Octavianworld

One Tough Neighborhood

Via Windows Vista on my laptop ("Puny human, I laugh at your feeble attempts to tame me!"):

Analytic Commons Project

With inspiration and encouragement from @perryhewitt, New Circle Consulting and Force Five Partners have launched the Analytics Commons Project (http://analyticscommons.com).  Here's the pitch:

Web analytics is a relatively new field that is evolving very quickly. Fortunately, it's been our experience that the community of web analysts is welcoming, vibrant, and very willing to share. The Web Analytics forum on Yahoo! is a wonderful example of this.

Analytics Commons is an effort to improve on this sharing by structuring it a bit. With structure, we can make relevant knowledge a little easier to find, and we can also make it easier to vet the expertise and reliability of the source of that knowledge. (The new Web Analytics Association Certification program is another good step in this direction.)

In designing Analytics Commons, we also decided to start by focusing on a specific form of analytics knowledge, rather than trying now to architect some general information architecture about the field that could capture all its (quickly changing) variety. In particular, we noticed:

• Google Analytics is ubiquitous.
• We're happy users of it.
• It recently added the ability to share Advanced Segments and Custom Reports.
• While GA has an Apps Gallery that features third-party creations, there is currently no public registry of such shared reports that we're aware of.
• But, there does seem to be pent-up demand for sharing reports.
• And, we had a specific itch we needed to scratch ("Target Towns", more on that below) that would help us Keep It Real.

We also figured we would start with something that would be within our ability to actually get done. Our ambition for this initiative doesn't stop here, however. So, the service also provides a way for visitors and users to suggest feedback to shape the vision and path for getting there.

So how does it work? If we've done our job well, it's hopefully self-evident. You register on the Analytics Commons site, and tell us a little about yourself, ideally through links to places where you keep your description up to date (e.g., LinkedIn, Twitter, etc.). If you've got a report to contribute, you get the url for it by clicking on the "Share button" in Google Analytics' Custom Reports or Advanced Segments sections from a GA profile in which you have access to them. Then, you add the url to our service and tag and describe what you've shared. If you need a report, you search for it on our service. If you find and try a report, all we ask is that you rate and comment on it to tell us how well it matched what you needed. Hopefully, discussions about each report will happen on our service, but if you want to connect privately with a report contributor, we've made room in our registered user profiles for folks to provide contact information if they wish. If you don't find what you were looking for, we let you store the search on our service, and if something matches in the future, we'll send you an email with the search results. If you want, you can subscribe to a weekly email listing new reports that have been added to our service, or get an RSS feed of the same.

The service is free to its users. Our privacy policy is simple: everything here is public, except your registration email if you choose not to share that. We won't share that with anyone, period. If you share a report, we assume you have the authority to do that. If you comment on a report, please be polite and constructive. We reserve the right to moderate comments, and to ban anyone who posts material we deem to be inappropriate or offensive

We saved some space on our pages for advertising / sponsorship, to help cover the server bills. If you're interested, please contact us.

Questions? Suggestions? contact us if you wish at help@analyticscommons.com.

About "Target Towns"

In our work for a client, we observed the following:

• They target wealthy customers.
• Wealth is highly concentrated in the US.
• Wealthy people are highly concentrated in a few towns.

Therefore, we thought it would be useful to track traffic and behavior from these "Target Towns".

We tried to construct an Advanced Segment for "Target Towns" through the GA UI. It didn't appear to support what we had in mind. So we asked for help. Avinash Kaushik, Nick Mihailovski, Judah Phillips, and Justin Cutroni all helped us with a piece of the puzzle (Thank You all!). In the end, the answer turned out that we needed to use the GA API. But the API also had limits on how much information you could hit it with in a single query. So we figured we needed a service that would pass the towns ("Dimensions") about which you wanted information ("Metrics") past the API sequentially, and then would aggregate and present the results in a usable form.

Then we thought: "This is a report many people are likely to need!" So, the "Target Towns" service seemed like it would be a good candidate to help seed our Analytic Commons initiative.

#OMMA Metrics SF 7/21 "Modeling Attribution" Panel: Proposed Questions

Prepping for http://bit.ly/b7KIQz

Here are some discussion questions we're considering.  What's your "keep / change / drop / add" to this list? And, please take the poll at bottom!

1. How do you define "attribution analysis", and in particular, how do you distinguish it from media mix modeling?  Where are the boundaries with "CRM"? Is it just a question of the fineness of the degree to which you can relate media effects to each other? 

2. Everyone's got a poster child example or case study that illustrates the potential of multi-channel attribution analysis.  For each of you, what's your poster child?

3. What are the practical limits of the utility of this analysis, and what's behind those limits?  Put another way, at what point do you see diminishing returns to investments in attribution analysis, and why?

4. Let's talk techniques for a moment, since the session description promised we would.  What particular approaches to data integration or to statistical analysis do you find robust enough  for real-world use, and which ones are still too fragile to make work in most cases?

5. Some people approach attribution analysis as a capability-building exercise -- if we build it, they will come -- while others come at it from a tight, hypothesis-driven focus about where the value might lie, and in what sequence it might best make sense to explore connections.  What do you need to know about a client to suggest which way, or what mix of the two, might make sense for them?

6. What are some principles and tactics for the governance of attribution analysis -- things like reconciling metrics and comp with the global optimization it implies -- that make sense here?  Can you tell any stories about how these have been developed and applied?

7. What kind of experience, training, and topical education does it make sense for marketers to have, to fully take advantage of this?

8. How do you operationalize this analytic capability -- how do you make sure we move beyond insight and apply, either manually or even in automated ways, the directions the analysis suggests?  And, how does this prospective operationalization [warning: mouthful!] affect the analysis you consider doing, in turn?

9. Let's build the ideal RFP for attribution analysis efforts, to help our clients out.  What's in it?  What shouldn't be?

10. What's your recommended reading list for learning about and following this field?

Please Sponsor Me: Nashoba Learning Group Bike-A-Thon (July 17)

This Saturday, July 17, I'll be riding in the 50-mile Nashoba Learning Group bike-a-thon.  The school does extraordinary work with developmentally-disabled children (here's a good Boston Globe article that ran a while back), and it's become a model for other schools around the country in the process.  If you are able, please sponsor me and help support the school by visiting http://www.nashobalearninggroup.org/donations.htm (select "2010 bike-a-thon / walk-a-thon").  Thank you!

OMMA Metrics & Measurement "Modeling Attribution" Panel SF 7/22: Hope To See You There

I'll be moderating a panel at the OMMA Metrics & Measurement Conference in San Francisco on July 22.  

The topic of the panel is, "Modeling Attribution: Practitioner Perspectives on the Media Mix".  Here's the conference agenda page.

The panel description:

How do you determine the channels that influence offline and online behavior and marketing performance?  

