motional data points in the form of reviews, blogs, ratings, tweets, likes and other forms of approval or criticism.

Google’s recommendation is to focus marketing dollars on impacting that decisive, but slippery, ZMOT phase. (They also, unsurprisingly, put search at the center of that phase – at least that’s how many people read it.)

Facebook, now ready to IPO and become beholden to quarterly earnings forecasts, needs to make a rigorous case for itself as a marketing platform. To date, the argument for most marketers has been that brands need to be where the customers are – and since hundreds of millions of them are on Facebook, we need to get after it. This certainly gets marketers’ attention, but not necessarily the dollars (see Martin Sorrell’s evolving thinking about Facebook.) With “Grouped: How small groups of friends are the key to influence on the social web, Facebook is entering into a more formal description of customer decision-making and making a case for itself as a marketing platform, and not just a place with a lot of eyeballs. (For the record, Grouped is written by a Googler turned FB staffer and not, strictly speaking, a Facebook document. But it was the centerpiece of the Hack event.)

Facebook’s argument is pretty straightforward, (and, I might add, similar to a piece I did for Boards magazine): people turn to friends and family and their friends for decisive inputs into their purchase decisions. Yes, consumers are more information-hungry, even about low-consideration products, but, in a world where available information is exceeding the memory/storage capacities given to us on the Savannah, we need intermediaries more than ever. The most trusted, easiest to access, intermediaries are our carbon-based social networks, which often express themselves most clearly on silicon-based social networks. The nods and disapproving looks our friends give to brands on-line will be decisive.

Paul Adams, the author of Grouped and a Google defector, gave a great talk pretty much covering the book. Some highlights:

Towards the end, he challenged the room: “how many brand pages have you looked at on FB that are for brands that you haven’t worked for?”

If you’re Google, the message is: brands need to be present in the information set of the consumer. If you’re Facebook, brands need to be present in the small social networks and sub-networks of people. Both companies’ arguments point to the strengths of their platforms. ZMOT emphasizes the information (and search)-intensive moments when a consumer is building a consideration set and forming brand preferences. Grouped, on the other hand, emphasizes how the overwhelming amount of information and limited time consumers have for research forces them to rely on their social networks for decisive, validating moments in a purchase path.

Both, of course, have validity and both challenge classical marketing models based on the 4Ps, the funnel, the emphasis on emotional brand-building. Both also emphasize patience, humility, and hard, slogging work. Should be fun to watch.

Digital data – exhaust data from user clicks, social media gathering and parsing, web metrics – are new and agitating. There’s lots out there, we know we must capture it, and we chase it madly. For the most part, however, we use this data as statements of fact and benchmarking. How are we doing? How’d we do with that last thing? Where do we need to be? Very few companies are using this data to generate deeper audience insights, generate new ideas, or capture cultural tensions and what some practitioners like to call “human truths”.

We’re seeing companies, like Attention (a partner in the network I work for) and Motivequest (independent), using social and exhaust data to generate deeper insights, discover fertile areas for creative and strategic exploration, and add new dimensions to our understanding of people and categories. But, we see very few planning and strategy groups fully embracing the new data. Most analytics professionals I meet wish they could get people upstream to look at the data with them. They feel like there’s untapped veins of insights and ideas.

Practically, social data should be appealing to nearly every agency, especially small ones. Most ‘listening tools’ that capture data need only four or 5 days to generate a crunchable data set, and it’s relatively inexpensive, especially after the tool is built. Theoretically, social and digital data should be even more appealing than focus groups, surveys, and panels. Digital data captures real behaviors rather than stated intentions, it happens in real time and authentic environments, and you can track it continuously over time (as opposed to quarter to quarter or year to year).

But it’s still not being adopted widely. Why? Again, many (probably most) of the new analytics professionals I work with or speak to report, in a variety of ways, that people don’t get it, don’t want to get it.

It’s actually very understandable that account leads and planners would be hesitant to get into this space. One of the worst things that can happen to you as a strategic resource is to have some cold, hard, decisive number fall apart under scrutiny or become shrouded in doubt. With traditional data, there’s a sense of safety. We know how to use it, everyone is steeped in the measures and the techniques, and there are trusted and respected names in the field that can be invoked to gain trust and build credibility for the analysis and resulting conclusion.

In digital data, there is no gold standard, basic measures are still being hotly contested, and nobody has a very long track record. As my friend, UX consultant Jeff Parks, jokes about social media expertise: “this stuff hasn’t been around long enough for anyone to get their 10,000 hours in, so how can we have experts?”

But this is a miss. For small agencies, digital and social data is an inexpensive way to bring better insights and ideas to a client. For many small agencies and brands, it may be the only cost-effective way to improve audience understanding. For mid-sized agencies pitching a new client, social and digital data can provide fresh new insights and areas for exploration. For every agency, it can be another arrow in the analytics quiver – leveraged as a generative resource or to validate ideas.

So, what’s needed to make this shift?

Buy

Build

There’s a new option, right in the middle, that blurs the buy and build scenarios and requires new skills for agency and client. I couldn’t come up with a word that begins with B, so it’s hack.

The hack option leverages open source platforms and requires some cobbling together of functionality and tweaking (or building UI). Open source in the last years has begun to offer all sorts of solutions that weren’t as readily usable as recently as 2008. Drupal is the best example. As a CMS, it’s become a go-to option for any large-scale publishing, even if workflow management, the usual reason to go down a CMS route, isn’t necessary. WordPress, while being a blog platform, is also finding its way into being the hack choice for people looking to build a web presence. Open APIs, particularly Google’s, constitute a similar hack choice, even though they’re not open source.

So what? For many people the hack option looks to combine the best of both worlds. You avoid licensing fees, have much more freedom over the roadmap, reduced switching costs when you put a new team on the work. A former colleague of mine described the agency’s role in the hack option as architecting and writing “glue code.” To many, if not most, people, this sounds easier than actually building, and less risky.

It’s worth building hack into the equation – though a better word is needed. That blurred and sliding space between build and buy is a valuable option, but it requires new skills and accountabilities:

In many ways, you get the best of both worlds, because you’re taking on the worst of both worlds. It’s a powerful way to go. These platforms reflect a matured understanding of needs in the areas of publishing, so they deliver well on them. But these benefits are made available lower on the stack than buy options. So, once again, you need to learn some code already.