Dave Jenkins

I really don’t like shopping.  It used to bring out my inner Marxist, but now it just incurs a low-level buzz in my head.  I’ve found I can keep it under control if I satiate my internet addiction every 10 minutes or so.  Many stores, however, are large window-less Faraday cages, which kills the 3G signal on my phone.  There’s wifi, but it’s not free (it’s usually the corporate offices of the store, and the days of poor security with open enterprise networks are over).  Free wifi in a retail environment is still a rare treat.  Some stores get it, but the vast majority do not.

So, here’s my case for offering free wifi in a retail environment:

• The percentage of customers with smart phones will only get bigger.  The share of people who will want to check prices, ask-a-friend, or otherwise tweet about their shopping choices will only get bigger.  Do you want to welcome those people, or frustrate them?
• The potential for data mining about what customers are doing on their smart phones is a huge opportunity.
• Cost is pretty minimal.  One wifi antenna should do for most stores; Macy’s might need one on each floor.

Risks are fairly minimal, and can be contained with some common sense policies:

• Put a standard anti-porn filter to mitigate the legal liability of perverts in the store.
• It’s doubtful someone would go down to the mall to download mp3s– the bandwidth is relatively poor compared to the land-line available at the public library (not that I condone that kind of behaviour).
• Someone may try to hack into NORAD from the store wifi, but again– internet cafes are better for that because they offer coffee and a table for all your blue-tooth voice encryption equipment (again– I’m not suggesting anything).  Barnes & Noble isn’t a hip enough place to hang out for that long anyway.

So, where’s the upside?  Where’s the money?  It’s in that second point in the first group: the data mining.  There are several forms of valuable bits of data flying around that the store would be well to catch:

1. Competitor Recon: if Barnes & Noble could know exactly which books people are looking up on Amazon, they could match it against their own conversion rates on those same books.  They would know where they’re losing the sale.  They would also know which books people are viewing on Amazon that B&N doesn’t stock.  This is great informaiton for gauging demand.
2. Brand Awareness:  how often are REI customers going to REI.com whilst inside the store?  Are they trying to get details on products that the floor peeps aren’t explaining well enough?  Should the floor manager and corporation welcome this kind of look-up? [yes]
3. Social network awareness: how often do customers ping Facebook that they’re about to buy / just bought a 60″ LCD or a $600 pair of boots?  How often are they tweeting?
4. Instant couponing: most free wifis have a ‘Conditions of Use’ short login page.  This doesn’t need to have a username and password, just a paragraph that tells the customer we are tracking web traffic anonymously (for all these rich data mining opportunities).  it’s a great opportunity to offer someone some up-sell and cross-sell offers, and maybe an instant coupon with a barcode for 10% they can take up to the register.
5. These same advantages apply for airports: people love to surf– a gold mine of surfing behaviour lying unexploited because some airport middle manager thinks there’s more money in trying to charge $9.99 for the 2% of people on expense accounts that will fork over that money. [stupid]

Some stores will understand this sooner than others, but in a pretty short window (the next 18-24 months), we should have pretty ubiquitous wifi signals in any urban or suburban environment.  The benefits for free and onmipresent wifi are legion.  The most apparent opportunity is the VoIP, and the chance to show some advertisements.

Google gets this second point clearly– they’ve chosen a target-rich environment (airports), and are handing out free wifi just to get people to surf, and maybe use Google, and maybe click-thru on some AdWords.  In this sense, they’re competing with the idiot box CNN.  If it pays off, I wouldn’t be surprised to see Google putting in free wifi anywhere there are more than p number of people waiting for an average of t amount of time.  The equation would look something like:

Demand (D) = p * t * p(sp)
Opportunity (O) = D * p(G) - wificost
where
p = number of people in a given location
t = average time of wait or lounging around that location
p(sp) = percentage of people with smart phones
p(G) = percentage of people who will go to Google and click on an AdWords
wificost = cost of installing and running wifi base station

In the market, I would not go long on telco stocks, unless they’re leading the pack on opened smart phones.  I would go long on Skype and Cisco, and business intelligence providers, and of course, Google.

