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There Really Is Nothing that Cannot Be Innovated

Credit: Damjan Stanković

Credit: John Chuckman

In a recent post, Four Quadrants of Innovation, I described one type of innovation as leveraging existing technologies, serving existing customers. In popular culture, this type of innovation is..well, frankly it’s boring. No cool new advances, no new stuff you haven’t tried before.

But what is compelling about this type of innovation is how well it fits Clayton Christensen’s focus on understanding the “job” your product has been hired to do. Companies need to stay on top of their products, and changes in customer behaviors. Sometimes that’s sexy new technology advances. Mostly, it’s not. Rather, it’s good ol’ roll-up-the-sleeves and innovate to meet changing customer needs and expectations.

SlideShare CEO Rashmi Sinha wrote a great post recently where she asked Is it time to reimagine your product / service? She makes the point that many web services reflect their vintage year. They fail to evolve as the market does, ultimately falling further behind the curve of customer expectations.

Rashmi Sinha’s post very much reminds me of Clayton’s Christensen’s point of view. Your customers have:

  • Requirements you have not yet discovered at any given point in time
  • Changing requirements over time that you need to decide whether to meet

On top of that, there’s something deeper in the Sinha’s post. There are times you need to push need innovations, even if your customers aren’t yet asking for them. Let your customers catch up to you.

These points don’t just apply to web services. They apply to all manner of products and services. Everything can be innovated. One key is to understand that sometimes innovation comes in service delivery or business models, not just product features.

Even things you wouldn’t expect to be innovated, can indeed be innovated.

In line with this, I came across a great post by Jake Kuramoto of Oracle AppsLab. In Unexpected Innovation, Jake notes two recent innovations he has seen with…

traffic lights. Of all things.

Yes, Traffic Lights Can Be Innovated

The first innovation is actually not all that surprising, and really is the application of existing technology. New lights use energy efficient LED bulbs. They have some issues to be worked out in terms of their ability to melt accumulated snow. But they make a lot of sense.

The second innovation is one that really speaks to a deeper understanding of what’s going with traffic lights. See the pictures at the top of this post? Designer Damjan Stanković came up with a concept where a timer is added to stoplights. Stanković posits these benefits of such a timer:

  • Less pollution. Drivers can turn their engines off and cut carbon emissions while waiting for the green light.
  • Less fuel consumption. Turning off your vehicle while waiting on the traffic light can lower fuel consumption in the long run.
  • Less stress. Since you know exactly how long you have to wait you can sit back and clear your head for a while.
  • Safer driving. With the Eko light both drivers and pedestrians can be fully aware of how much time they have left before the light changes and that way reduce the chance for potential traffic accidents.

That last bullet is the benefit that intrigues me most, in terms of the job I want a stoplight to do: safer driving. Here in San Francisco, we have walk signals at intersections that include countdowns. When the WALK signals appears, you can see how many seconds are left to cross the street.

Both Jake Kuramoto use these walk signal countdowns in a different way. When you are driving, you can see the countdowns. If you’re, say 50 meters out, this gives you something of an advantage in how you approach the intersection. When there are only a few seconds left, you know the light will be yellow well before you get to the intersection. With kids in the car, I slow down to be ready to stop for what will be a late yellow light by the time I reach the intersection.

Now if someone had asked me, I wouldn’t have come up with a requirement for traffic lights to have timers. But because someone put those countdowns on the walk signals, I’ve found myself using them in my driving when they are available. And Stanković’s design makes me realize that, “hey, I want those timers on traffic lights.”

Which goes to show you. Everything can be innovated upon. Even the most…uh…pedestrian of products and services.

Finally, I love this quote from Amazon’s Jeff Bezos in a Newsweek interview:

There’s a tendency, I think, for executives to think that the right course of action is to stick to the knitting—stick with what you’re good at. That may be a generally good rule, but the problem is the world changes out from under you if you’re not constantly adding to your skill set.

Markets are always shifting. Don’t think that anything is immune from innovation.

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My Ten Favorite Tweets – Week Ending 010110

From the home office in the future, where I’m currently reviewing all these 2010 predictions with a skeptical eye…

#1: How Companies Increase Innovation – WSJ.com #innovation http://post.ly/GubP

#2: RT @chuckfrey Amazon’s Jeff Bezos on two ways to approach customer-focused innovation: http://ow.ly/QIbl #innovation #strategy

#3: RT @briansolis Ideas Connect Us More than Relationships (video interview) http://bit.ly/8wPTzf

#4: Outstanding, detailed post on Enterprise 2.0 adoption from @ITSinsider & the @20adoption council: http://bit.ly/516Cv4 #e20

#5: Designing For Social Traction by Joshua Porter #design http://post.ly/GoE6

#6: Intellipedia anyone? “Preventing the Terrorist Attack: Massive Failure in Collaboration” http://bit.ly/6AQgPV #e20 #gov20

#7: 2010 Predictions from @jkuramot of Oracle AppsLab: http://bit.ly/7ainDr “Reputation will be all the rage in 2010.” > Agree

#8: RT @matthewemay Six years ago this USAToday essay by Jim Collins changed my entire view of the world. http://is.gd/5HPPu

#9: RT @davewiner: Anil Dash, an upper-caste Twitterer, explains to low-life scum like you and I, what it’s like up there. :-) http://r2.ly/yxbt

#10: My 5 1/2 y.o. son on why he didn’t see a friend’s kindergarten girl from the sister school in his coed class: “All the girls look alike.”