How should you allocate your budget across CRM emails, display ads, print advertising, television and radio commercials, direct mail, and other marketing sources? 

What models, techniques, and technologies should you use develop attribution and predictive models that can drive your business? 

Do you need SAS, SPSS, and a PhD in Statistics? 

Does first click, last click, direct, indirect, or appropriate attribution matter – which is best?

What about multiple logistic regression? 

What is the impact of survey and voice-of-the-customer data on attribution? 

Hear from experts who have to answer these questions and tackle these tough issues as they work hard in the field every day for their consultancies, agencies, and brands.

So far, Manu Mathew, CEO from VisualIQ, and Todd Cunningham, SVP Research at MTV Networks, will be participating on the panel as well.

Hope to see you there.  Meanwhile, please suggest questions you'd like to ask the panelists by commenting here.  Thanks!

MITX Panel: "Integrating Cross-Channel Customer Experiences" (April 29, 2010 8-10a) Part II

We've assembled a terrific panel for tomorrow's event:

• SmartDestinations' Rob Schmults is also a Creative Good Council Leader;
• Judah Phillips is a leader at the cutting edge of analytics in his role at Monster;
• At Staples, Colin Hynes plays a leading role in figuring out store / digital integration, and is heavily focused on mobile's role in that;
• VisualIQ's Manu Mathew sees a broad assortment of situations in facilitating his customers' efforts to develop a cross-channel perspective and optimize based on it.

Here are some of the questions we thought to cover:

• What integrated experiences do you look to as best practice models?
• What are you doing in your organizations (or your clients') to better integrate experiences?
• Where do you believe the greatest opportunities for better integration still lie for you?
• How are you addressing the organizational and technical challenges required for better integration?
• How far down the path toward a more integrated, globally-optimized analytic perspective do you see yourself today?
• What's your favorite integrated experience story, for good -- or not so good?
• What resources have you found helpful for learning more / tracking what's going on in this area?
• What advice would you have for folks trying to push further down this path?

Suggestions for questions welcome -- just email me via the link at left.

----------

Postscript:  a recap of the panel on the MITX blog

----------

By this point, many of you will be familiar with some of the more interesting and exotic examples of "integrated cross-channel product experiences", such as the Nike+ product/ service/ community.  But the approach has gone mainstream too.  Here's a recent example I experienced:

I went with my family to the "99" Restaurant in Centerville, on Cape Cod in Massachusetts (the one on Route 28).  Lying on the table was a pad of these forms:

  I texted my information in, and 24 hours later this appeared in my inbox:

I clicked through:

Store to text to email to web to store, all nicely connected.  Cool!  Hope we're back before it expires.  Otherwise we'll have to sacrifice another family member's phone.  (Maybe do that anyway, and ask for separate checks... Hey, times are tough!) 

This program is run soup-to-nuts for the "99" by an external service called Fishbowl Marketing.  It's pretty good! I'm hoping to speak with them about experiences and results with it.

A few observations:

• Instead of texting "99", they might have asked for "CapeCod", or "Cville" to track the geographic location of the signup, allowing them to compare signups to store traffic across regions. (Fishbowl might need an SMS address unique to the "99" client for this, and that's more expensive.)
• I may not get back to the Cape soon.  When I clicked through from the email to the landing page from home, they could have recognized where the request was coming from and returned a link to a map of nearby locations under the coupon.  I'm betting most folks won't explicitly update their preferences, especially with the unremarkable landing page copy exhorting them to do so (good testing opportunity!).
• I sometimes participate in other offers like this.  They could offer me an opportunity to personalize my offer based on crossing my cell number against other databases that also might have it, to see what other information might be there that might have helped them -- and me (analogous to caller ID).
• Some sample of users could (may?) have been asked to participate in an exit survey about their experience, perhaps for additional benefits.
• maybe implement a "Share this coupon with three friends and get another $5-off when they sign up" opportunity? (I did get follow up email messages on holidays inviting me back, and suggesting I invite friends; but when I clicked through to landing pages for inviting friends, the forms asked me to tell them who I was, again, even though I hadn't cleared cookies in the interim.)
• Also, they might have added links to their social media presences like Twitter and Facebook (for feedback, or to offer other promotions), below the coupon. 
• Finally, and I'm sure this is on Fishbowl Marketing's agenda, they might consider signing up with a mobile location-based service provider, like Foursquare or Gowalla, either as part of the vendor branded experience or via a "white label" application developed off those vendors' APIs.  That way the "99" could vary loyalty rewards granted according to number of check-ins, and take advantage of the viral marketing advantages of these services (your friends get notified when you check in at the "99", so maybe they stop by too).   Of course you say, are "99" customers leading-edge tech adopters with the latest 3G smartphones, with OC(I)D (Obsessive Check-In Disorder)?  Not yet, but what were we saying about Facebook a couple of years ago?

What's your favorite example?  Hope to see you tomorrow morning!

MITX Panel: "Integrating Cross-Channel Customer Experiences" (April 29, 2010)

On the morning of April 29 I'll be moderating a MITX panel discussion titled "Integrating Cross-Channel Customer Experiences", in Cambridge, MA (Kendall Square).  More here, more posts to follow.  Hope to see you there!

Fly-By-Wire Marketing, Part II: The Limits Of Real Time Personalization

A few months ago I posted on what I called "Fly-By-Wire Marketing", or the emergence of the automation of marketing decisions -- and sometimes the automation of the development of rules for guiding those decisions.

More recently Brian Stein introduced me to Hunch, the new recommendation service founded by Caterina Fake of Flickr fame.  (Here's their description of how it works.  Here's my profile, I'm just getting going.)  When you register, you answer questions to help the system get to know you.  When you ask for a recommendation on a topic, the system not only considers what others have recommended under different conditions, but also what you've told it about you, and how you compare with others who have sought advice on the subject.

It's an ambitious service, both in terms of its potential business value (as an affiliate on steroids), but also in terms of its technical approach to "real time personalization".  Via Sim Simeonov's blog, I read this GigaOm post by Tom Pinckney, a Hunch co-founder and their VP of Engineering.  Sim's comment sparked an interesting comment thread on Tom's post.  They're useful to read to get a feel for the balance between pre-computation and on-the-fly computation, as well as the advantages of and limits to large pre-existing data sets about user preferences and behavior, that go into these services today.

One thing neither post mentions is that there may be diminishing returns to increasingly powerful recommendation logic if the set of things from which a recommendation can ultimately be selected is limited at a generic level.  For example, take a look at Hunch's recommendations for housewarming gifts.  The results more or less break down into wine, plants, media, and housewares.  Beyond this level, I'm not sure the answer is improved by "the wisdom of Hunch's crowd" or "Hunch's wisdom about me", as much as my specific wisdom about the person for whom I'm getting the gift, or maybe by what's available at a good price. (Perhaps this particular Hunch "topic" could be further improved by crossing recommendations against the intended beneficiary's Amazon wish list?)