Every few years someone re-invents real time chat.   Back in the 70s we had teletypes in the high school computer lab.  Internet purists had IRC to keep themselves entertained in the 1980s, while the early 90 gave us AOL chat rooms for the rest of us poseurs.    Soon, we all had ICQ numbers (I still have mine memorized),  then AIM aliases, which were soon replaced by jabber handles, Google chat IDs, and then came the facebooks.  All shared some basics: real-time typing, conversation windows, text-centric, and just below the speed of verbal communication.  Still, they’re all just variants on the real-time chat, a communication path that’s been around since The Beginning.

If we were to graph a spectrum of communication forms, spreading them out along the x-axis in terms of speed, and y-axis for quality of information, then email would be somewhere to the left and slightly higher than chat: It’s not real-time (you send something, and an answer comes back whenever the other person feels like it), but it can contain pictures and video, so it’s arguably better quality.  Below and to the left, we would have twitter: asynchronus, poor quality (short).  To the right of chat we would telephones (real-time verbal), and above that we would Skype: real-time verbal communication with the bonus of your friend’s beautiful face on your screen.  Skype’s real-time video conferencing should be superior (above and to the right) of all of them, right?
Why do we still have the other forms around?

• Is it because we don’t necessarily always want to see the other person? [yes]
• Is it because we sometimes don’t want to deal with the other person (your boss or girlfriend or bosses’ girlfriend or boss-you-wish-was-your-girlfriend) in real-time? [yes]
• Is it because we want to spew something out of low-quality and not have to burden ourselves with the responsibility that comes with actually having to put forward a cogent logical position? [yes]

So, it seems there is room for something that can land in that flexible in-between the safe distance that asynchronous  email gives us, but the conversational flow of chat.  If it were an open platform, people could start grafting on the higher-quality content elements like music and videos and pictures of cats eating cheezburgers.

Enter GoogleWave.  I’ve had it for a little while now, and I see some promise if people understand the construct.  Google is betting that people will want to sometimes be real-time, sometimes not-so-real-time, sometimes lo-fi, sometimes hi-fi.  I bet they’re right.

My GoogleWave ID is tokyodave@googlewave.com.  Hit me up.

I read last night that I’ll be recouping some of my losses after betting on Omniture a couple of years ago, with the pending buyout by Adobe.  The early take on this is that Adobe needs to pick up some ongoing subscription revenue, I am assuming because they simply cannot keep raising the price on the 167 legitimate licenses for Photoshop which are sold to designers in New York that everyone else copies over to Pirate Bay.

So, the revenue part I get.   But where’s the Bonus Fat?

• Up until now, Adobe provides a suite of tools that creates and converts various bits of digital eye candy for presentation on the web, but has precious little to do with the operations part of actual presentation layer.  Adobe has become the de facto ’solid document’ format with .pdf, but there’s no real money there.  They also offer the Scene7 technology, which can convert a multipage .pdf or other print document into a “browsable” online catalog (which is insane to me, but that’s how some people like to shop, I guess).  Flash is becoming more prominent but it’s never been able to get passed the debate of ‘needless cartoons’ vs. ‘functional website navigation’.

• Omniture is all about the data.  Their strategy so far has been to build up all the back-end marketing tools needed to run a dotcom: page and traffic analytics, A/B comparison, keyword tracking, affiliate relationship management, some crude BI.  They are in the driver’s seat on a lot of this– despite the disappointment that a lot of these platform tools came in through acquisitions, and didn’t necessarily play nice with each other.

So, what to make of this acquisition?  We have someone who has some juice in the front-end presentation layer, who now will have a hand in the back-end data that should be driving that presentation layer.  One thing is for sure: every marketing service in the dotcom space has one thing in common– somewhere in the sales pitch you’ll hear the salesman say “we simply take your traffic data from Omniture and…”

Ah.  There it is: product personalization, merchandising, traffic shaping, and all that crap getting shoved through the presentation layer touches Omniture-derived data at some point or another.  If Adobe can make the merchandising and happy bouncing balls that appear on the website become that more integrated and real-time personalized with the Omniture data, then they have something.

But wait– someone’s doing exactly that– they’re taking Omniture traffic data and showing personalized merchandising via Adobe Flash out to the Consumer.  They’re name is Allurent, and I bet they’re next.