The Four Quadrants of Innovation: Disruptive vs Incremental

I recently wrote up a post, Most Dangerous Innovation Misperception – The Silver Bullet Approach. In it, I discussed the issue of organizations myopically focusing on only disruptive innovations to the exclusion of more incremental or sustaining innovations.

In doing more research on the subject, I began thinking about the dynamics that apply when a firm pursues different kinds of innovation. A post by Venkatesh Rao, Disruptive versus Radical Innovations, was very useful for distinguishing between disruptive and radical innovations.

Building on that, I wanted a framework for delineating innovations based on their technology and business impacts. Because they’re not necessarily the same. The four quadrants below describe the dynamics for innovations according to their technology and market impacts:

technology vs market innovations - disruptive or incrementalIn each quadrant, there are different rationales and issues that apply. Let’s take a look.

Existing Tech, Manage Existing Market

The lower left quadrant represent innovations that leverage existing technology, and service existing customers. This is every day innovation. The block-n-tackle innovation that keeps companies nimble and operating at rates above industry averages.

Example? See how Walmart improved the fuel efficiency of its vehicle fleet:

Wal-Mart has taken a number of steps, including the installation of diesel Auxiliary Power Units on all its trucks, and applying aerodynamic skirting. On the tire side, Wal-Mart is working with super single tires. and is testing nitrogen-filled tires and an automatic filling process to maintain constant tire air pressure.

Improving the customer experience is also a critical opportunity. In an era of social-media empowered customers impacting your brand, the consequences of failing to improve the customer experience are higher than ever.

But this quadrant is the one often pooh-poohed by many in innovation. I like the way PriceWaterhouseCoopers puts it in this blog post:

An unintended consequence of the Innovators Dilemma has been that companies have begun believing that unless they were pursuing a strategy of seeking disruptive innovations, they were somehow losing out.

Walmart’s efforts have paid off. The retailer has held relatively strong during the Great Recession, as seen in its stock price. And Toyota famously gathered over million ideas a year from its employees to emerge as a global leader in the automotive industry.

Existing Tech, Create New Market

In this quadrant, existing technology is leveraged to create a new revenue streams. This is the quadrant where the following phrase applies:

Good artists borrow. Great artists steal.

The simple application of a technology that serves one purpose toward a different purpose can be disruptive from a market perspective. It’s not a large technological leap. It’s the intelligent application of what’s already at hand.

Twitter is a great example. The technology itself is…simple. Web form. Subscription model. Limit to 140 characters. Yet it’s revolutionized the way people share and find information, causing Techcrunch’s MG Siegler to compare it to a modern day Walter Cronkite. All for a simple little web app. Here’s what WordPress founder Matt Mullenweg says about Twitter:

Whether the Twitter team intended it or not, they’ve built a killer and highly addictive reader platform with dozens of interesting UIs on top of it.

The thing with these innovations is that they are very much a market-determined disruption. This isn’t some sort of EUREKA! the moment the technology is rolled out of the labs. It takes the market to say that it’s disruptive.

Clayton Christensen (Innovator’s Dilemma) types of innovation will often fall in this quadrant. Existing technologies applied in new ways to address the lower end of the market.

Venkatesh Rao has a great perspective on this quadrant:

In fact, in most documented cases of disruption, the disruptive innovation was a minor/incremental change and well within the technical capabilities of the incumbent (and was often taken to market by a renegade spin off from the original company).

This quadrant is the best one for producing organic growth for companies. It has lower risk, but produces meaningful revenue growth.

Radical Tech, Create New Market

If any one quadrant defines the popular view of innovation, it’s this one. And that’s not without good reason. In the previous quadrant, existing technologies are applied to new markets. Well, existing technologies have to come from somewhere. That’s this quadrant.

This is the cool stuff that the press writes about. Check out AT&T’s Technology Showcase for a great example of some of these new technologies.

Amazon’s Jeff Bezos has done well in this quadrant. His latest innovation, the Kindle, is an example. It includes a new “electronic ink“. Ability to read text aloud. It’s incredibly thin profile.

And it’s paying off. Amazon reports that the Kindle set a new sales record this November. Which points to the Kindle as a strong new revenue stream down the road, and a new source of sales for Amazon’s book sales. A home run in this quadrant.

These types of innovations are important for maintaining the long-term growth rates of companies. They provide needed growth, replenishing changes in existing markets.

Which leads us to the final quadrant…

Radical Tech, Manage Existing Market

There are times a company’s business is under attack, and it needs to address changing behaviors in its market. Innovations in this quadrant share the high risk profile of the previous quadrant, but they have a defensive nature to them. They don’t seek to find new opportunities, they seek to address changes in customer behavior.