My point isn't that Hunch isn't an interesting or potentially useful service.  Rather, as I argued several months ago,

The [next] question you ask yourself is, "How far down this road does it makes sense for me to go, by when?"  Up until recently, I thought about this with the fairly simplistic idea that there are single curves that describe exponentially decreasing returns and exponentially increasing complexity.  The reality is that there are different relationships between complexity and returns at different points -- what my old boss George Bennett used to call "step-function" change.

For me, the practical question-within-a-question this raises is, for each of these "step-functions", is there an version of the algorithm that's only 20% as complex, that gets me 80% of the benefit?  My experience has been that the answer is usually "yes".  But even if that weren't the case, my approach in jumping into the uncharted territory of a "step-function" change in process, with new supporting technology and people roles, would be to start simple and see where that goes.

At minimum, given the "step-function" economics demonstrated by the Demand Medias of the world, I think senior marketing executives should be asking themselves, "What does the next 'step-function' look like?", and "What's the simplest version of it we should be exploring?" (Naturally, marketing efforts in different channels might proceed down this road at different paces, depending on a variety of factors, including the volume of business through that channel, the maturity of the technology involved, and the quality of the available data...)

Hunch is an interesting specific example of the increasingly broad RTP trend.  The NYT had an interesting article on real time bidding for display ads yesterday, for example.  The deeper issue in the trend I find interesting is the shift in power and profit toward specialized third parties who develop the capability to match the right cookie to the right ad unit (or, for humans, the right user to the right advertiser), and away from publishers with audiences.  In the case of Hunch, they're one and the same, but they're the exception.  How much of the increased value advertisers are willing to pay for better targeting goes to the specialized provider with the algorithm and the computing power, versus the publisher with the audience and the data about its members' behavior?  And for that matter, how can advertisers better optimize their investments across the continuum of targeting granularity?  Given the dollars now flooding into digital marketing, these questions aren't trivial.

#Adobe: Duct Tape for the "Splinternet"

(Previously titled: "Adobe: Up In The Air")

As folks line up for the iPad, SXSW rages, and the Splinternet splinters, if you own a smartphone or plan to own one, or a tablet, or if you're about to commission an app for one of these platforms, this post is for you.

A couple of years ago, Adobe seemed to have positioned itself smartly for global domination.  The simple logic:

• Online experiences becoming richer
• Adobe makes tools for rich experiences (Flash, Flex, Air)
• Ergo, Adobe becomes richer

Or for you Mondrian fans, the visual version of Adobe's "All Mine!"

Oh that it were that simple.  So, Apple, also vaguely interested in rich immersive experiences as its path out of the hip hardware niche toward intergalactic domination, plays the digital Soup Nazi: "No Flash support for you!"  Again, for the Visualistas:

The nerve!  As if that weren't bad enough, there are those pesky evolving standards to stay ahead of.  HTML 5 now rides into town to save the Internet garden from the weedy assault of proprietary browser plugins (Flash, Gears, Silverlight) for supporting rich experiences (read as: need more client-side processing and storage than HTML 4 + browsers could offer).  Like any abstraction, it has performance compromises.  But, with powerful friends behind it with a shared interest in taking down the de facto rich experience standard -- Flash is on basically every non-mobile browser out there -- HTML 5 will get better, if like any standard, slowly.  The picture:

For you conspiracy theorists, a Smoking Gun:

link

Now, those Adobe folks are pretty smart too, and they aren't sitting still.  Basically, their strategy amounts to two things:

• "Duct tape for the Splinternet", aka "Son Of Java" -- the ability to develop your app in their tools, and then compile them for whatever platform you'd like to publish to, including Apple's.  Remember "Write once, run anywhere?"  Of course you give a few things up -- some features, some performance.  But if you're a publisher, pretty tempting! 
• Do what Microsoft did a few years ago -- "Embrace and Extend".  Basically, agree to play nicely with the non-threatening parts of the HTML 5 spec while continuing to extend the feature set and performance of Flash so it's preferred on the margin as the environment for the coolest rich experiences. For example, one way -- now that Adobe owns Omniture -- to extend the feature set might be to embed analytic tracking into the application layer.

Here's a good interview Rob Scoble did with the Adobe guys where they explain all this in 22 minutes.  Here's my graphic translation of the interview:

 
A while ago I wrote a post on strategy in the software business that forms the frame for how I try to understand what's happening.  I think it still makes sense, but I'm eager to hear suggestions for improving it!

So what?  What does this mean for the publishers who are trying to figure out how to respond to the Splinternet?  I think it makes sense, as always, to start with The User.  Is what you are trying to do for him or her sufficiently exotic (and rewardably so) that you need the unique capabilities of each smartphone's / tablet's native OS / SDK?  Or is the idea sufficiently "genius" that you don't need to tart it up with whizziness, and can accept certain limitations in exchange for "Write once, run anywhere?"

I'd predict that Adobe will make common cause with some hardware manufacturer(s) -- HP, anyone?  It will be interesting to see what Adobe's willing to trade off for that support.

Where's Microsoft in all this?

Filtering The Collective Preconscious: Darwin Ecosystem

More and more, people agree that filtering the flood of information that's coming at us is supplanting publishing, finding, and connecting as the problem of the Information Age.  Today, the state of the art for doing this includes several approaches:

• Professional filters: we follow people whose jobs are to cover an area.  Tom Friedman covers international issues, Walt Mossberg covers personal technology.
• Technical filters: we use services like Google Alerts to tell us when there's something new on a topic we're interested in
• Social filters: we use services like Digg, Reddit, and Stumbleupon to point us to popular things
• Tribal filters: we use Facebook, Twitter, LinkedIn, and (Google hopes) Buzz to get pointed to things folks we know and trust think are important

In addition to what gets through, there's how it's presented.  RSS readers for example offer a huge productivity boost to anyone trying to keep up with more than a few sources of information.  However, once you get several hundreds items in your RSS reader, unsorted by anything other than "last in", it's back to information overload.  To solve this, innovative services like Newsmap provide multi-dimensional visual displays to try to push your information awareness productivity even further.  But so far, they've seen only modest adoption.

One limitation of today's filtering and productivity tools is that they pick items up either too early, before it's clear they represent something meaningful, or too late, once the advantages of recognizing a trend have passed.

Yesterday, I visited the team behind a new service called Darwin Ecosystem (video showing it off here) that takes a different and potentially more powerful and useful approach to helping you "filter the collective preconscious"  -- that is, to identify emergent signals in the vast noise of the Internet (or any other body of information you might point to -- say, for example, customer service call logs).  Co-founder and CEO Thierry Hubert is a veteran of the knowledge management world going back to senior technical roles at Lotus and IBM; his partner Frederic Deriot shares similar experiences; and, my friend Bill Ives -- formerly head of Accenture's KM client practice -- is also involved as VP Marketing.