I watched Amazon’s acquisition of Zappos with some interest last week.  I am certainly not the first one to blog about this, and I am no doubt one of thousands of armchair pedants on the subject, but here’s my take: Amazon is becoming the new EDI for online retail, and will continue to acquire front-end retailers– the real money is on the back-end (the real money is always on the back-end, it seems).  Amazon is becoming the new EDI.

For those of you who may not be familiar with EDI, it’s a system for all those coal-burning AS-400 mainframes and other legacy computers to share data with each other in a standard format.  Through a series of arcanely formatted pre-set protocols, computers send invoices, inventory levels, sales requests to each other, and then send back all the acknowledgement messages.  It’s efficient, but klunky.  I would bet that Amazon sees this klunkiness, and thinks it can do better, and make a little bit of cash by providing a better service.

Retailers will come and go, but they’ll always need to do a few things: store their data securely, talk to vendors, track customers, and sell stuff.  Look at Amazon’s trajectory: they offer all of these things either freely, or for a small percentage-type handling fee.  They have the A9 search/merchandising platform, a cloud computing offering, most of their sales comes in from vendors, they have millions and millions of customers tracked in real-time, and they offer a method for small vendors to sell goods fairly easily.  Prediction: Amazon.com will continue to be a front-end website, but more and more, we’ll see Amazon showing up as the “retail platform” for other branded websites (like Zappos.com).

The ice is getting thinner for conglomerated pure-play online retailers.  If they don’t offer something uniquely value-add, customers will simply go directly to the brand’s own website to buy their stuff.  Where would you buy your Adidas?  Zappos.com, Shoes.com, or Adidas.com?  It depends on what you need and what each one offers, right?  The end product is the exact same, so it comes down to the free shipping, the search engine, and the eye-candy on the website.  Amazon was never that glamorous a website to start with–  a very utilitarian look and feel (but very information-rich) experience overall.  We all know that Amazon does usability research, so all that data must be worth something, right?

Zappos has built a great base of user loyalty through its mix of customer-centric activities and transparency.  Their back-end has always been first-rate, but also probably very expensive (call centers are pricey).  If all that IT development and warehouse operations can be folded into the larger Amazonian Empire, then Zappos can concentrate on giving away free pizzas to the customers, or tweeting about Tony’s sushi dinner, or whatever.

Amazon will pick up a few more “major” retailers.  My short list of predictions includes: NewEgg.com, Overstock.com (hostile takeover likely), Etsy.com, and maybe even Target retail to finally “go cross-channel”.  They’ll likely buy out BillMeLater or even Mastercard to get the financial end covered.  Afterall, Amazon needs to watch out for Walmart.

Okay, that was a pretty lame title, but it’s actually the most clear way to express the question: what criteria or elements need to be in place to justify a mobile version of a website?

I was talking with a friend of mine, who recently got the .mobi version of his company’s domain, but hadn’t done anything with it.  He asked for advice, and I offered up the following crude thumbnail that Internet (not web) information can be broken into three main types:

1. Transactional snippets of information: flight times, restaurant addresses, bank account info, sports scores, short text email, answers to salient questions.  Mobile phones do very well at this– iphone or not– just about everyone with a phone participates in this type of internet transaction.  If you see it that way, the iphone app store really becomes a collection ot targetted info queries all eye-candied up.
2. Search-centric information: Any business model that centers around the shear number of stuff for sale/rent/download/sharing is really a search-centric model and not a browsing model.  Amazon, zappos, walmart, piratebay, and wikipedia are all search-centric.  So is Yelp.  Notice how all of these operations are either exploiting a mobile strategy fairly well (half-way), or are likely close to one.
3. Browsing ecommerce information: anything that is a context-rich window-shopping experience doesn’t do well on a mobile phone.  The screen isn’t big enough, and we don’t have the patience to make the Solomon’s decision of either viewing a stripped down version of the site or spend the time endlessly scrolling around to see the website in it’s original layout.  Etsy, Borders magic shelf, Dell, or other ecommerce sites that are inherently dependent on the web-surfing serendipity of the site won’t do well on a mobile phone– at least not without some major rethinking on what works and what doesn’t.