Briefly -- look at the demo, it does a better job of explaining itself -- the service presents a tag cloud of topics that it thinks represent emergent themes to pay attention to in the "corpus" filled by sources you point it to (in the demo, sources run to hundreds of news sources and social media).  The bigger the font, the more important the theme.  Hover your mouse over a theme, and it highlights other related themes to put them all into a collective context.  The service also provides a dynamic view of what's hot / not with a stock-ticker-style ribbon running at the top of the page.  You can view the cloud of emergent themes either in an "unfiltered view", or more usefully, filtered with "attractor" keywords you can specify.

This interface, while interesting, will likely not be the eventual "user/use-case" packaging of the service.  I can see this as a built-in "front page" for an RSS reader, for example, or, minus the tag cloud, as the basis for a more conventional looking email alert service.

The service is based on the math behind Chaos Theory.  This is the math that helps us understand how the proverbial beating of a butterfly's wings in China might become a massive storm.  (Math nerds will appreciate the Lorenz-attractor-plot-as-butterfly-wings logo.)  The service uses this math to tell you not only what individual topics are gaining or losing momentum, but also to highlight relationships between and among different topics to put them into context  -- like why "underwear" and "bomber" might be related. 

Now in beta, with a few large organizations (including large media firms) as early adopters, the service has had some early wins that demonstrate its potential.  It told users, for example, that Lou Dobbs might be on his way out at CNN a week before his departure was reported in the mainstream press.  It also picked up news of UCLA's planned tuition hikes 48 hours in advance of this getting reported in popular mainstream or social media.

It strikes me that a service like Darwin is complementary to that of  Crimson Hexagon, a sentiment analysis firm based on Prof. Gary King's work at Harvard (here's the software that came out of that work), with a variety of marketing, media, and customer support applications.  Darwin helps tell you what to pay attention to -- suggests emergent themes and their context; Crimson Hexagon can then tell you how people feel about these issues in a nuanced way, beyond simple positive / negative buzz.

The current business model has Darwin pursuing enterprise licensing deals with major firms, but depending on partners that emerge, that may not be the last stop on the adoption / monetization express.  For example, it seems to me that a user's interaction with a tool like Darwin represents highly intentional behavior that would be useful data for ad / offer targeting, or personalization of content generally.  This potential use as a marketing analytics input makes it especially interesting to me.

Bottom line: if you are responsible for syndicating and helping users usefully navigate a highly dynamic information set collected through a multitude of sources -- say, a news organization, a university, a large consumer products or services firm -- and are evaluating monitoring technologies, Darwin is worth a look.

Beyond #A/B and #MVT #Testing: Optimizing Experiences

I caught up recently with Jeff Eckman and Geordie McClelland of BGC to learn more about their service for deploying, testing, and optimizing direct-response page flows.  The easy-to-use service (I saw a live demo), which is based on ion Interactive Pres & CTO Scott Brinker's LiveBall platform, combines a template-based authoring tool, CMS platform, and testing engine.  A marketing organization creates a subdomain on its web domain, and then works with BGC to develop different landing "experiences" (sequences of pages arrayed along a logical path) on it, instead of a single landing page or static, product-focused microsites.  Then the system tracks conversion rates along and through these experiences and, with full transparency to the marketers, shifts a greater share of requests to the winner.  Meanwhile, the marketers develop new page elements, pages, and paths based on what the more granular feedback about those suggests might make sense.

Contrary to popular wisdom about how fewer clicks drive increased conversion rates, BGC has found that an experience that asks for an "optimum" amount of information in an "optimum" series of screens delivers far higher results: on average 300% higher and as much as 3000+% higher in the 3+ years this practice has been in use.  I asked if their experience across multiple clients had yet suggested an overall rule of thumb, such as, "For products in this price range, three pages and three questions to each page work best", to help jump-start the creative process and save on initial creative costs, but Jeff and Geordie hadn't seen one emerge yet, and were somewhat skeptical that it could / would be worth it to pursue.  I struggled with that answer for a bit, but it's occurred to me that maybe I need to break out of my heuristic-seeking box and accept that in 2010 and beyond, the Process is the Answer (see my earlier post "Personalization Is A Process").  Jeff and Geordie are putting their money where their mouths are on this point:  The service can be offered on an easy-to-try-and-buy CPA basis (after a very modest setup fee).

We discussed technical directions that could broaden the span of the experiences they can engineer and test.  For example, you might imagine that an experience might start within a Facebook application for a couple of screens, and then make the jump to your site for the rest of the process and, hopefully, a conversion.  While they haven't done one of these yet, since a url is a url and its contents can be rendered ecumenically, this should be straightforward.

I haven't seen all the direct and indirect competition yet, but BGC's solution seems fairly unique and easy to use.  In theory you could cobble a GA-based solution together that combines their funnel analysis with their Web Optimizer A/B testing tool, but that would be clunky and likely brittle, perhaps a false economy.  And, not too long ago I wrote about Sitespect's url tunneling capability, but it strikes me that while somewhat similar, the two are currently focused on different parts of the "attract-engage-convert" process.

Bottom line: have a look, especially if you use form-based landing pages to qualify and convert leads for higher-price-point products and services.

Google Buzz: Right On Schedule

As reported in Mediapost today.  Here's my New Year's Day post on Google Wave, predicting what they're calling Buzz.  Interesting, bit not surprising -- no FB integration. 

Ecommerce On The Edge In 2010 #MITX

Yesterday morning I attended MITX's "What's Next For E-Commerce" Panel at Microsoft in Cambridge.  Flybridge Capital's Jeff Bussgang moderated a panel that included Shoebuy.com CEO Scott Savitz, CSN CEO Niraj Shah, Mall Networks CEO Tom Beecher,and Avenue 100 Media Solutions CEO Brian Eberman.

The session was well-attended and the panelists didn't disappoint. Across the board they provided a consistent cross-section of the sophistication and energy that characterizes life 2 SDs the right on the ecommerce success curve.

My notes and observations follow. But first, courtesy of Jeff, a quiz (answers at the end of the post):

1. Name the person, company, and city that originated the web-based shopping cart and secure payment process?

2. Name the person, company, and city that originated affiliate marketing on the web?

3. Name the largest email marketing firm in the world, and the city where it's headquartered?

Jeff opened by asking each of the panelists to talk about how they drive traffic, and how they try to distinguish themselves in doing so.

Brian described (my version) what his firm does as "performance marketing in the long tail", historically for education-sector customers (for- and non-profit) but now beyond that category. What that means is that they manage bidding and creative for 2 million less-popular keywords across all the major search engines for their customers. Their business is entirely automated and uses sophisticated models to predict when a customer should be willing to pay price X and use creative Y for keyword Z to reel in a likely-profitable order. The idea is that the boom in SEM demand has driven prices way up for popular keywords, but that there are still efficient marketing deals to be mined in the "long tail" of keyword popularity (e.g.,structured collaboration").