My friend is in an information-sharing business.  He handles sets up relationships between business partners, and brokers deals where he sees possible matches.  His real strength is the depth of information, but he certainly has plenty of small transaction-level updates that would be more valuable if offered in near real-time.  My advice to him was to look through all the activities he does, find those that are in the first bucket, and go with the .mobi version.

Times are tough.  Escapism is rising. As with all depressions, movie attendance is up, Hulu actually has a shot at beating Youtube at its own game, and alcohol sales are up, as are random hook-ups.  We can see the trend on TV: two years ago, the prime-time dreck centered around bling and fabulous homes and even more fabulous lives of the fabulous people that live in them.  Now, that same focus on the rich is there, but it’s gotten nasty: they’re being shown as the bunch of back-biting vapid rodents that they are.  I am not going to expand much on that, because you already know your favorite rodent shows that you watch every week.

Here’s the question: spending is down, and escapism is up– do those two factors translate into higher ’shopping by proxy’?  Do you find yourself spending more time online, “researching” products?  Do you use this research time as a methadone substitute to your normal online shopping habit?  My thesis was that page views on shopping sites would be higher, as people spend more time browsing around, but not necessarily buying anything.  So far, my thesis is half-right:

Discounters like ebay and Walmart are up, as is the unstoppable ruthlessly efficient Amazon (which I hate and admire at the same time, like Ash did in the first Alien):

But overall page views are the same, or slightly down.  Page views have steadily declined as site navigation becomes more efficient, and as buyers decrease, less people go through the shopping cart, which also brings down the average– but the point is that people simply aren’t window shopping on the intarwebs like everyone thinks:

Perhaps the time-wasting website traffic is up?  Are we filling our time photoshopping domo-kun and pictures of Kim Jong Il? Nope– flat, with the only gain coming from hulu (likely due to their very expensive ad campaign).

So, what is everyone doing all night?  I hate to postulate, but in the end, I think TeeVee will win the day.  It may come in through our desktops instead of home theatres, but professionally written stories with good-looking people will beat mindless cartoons and witty political banter discussion threads for the vast majority of us.

So, the Internet is everywhere.  Times was (back in the day), that we used to surf around to websites just to see the design or some cool functionality, but we are no longer enamored with the technology (well, almost).  Futurists no longer spend their time pontificating about capacity, bandwidth, or the extent of data that could be recorded in their great computers– all of that is assumed to be in place.  Rather, these seers spend their time in two activities:

a) Blowing their own horn on twitter — not worth watching

b) Showing insights on the social interaction of the great online hive that has now come into being — these are what I’ll call  “Network Biologists”, and are worth your time.

The network biologist will spend his/her time researching the strange interactions between people, and the even stranger medium that is created as a result.  They are not sociologists, because it is more than the interactions of the humans; there are robots, scripts, and crude AI influencing the mix.  The environment itself is ever changing– and the actors change as a result– but the center of focus has shifted to the behaviour of the fish, not the mechanical workings of the reef: hence the term ‘biologist’.

The usability managers in ecommerce companies were an early manifestation.  Now, everyone in the online marketing department, merchandising, and even finance is trying to ascertain how the huge mass of people will react to the online environment.  This is different from standard “retail science” or “catalog management” because of the constant arms race in online functionality as well as the multiple-variable equation where customers will influence each other in real time, as well as try to get in on the deal with some sort of affiliate, coupon, or recommendation in exchange for a slice of the profits.

The best results so far have been to segment and clasify online users into their various behavioural patterns.  Oddly enough, people don’t mind surrendering them willingly.  The current spate of “what [blank] are you?” viruses circulating on facebook are a segmentation maker’s dream: people are happy to tell us exactly what drives their brightest fears and darkest hopes. The most successful websites out there have tapped into the hive behaviour that humans portray when given just the right mix of anonymity and self-aggrandizement: Google’s page rankings are a canopy of dominant players and ground-dwellers in their shadow; Amazon’s entire merchandising catalog for millions of products is an expansion of fecundity like salmon spawning; Facebook is basic tribalism that proves Dunbar’s number, De.licio.us is our own pollen-finding wiggle dance; twitter is a sea of iridescent jellyfish desperate for attention; there is a flavour of pr0n out there for every strange perversion you could imagine (and a few you don’t want to).