Niraj noted that there's an increasing returns dynamic in the SEM channel that raises entry barriers for upstarts and helps firms like CSN preserve and expand their position.  Namely, as firms like his get more sophisticated about conversion through scale and experience, they can afford to pay higher prices for a given keyword than smaller competitors can, and can reinvest in extending their SEM capabilities.  CSN now has a 10-person search marketing team within its total staff of 500. Since SEM is, to some degree, a jump-starter for firms that don't yet have a web presence sufficient to drive traffic organically, this edge is a powerful competitive weapon.  CSN is up to $200 million in annual revenues, and now manages the online furniture stores for folks like Walmart.

Scott sounded a different note, with similar results.  Shoebuy has focused more on cultivating its relationship with its existing customers and on Lifetime Value -- including referrals.  This focus has had a salutary effect on SEO, allowing them to rely less on SEM as it gets pricier.  Last year Shoebuy experienced double-digit top line growth and hit 8M uniques for December's shopping season, while realizing its lowest marketing expense as a percentage of sales since 2002.  They've continued to plow the savings into a better overall customer experience.  One way Shoebuy guides this reinvestment is through extensive use of Net Promoter-based surveys.  They keep the surveys brutally simple:  1)"Were you satisfied?" 2)"Whould you shop with us again?" 3)"Would you recommend us?".  Then they calculate the resulting NP scores to different things they try in their marketing mix, to give them a more nuanced insight than the binary outcome of an order can provide.

Tom described how while Mall Networks' traffic is "free" -- it all comes from their loyalty program partners' sites (e.g. Delta Skymiles website awards redemption page) -- they still have to jockey for Mall Networks' placement on those pages. (Though Tom was too polite to say so, the processes for deciding who goes where on popular pages is often a blood sport and ripe in most organizations for a more structured, rational approach.)

Former Molecular founder and CEO Ralph Folz asked about display -- is that making a comeback?  Brian indicated the lack of performance and the lack of placement control through ad networks made that a highly negative experience.  He did note that they are now experimenting with participation in real-time-bidding through ad exchanges for inventory that ad networks make available, sometimes for time windows only a hundred milliseconds long.  Jeff reinforced the emergence of "RTB" and mentioned MIT Prof. Ed Crawley's Cambridge-based DataXu (which Flybridge has invested in) as a leader in the field.

Affiliate marketing came up next.  Tom explained the basics (in response to a question): each of the 600 stores in Mall Networks stable pays Mall Networks, say for example, a 10% commission on orders that come through Mall Networks.  Mall Networks gives a chunk to the members of various loyalty programs that shop through it -- say 3-5% of the value of the order; some goes to the loyalty programs themselves, as partial inducements for sending traffic to Mall Networks, and the rest goes to Mall Networks to cover costs and yield profits.

All the other panelists include affiliates in their marketing mix, and all appeared satisfied to have them play a healthy role.  Niraj specifically mentioned the ShareASale and Google Affiliate networks.  Jeff asked about everyone's frenemy Amazon; the answers were uniformly respectful: "they're a tough competitor, but they build general confidence and familiarity with the ecommerce channel, and that's good for everyone."  Niraj noted the 800 lb. gorilla nature of their category dominance: "They're at $20m and NewEgg is the next biggest pure play at $2B.  They're a fact of life. We just have to be better at what we focus on."

Someone in the audience raised email.  All of the panelists use it, with lists ranging from millions to hundreds of millions of recipients in size.  They noted that this traditional pillar of online marketing has now gotten very sophisticated.  In their world, they look well beyond top line metrics like open- and clickthrough rates to root-cause analysis of segment-based performance.  Re-targeting came up, and Niraj noted that for them, email and re-targeting weren't substitutes (as some have seen them) but in fact played complementary roles in their mix.  (Jeff explained re-targeting for the audience: using an ad network to cookie visitors to your site, and then serving them "please come back!" ads on other sites in the network they go to after they've abandoned a shopping cart or otherwise left your site.  A twist: serving ads inviting them to *your* site after they've abandoned one of your competitors' sites.  Hey, all's fair in love, war, and ecommerce...).  A common theme:  unlike most of the rest of the world, email teams at these leading firms are tightly integrated with other channels' operators to better integrate the overall experience, even to the point of shared metrics.

What about social?  Scott: "Building community is key for us.  We run contests -- "What are you hoping will be under your tree this Christmas?" -- to stimulate input from our customers.  And, while we have social media coordinators, many people here participate in channels like Twitter in support of our efforts."  Niraj: "Our PR team came up with a 'Living Room Rescue' contest which we did in partnership with [a popular] HGTV host [whose name escaped me -- C.B.].  We got six thousand entries; we used a panel of professional decorators to narrow the list to a hundred, and then used social voting to choose a winner.  We publicized the contest, and it took on a life of its own, as local papers tried to drum up support for their local [slobs -- my word, not Niraj's].  While we couldn't / didn't measure conversion directly from this campaign, our indirect assessment was that it had a great ROI."  Jeff observed that social's potential seems greater when the object of the buzz is newsworthy.

It was a short leap from this to a question about attribution analysis, the simultaneous-dream-and-nightmare-du-jour for web analytics geeks out there.  Brian was surprisingly dismissive.  In his experience (if I understood correctly), he's seeing only up to 20%, and usually only 5-10% of order-placing customers touch two or more properties they source clicks from, across the broad landscape they cover, across a time frame ranging from a day to a month long.  "In the end, only a couple of dollars would shift from one channel to another if we did attribution analysis, so in general it's not worth it."  We chatted briefly after the panel about this; there are large ticket, high-margin exceptions to this rule (cars).  I need to learn about this one some more, it surprised me.

Mobile!  Is it finally here?  Scott reports that 6-9 months ago *customers* finally began asking for it (as opposed to having it pushed by vendors), so now they have a Shoebuy.com iPhone app.  Jeff noted that customers are rolling their own mobile strategies -- some folks are now going into (say) Best Buy, having a look at products in the flesh, then checking Amazon for the items and buying them through their iPhone if the price is right.  So, your store is now Amazon's showroom.  If you can't find something, or didn't even know you wanted it, but happen to stray near a store carrying it, location-based services will push offers at you -- and the offers may come from competitors.  (Gratuitous told-you-so here.)  Niraj:  "Say you're in Home Depot.  You want a mailbox.  Their selection is 'limited' [his description was more colorful]. We have 300 to choose from.  Wouldn't you want to know that?" Jeff:  Soon we'll also see the death of the checkout line: you'll take a picture of the barcode on the object of your desire, your smartphone will tell the store's POS system about it, and the POS system will send back a digital receipt you can show someone (or in the future, something) on your way out of the store. 