I would imagine that colleges will soon have some sort of degree in Network Biology: it will be a combination of sociology, crowd biology, and basic network mechanics, to show how it is all wired together.

My good friend has decided to look for a new job.  Today, she brought in some good Mexican food for the crew as a thank you.  It was, however, not a free lunch.  In return for the tacos, we were supposed to go to the white board in the conference room and suggest where she might work next.  For the price of 2 dozen lunches, my friend tried to crowdsource her next job.

Soon enough (if not already), everyone will be connected to everyone else in their immediate market segment.  We’ll all have a Kevin Bacon number of 3 or lower.  Linkedin, which originally provided value as the “inside connection” to a given company or executive, now has become the ubiquitous contact folder for everyone.  Where recruiters used to thrive on Linkedin because it complimented and extended their most valuable asset: their rolodex of contacts, it now threatens to replace that rolodex completely.  The Recruiter still has value, as someone who knows how to interview a candidate and get at the soft chewy center of a person to see if they are a good match for the company with an open position, but not as a simple nexus of resumes in one hand and job openings in another.

Given that Linkedin has given us all that magic rolodex, why not try to crowdsource positions?  How could one simultaneously incent the armchair recruiter in all of us, yet invoke enough friction to keep out the spammers and robots?

Here is my idea:

1. Vigorously pursue companies to list their open positions on the network
2. Invite people to recommend people in their network for the open positions, with a standing bounty of 10% of first-year salary (still leaving room for the recruiter doing the actual interviews to make 10-15%)
3. If Andy is going to recommend Betty to C Corporation, then Andy needs to pay $5 to Betty (she’s the one looking for a job, and probably needs the $5 anyway)
4. C Company would see that Betty is recommended by 7 of her friends (all willing to stake $5 on it), and therefore she is probably worth a look.  If Betty is hired, the 10% is split amongst the 7 people who recommended her.
5. Andy just profited $1423 for his work (assuming 10% of $100,000 job, spilt 7 ways, minus the $5)

Hmmm.  This might work.  I should ping Harry or Alex or my old friends at Daijob.

I’ll be in Orlando this next week for the Shop.org Strategy and Innovation Forum.  The noise from vendors is discernibly more quiet, compared to last year.  I am also getting a vibe that not so many people (customers like me) will be attending.  I’ve got some specific people to visit, and some intel to gather on a couple of vendors.  We’ll see.

i’ll be sending updates at @davejenk1ns.

A good friend of mine (Let’s call him Sam Rothstein) is just finishing up a stint in the hedge fund business.  He is a bit of a quant and an overall critical thinker, so I ran the Keyword Derivative Market idea by him.  His verdict?

“It won’t work”

“Why not?”

“The risk– there’s no way to calculate the risk.  You think you’re all smart and have worked out the percentages on the bell curves and all the possibilities of what might happen that would wreck your prices, then wham! That one-in-a-billion thing that could sink your risk hedges actually happens, because it turns out to be a one-in-a-thousand thing.”

“Yeah, but that’s why I pad the keyword bids a little.”

“By how much?  What amount?  That padding is your determination of the cost of the risk– you cannot calculate it, therefore you cannot come up with a price.”

“shit.”

Sam went on to describe the basic flaws in risk-based hedge funds.  He complimented me on coming up with a business model that had recently bilked billions out of the market, but simultaneously reminded me that there are thousands of people trying to figure this out– many of them much smarter than me.

In the end, a keyword is an expungable commodity, but it also has something what I’ll call “high sucker elasticity“: Retail companies calculate the price they are willing to pay for a keyword position, usually based on some determined cost-of-acquistion equation.  If the price of a keyword bid gets pushed too high (according to a rational cost/revenue calculation), there is always another sucker to buy that irrationally high keyword postion.   Google’s profits are intrinsically linked to the irrationality of the market.

Keyword management software providers like efficientfrontier, kenshoo, marin, and others are making great headway in bringing rationality to this market, and are good for the long haul or large corporate spends– but the little man will always make keyword purchases with snap decisions based on insufficient information.  He’ll get suckered.

To their credit, Google tries to explain this out as much as possible: they make their API open to the keyword management companies, they give away performance statistics for free, they try not to be evil.

The odds on craps are written right there on the green felt, too.