With all these channels in use, I asked how often they make decisions to reallocate investments across (as opposed to within) them -- say from search to email, as opposed to from keyword to keyword.  Brian: "Every day, each morning.  Some things -- like affiliate relationships -- may take 3-4 days to unwind.  But the optimization is basically non-stop."  Later we talked about the parallels with Wall Street trading floors.  For him, the analogy is apt.  Effectively he's a market-maker, only the securities are clicks, not stocks.  It's now reflected in their recruiting: many recent hires are former Wall Street quants.

A final note: The cultures in these shops are intensely customer-focused, flat, and data-driven.  Scott reads *every one* of the hundreds of thousands (yes you read right) of customer survey responses Shoebuy gets each year.  He also described the enthusiasm with which their customer service team embraced having all company communications to customers end with an invitation to email senior management with any concerns.  Niraj described CSN's floor plan:  500 people, no offices.  Everyone in the company takes a regular turn in customer service.  Everyone has access to the firm's data warehouse.  Brian told us about a digital display they have up in their offices showing hour-by-hour, source-by-source performance.  They also recently ran a "Query Day" in which everyone in the company -- including sales, finance, HR -- got training in how to use their databases to answer business questions.  Tom described that they “watch the cash register every minute, hour, day during the Christmas shopping season.”

This was a terrific session, and I've only captured half of it here.  Further comments / corrections / observations very welcome.

Quiz Answers:

1. MIT Prof. David K. Gifford, Open Market, Cambridge

2. Tom Gerace, BeFree, Cambridge

3. Constant Contact, Waltham

What's NYT.com Worth To You, Part II

OK, with the response curve for my survey tailing off, I'm calling it.  Here, dear readers, is what you said (click on the image to enlarge it):

(First, stats: with ~40 responses -- there are fewer points because of some duplicate answers -- you can be 95% sure that answers from the rest of the ~20M people that read the NYT online would be +/- 16% from what's here.)

90% of respondents would pay at least $1/month, and several would pay as much as $10/month. And, folks are ready to start paying after only ~2 articles a day.  Pretty interesting!  More latent value than I would have guessed.  At the same time, it's also interesting to note that no one went as high as the $14 / month Amazon wants to deliver the Times on the Kindle. (I wonder how many Kindle NYT subs are also paper subs getting the Kindle as a freebie tossed in?)

Only a very few online publishers aiming at "the general public" will be able to charge for content on the web as we have known it, or through other newer channels.  Aside from highly-focused publishers whose readers can charge subscriptions to expense accounts, the rest of the world will scrape by on pennies from AdSense et al. 

But, you say, what about the Apple Tablet (announcement tomorrow! details yesterday), and certain publishers' plans for it?  I see several issues:

• First, there's the wrestling match to be had over who controls the customer relationship in Tabletmediaworld. 
• Second, I expect the rich, chocolatey content (see also this description of what's going in R&D at the Times) planned for this platform and others like it to be more expensive to produce than what we see on the web today, both because a) a greater proportion of it will be interactive (must be, to be worth paying for), but also because b) producing for multiple proprietary platforms will also drive costs up (see for example today's good article in Ad Age by Josh Bernoff on the "Splinternet"). 
• Third, driving content behind pay walls lowers traffic, and advertising dollars with it, raising the break-even point for subscription-based business models. 
• Fourth, last time I checked, the economy isn't so great. 

The most creative argument I've seen "for" so far is that pushing today's print readers/ subscribers to tablets will save so much in printing costs that it's almost worth giving readers tablets (well, Kindles anyway) for free -- yet another edition of the razor-and-blade strategy, in "green" wrapping perhaps.

The future of paid content is in filtering information and increasing its utility.  Media firms that deliver superior filtering and utility at fair prices will survive and thrive.  Among its innovations in visual displays of information (which though creative, I'd guess have a limited monetization impact) is evidence that the Times agrees with this, at least in part (from the article on Times R&D linked to above):

When Bilton swipes his Times key card, the screen pulls up a personalized version of the paper, his interests highlighted. He clicks a button, opens the kiosk door, and inside I see an ordinary office printer, which releases a physical printout with just the articles he wants. As it prints, a second copy is sent to his phone.

The futuristic kiosk may be a plaything, but it captures the essence of R&D’s vision, in which the New York Times is less a newspaper and more an informative virus—hopping from host to host, personalizing itself to any environment.

Aside from my curiosity about the answers to the survey questions themselves, I had another reason for doing this survey.  All the articles I saw on the Times' announcement that it would start charging had the usual free-text commenting going.  Sprinkled through the comments were occasional suggestions from readers about what they might pay, but it was virtually impossible to take any sort of quantified pulse on this issue in this format.  Following "structured collaboration" principles, I took five minutes to throw up the survey to make it easy to contribute and consume answers.  Hopefully I've made it easier for readers to filter / process the Times' announcement, and made the analysis useful as well -- for example, feel free to stick the chart in your business plan for a subscription-based online content business ;-)  If anyone can point me to other, larger, more rigorous surveys on the topic, I'd be much obliged.

The broader utility of structuring the data capture this way is perhaps greatest to media firms themselves:  indirectly for ad and content targeting value, and perhaps because once you have lots of simple databases like this, it becomes possible to weave more complex queries across them, and out of these queries, some interesting, original editorial possibilities.

Briefly considered, then rejected for its avarice and stupidity: personalized pricing offers to subscribe to the NYT online based on how you respond to the survey :-)

Postscript: via my friend Thomas Macauley, NY (Long Island) Newsday is up to 35 paid online subs.

Marketing Zeitgeist: Winter 2010 #amab

Call me Ishmael.  Wednesday night I was on the tip of Boston's Fish Pier, attending the AMA Boston chapter's first panel of the year at the Exchange Conference Center. The title of the event was "Marketing 2010: What CMOs Are Saying".   Panelists included Harpoon Brewery's EVP of Marketing Charles Storey, Dancing Deer Bakery's VP of Direct-to-Consumer Marketing Scott Miller, and Philips Healthcare VP of Global Communications Frank McGillin.  Collectively they represented a useful cross-section of the B2C-B2B spectrum.

Myles Bristowe, the chapter president and an old acquaintance from ArsDigita days, moderated.  Myles' first question was "How has the economy affected your marketing plans for the coming year?"  The consensus answer I heard, channeling Stephen Stills, was to "Love The One You're With."  Charlie talked about increasing purchasing frequency among folks who know Harpoon and are brew-istas.  Scott described plans to de-seasonalize their business by positioning DD products as gifts for occasions beyond end-of-year holidays, and to invest in database technology to do a better job of personalization ("It's worse to do personalization poorly than not at all.")  And Frank talked about how Philip's event-focused strategy would focus less on tallying leads and evaluating events as lead sources per se, and more on the quality of engagement of interactions (online and off), trusting that this will prove a better indication of the efficiency and effectiveness of their investment in pricey events.

In answer to where they are increasing and decreasing their spend, the panelists presented an interesting duality, combining a "going to the mattresses" reliance on channels they know and love (Harpoon and Philips both rely heavily on events) and a forward-looking focus on integrating the cross-channel experience.  Charlie talked about Harpoon's intent to "cut in new channels and go back to the core [events]", describing their marketing strategy as "experiential" (focused on music festivals, road races, bike races, and the like) with support for "enthusiast activities with a social component" where they could use social media to reinforce the investment in the event itself.  Further, Charlie talked about the importance of documenting these experiences -- storytelling -- to reinforce and extend the impact of the events themselves on brand affinity.  Frank talked about how Philips is working to ensure that they are trying to "get better synergy across channels, by understanding customer segments and their purchasing experiences."  Scott described how DD's D2C average order value and conversion rates are much higher in areas where thay have a presence in grocery stores, and how they are re-focusing on "harvesting cross-channel affinity" by targeting their outbound D2C investments into geographies where they have a wholesale presence / store distribution. 

More generally, Scott talked about how the ebbs and flows of supply and demand are also affecting where they put their marginal dollars.  He described how a couple of years ago, surging postage and printing costs had pushed them away from physical catalogs and toward email but also SEM in particular.  However, more recently, popular keywords have been bid up to the point where that channel has become less attractive on the margin.  Meanwhile, affiliates have matured to the point where they can be relied on more, and, related, Scott's seeing major ROI in their SEO investments -- every dollar invested there has
produced $95 in revenue.  Throughout, direct marketing generally and email specifically "still work".  As for social media, his experience so far has been that it's useful for supporting the brand, but it's not yet accountable enough to be looked to as a monetization mainstay.

Speaking of social media, Charlie and Frank echoed Scott's sentiment.  Charlie noted that Harpoon still relies primarily on a high-five figure house list for its email newsletter as the get-the-word-out cake, and its so-far-more-organic social media efforts as frosting.  Frank talked about how for Philips, their main investment so far in social media has been more focused on listening in established communities such as Sermo and Facebook's "Innovations In Health" group, rather than "trying to build the world's biggest online community of MRI enthusiasts."  In particular, he noted there's a genuineness of the feedback you get in these settings that the artificiality of focus groups and surveys tends to suppress.  And Scott talked about how DD is trying to "recycle" the listening it does through its call center's conversations with customers, where "everyone's got a cookie story -- 'I just want you to know that Grandma had one of your brownies just before she passed!'" to do online justice to this organic brand advocacy they're hearing everyday.

Another question concerned how measurable they find / are trying to make their marketing, and what that's meant to their business.  Scott described DD as very analytically driven, telling a story about how insights have transformed their business.  he described how they had observed that 92% of their orders were "ship-to-someone-other-than-buyer".  This helped them conclude that they weren't really a bakery, as the founders perceived, but a gift retailer.  So, they stopped taking pictures of the cakes, and started taking pictures of the packages for their catalogs! (Very memorable "data is the new creative" example, IMHO.)

The panelists were asked about the degree to which they are pursuing finer-grained measurement, and how much they are using testing.  Interestingly, they suggested that there were both cost and utility limits to what they could do.  Charlie noted that being two layers away from the customer made measurement beyond profit per case-equivalent a very expensive proposition for them. As for testing, Scott noted that with most of their sales concentrated in a very tight seasonal window, testing carried high risks that didn't rule it out, but made them more conservative about what to try.  Nonetheless, he noted that given the ease of fielding some tests they are now able to adjust what they do within this tight holiday window if they start very early -- right after Thanksgiving this year, for example.

I asked what campaigns by others they found memorable and gave them ideas for their own marketing.  All three panelists mentioned good ones. I liked Frank's best: he described how, before and during a major snowstorm, Volvo Boston had sent email weather advisories and reminders about topping up on windshield fluid.  Great example of indirect brand building through a useful service.

Afterward I chatted briefly with Paul Regensburg, President of Rain Castle Communications, which recently helped Unica re-launch its brand.  Paul noted a slightly less breathless tenor about "new channels" among the panelists than you'd expect if all you read were the trades.  We agreed that it's always different to hear directly from practitioners, especially when you ask them about everything they're grappling with rather than any particular channel effort or campaign.  The calibration was really useful.

(Finally, congratulations to Myles and his volunteer colleagues for the great work they've done building the Boston chapter to be the fourth largest of 78 in the country.  Last night's event drew well over 100 people, not bad for a frosty January weeknight.  Myles noted that 30% of ticket sales for the event
had come from their viral "Tweets For Seats" Program.)

What's NYT.com Worth To You?

Via Chris Schroeder's  (@cmsschroed) RT of Henry Blodget (@hblodget), the news of the NYT's decision to start charging (again) for content.

Blodget's prior analysis suggested this might be worth ~$100 million per year  (my deduction based on his math) to NYT Co.  If a tenth of its 130M monthly unique visitors end up being "heavy users" that pay, 4 bucks a month gets them ~$600 million annually (13m * $4 * 12 months = $624 million).  (Seems high; better data anyone?)

What's it worth to you?  See what some folks had to say in the chart below.  Please take this survey to add your perspective, and let your friends know about it:

Note: I removed one response of "1 million articles for free, willing to pay $0 thereafter" because it messed up the display, but am mentioning it here for full disclosure. And to the respondent, thank you for participating!

Postscript: conclusions and analysis

Looking for a Web Marketing Analyst

Force Five Partners is looking for a web marketing analyst.  See http://www.forcefivepartners.com/opportunities.html for more details.  Referrals appreciated!

Grokking Google Wave: The Homeland Security Use Case (And Why You Should Care)

A few people asked me recently what I thought of Google Wave.  Like others, I've struggled to answer this.

In the past few days I've been following the news about the failed attempt to blow up Northwest 253 on Christmas Day, and the finger-pointing among various agencies that's followed it.  More particularly, I've been thinking less about whose fault it is and more about how social media / collaboration tools might be applied to reduce the chance of a Missed Connection like this.

A lot of the comments by folks in these agencies went something like, "Well, they didn't tell us that they knew X," or "We didn't think we needed to pass this information on."  What most of these comments have in common is that they're rooted in a model of person-to-person (or point-to-point) communication, which creates the possibility that one might "be left out of the loop" or "not get the memo".

For me, this created a helpful context for understanding how Google Wave is different from email and IM, and why the difference is important.  Google Wave's issue isn't that the fundamental concept's not a good idea.  It is.  Rather, its problem is that it's paradigmatically foreign to how most people (excepting the wikifringe) still think.

Put simply, Google Wave makes conversations ("Waves") primary, and who's participating secondary.  Email, in contrast, makes participants primary, and the subjects of conversations secondary.  In Google Wave, with the right permissions, folks can opt into reading and participating in conversations, and they can invite others.  The onus for awareness shifts from the initiator of a conversation to folks who have the permission and responsibility to be aware of the conversation.  (Here's a good video from the Wave team that explains the difference right up front.)  If the conversation about Mr. Abdulmutallab's activities had been primary, the focus today would be about who read the memo, rather than who got it.  That would be good.  I'd rather we had a filtering problem than an information access / integration problem.

You may well ask, "Isn't the emperor scantily clad -- how is this different from a threaded bboard?"  Great question.   One answer might be that "Bboards typically exist either independently, or as features of separate purpose-specific web sites.  Google Wave is to threaded bboard discussions as Google Reader is to RSS feeds -- a site-independent conversation aggregator, just as Google Reader is a site-independent content aggregator."   Nice!  Almost: one problem of course is that Google Wave today only supports conversations that start natively in Google Wave.  And, of course, that you can (sometimes) subscribe to RSS feeds of bboard posts, as in Google Groups, or by following conversations by subscribing to RSS feeds for Twitter hashtags.  Another question: "How is Google Wave different from chat rooms?"  In general, most chats are more evanescent, while Waves appear (to me) to support both synchronous chat and asynchronous exchanges equally well.

Now the Big Question: "Why should I care?  No one is using Google Wave anyway."  True (only 1 million invitation-only beta accounts as of mid-November, active number unknown) -- but at least 146 million people use Gmail.  Others already expect Google Wave eventually will be introduced as a feature for Gmail: instead of / in addition to sending a message, you'll be able to start a "Wave".  It's one of the top requests for the Wave team.  (Gmail already approximates Wave by organizing its list of messages into threads, and by supporting labeling and filtering.)  Facebook, with groups and fan pages, appears to have stolen a march on Google for now, but for the vast bulk of the world that still lives in email, it's clunky to switch back and forth.  The killer social media / collaboration app is one that tightly integrates conversations and collaboration with messaging, and the prospect of Google-Wave-in-Gmail is the closest solution with any realistic adoption prospects that I can imagine right now.

So while it's absurdly early, marketers, you read it here first: Sponsored Google Waves :-)  And for you developers, it's not too early to get started hacking the Google Wave API and planning how to monetize your apps.

Oh, and Happy New Year!

Postscript: It was the software's fault...

Postscript #2: Beware the echo chamber

A Springier #iPhone Springboard: Why, When, and How

Once again it's the Year Of Mobile.  Let's put aside for the moment whether you think this is still another macromyopic projection.  Assuming you buy that, there's no denying the iPhone's leadership position in the mobile ecosystem.  If mobile's important to you, the iPhone desktop is "strategic ground" whose evolution you should care about.

A frequent beef about the iPhone is that all apps are accessed from a single-level desktop, and that you have to swipe across several screens to get to the app you want.  (Sometimes, this can be life-threatening, as when a friend launches PhoneSaber, and you're slow on the draw.)  Today we're mostly stuck with this AFAIK, since my cursory research (browsing plus buttonholing some Apple Store folks) didn't reveal any immediate plans to upgrade the iPhone OS to address this.

It's interesting to see how what tribe you're from influences how you'd solve this.  If Microsoft (of yore, anyway) made the iPhone, the solution might likely be some sort of Windows Explorer-type hierarchical folders.  If Google made the iPhone, the answer to this challenge might be Gmail-style labels / tags.  If you come from the Apple/ Adobe RIA world, Expose might appeal to you.

From the business side, my mind runs to the "Why" that will shape the "When" and "How".  Here's a 2010 prediction:  big firms will stop thinking in terms of having one iPhone app, and more in terms of fielding "branded suites" of iPhone apps. 

Let's say you're a media firm, with multiple media properties.  These properties might share a similar functional need solved by a common app, like a reader.  Or, a single media property (say, a men's lifestyle one) might want a collection of lighter-weight, function-specific apps like a wine-chooser, a tie-chooser (take pictures of your ties, then have the app suggest -- via expert opinion, crowdsourcing, or an API for your significant other to code to -- which of your ties might go well with a shirt you see / snap a picture of at the store), and so on.

Without more dimensionality to Springboard, the BigCo app developer has two choices:

• Lard up a single app to do more within the "brand experience" it creates with its iPhone app.  But monolithic apps are slower and less reliable, presumably even if you're using the Tab Bar framework.  Plus, monolithic apps don't expand BigCo's share of the iPhone Springboard desktop, presumably a desirable strategic objective.
• Build multiple apps that get scattered across the Springboard, compromising the "critical mass" feel of the "branded suite" (apps that appear together make more of a brand impression than apps appearing separately, on different screens.  I don't have any data to support this, and you could argue the opposite, that apps scattered across screens provide more frequent brand reminders.  I think folks might be likelier mnemonically to remember "five swipes to the men's lifestyle screen".  Anybody got data?).

The BigCo marketing department has a choice not available to the lowly app developer, however, and that's to write Apple a check.  It's reasonable to expect that we won't all get access to the new "MDS" (Multi-Dimensional Springboard) API BigCo gets.  Today, Apple already price-discriminates among iPhone developers: the Standard enrollment charge is $99, while the Enterprise is $299.  As this platform becomes even more important, and as BigCos want to do more with it, it's reasonable to expect that Apple will get even more creative with its pricing, private or publicly.

So that's the "Why".  As for "When", I'm guessing no earlier than 2011, given Apple's Cathedral-style approach to iPhone development (this might provide an opportunity for Android, BTW). (Thanks for re-tweeting this, @perryhewitt .)

And "How"? I'm betting on an Expose-style interface.  Swipe down to "zoom in" to a single screen, swipe up to move to a "higher altitude" and view multiple screens at once, perhaps with a subtle label or background (brand-appropriate, natch) for each one.

Who's closer to this?  What do you know?

New Year's Resolutions, 2010, Part I: Less Is More

Tony Haile was my gracious host last week for a short visit to Betaworks in Manhattan's meatpacking district.  Fascinating conversation (Thanks Tony!), more about that in a separate post to follow. 

Across the street from Betaworks' offices was this sign:

 

Hit me like a ton of bricks (no irony).  My gold standard for trying boil down what I'm doing -- and for that matter what anyone else I'm working with is doing:

• Clarity -- it's veal.
• "Promise" -- not just veal: quality veal.
• Accountability -- got a beef?  Talk to Dave.
• Brevity -- more questions?  Knock on #425.

Probably not the same epiphany for you as it was for me, and Seth Godin's got nothing to worry about to be sure, but nonetheless a high signal-to-noise moment for me given what's been on my mind.  Hope to use it to full effect in the new year.