Hulu strikes me as an example of this. A joint venture of NBC, Fox and ABC, Hulu lets users view shows on computers. This initiative addresses the emerging market shift away from televisions to viewing on all sorts of devices. It’s a better answer for this shift than the music industry initially had for the proliferation of MP3 songs on various P2P sites.

Gary Hamel has noted the increasing volatility of markets across the globe. Customers have better access to information about new options, and are willing to shift their spending more quickly. With this dynamic, expect some increase in activity for innovations in this quadrant.

Companies Need a Portfolio of Innovation Opportunities

In a recent Accenture survey, 58% of executives said their organization is looking for the next silver bullet rather than pursuing a portfolio of opportunities. When I hear that, I think first of the upper right quadrant (radical tech, create new market). These types of innovations are incredibly important, and should be part of a company’s innovation efforts.

But there’s really a good basis for expanding that view to look at the other types of innovation: technology vs. market, disruptive vs incremental.

I’m @bhc3 on Twitter, and I’m a Senior Consultant for HYPE Innovation.

Kindle Breaks Record for Sales in a Single Month During November

My Ten Favorite Tweets – Week Ending 072409

From the home office in Sacramento, CA…

#1: AMZN CTO: RT @werner Was asked for definition of real-time web: to go f/ innovator to homophobic censor or book-burning nazi in 60 seconds.

#2: Reading: A First Look at SharePoint 2010 http://bit.ly/15y1tT Includes a great visual mapping of SharePoint 2007 to 2010

#3: Innovating innovation: An Interview with Scott Anthony of Innosight http://bit.ly/5pXbb Disruptive #innovation needs senior mgt support

#4: RT @VMaryAbraham Host a Failure Party http://tinyurl.com/oh99zc #innovation #KM Celebrate the journey, not just the destination

#5: Gary Hamel to keynote Spigit’s Customer Summit Aug 13-14, 2009 http://bit.ly/4wRljR #innovation

#6: The Potato as Disruptive Innovation http://bit.ly/4gqzQa “the potato explains 22% of the observed post-1700 increase in population growth”

#7: I generally avoid following the celebrities. But I’m so impressed with @KevinSpacey that I had to follow. His films and acting rock.

#8: RT @mattcutts A Google easter egg for people who know what recursion is: http://bit.ly/URa8U :)

#9: Rick Astley is playing on the radio here. We’re all being rick rolled.

#10: Working with my son on his Snap Circuits Jr electronics kit http://bit.ly/bRsJQ He wants to build his own nightlight.

My Ten Favorite Tweets – Week Ending 020609

From the home office in Victoria, Australia…

#1: Interesting convo w/ colleague. Is there any risk to tweeting that you’re traveling on vacation? Burglars searching for such tweets?

#2: Guy was turned down for a job because he switched majors his freshman year of college. Say what? Details: http://bit.ly/23yHBT

#3: FriendFeed continues to roll out the powerful features. Latest? Much more granular search options, very helpful: http://bit.ly/VNYX

#4: I’m impressed w/ Yammer’s hustle. If you’re doing an internal preso on it, they’ll help you with the preso. Smart. E.g.: http://bit.ly/PR1A

#5: RT @beccayoungs I really do think the Amazon Kindle will be a game-changer. Check this out – Kindle to be a $1B product http://tr.im/eflz

#6: RT @barconati Oh no! Yahoo briefcase is closing. Believe it or not I still use it. More out of habit than anything else http://tr.im/e88z

#7: Mike Gotta on the rise of employee social profiles inside companies: http://bit.ly/135Vz Benefits and advice w/ nice Connectbeam shout-out

#8: Check out http://www.socialwhois.com/ Lets you search for people on based on keywords in their lifestreams. Very cool.

#9: RT @lehawes w00t! I made the Wall St. Journal today! Page A11 in print edition or online at http://bit.ly/iRcH

#10: After the WSJ coverage…@lehawes blogs about being included in a recent WSJ article: Taken Out of Context http://bit.ly/17aRy

The Migration of Web Techniques to In-Store Retail Practices

Via ralphbijker on Flickr

Via ralphbijker on Flickr

Think about the companies doing the most technologically advanced stuff. Amazon. Google.

Grocery stores.

Say what…? The place where oranges sit in piles in the produce section. Boxes of cereal lines the aisles. The frigid ice cream aisle.

Well, they’re not in the league of Google and Amazon. But grocers are more than those aisles of food and ceilings of fluorescent lights you see. Two trends in the industry borrow heavily from the advancements on the Web:

  1. Website optimization
  2. Recommendations

I’m not talking about monitors with web pages inside stores. I mean the shopping experience has been affected by these developments. Here’s how.

Website Optimization => Store Layout and Merchandising

E-commerce sites live and die by their conversion rates. A key piece of the conversion rate puzzle is effective navigation and presentation of items to site visitors. One company that helps with that is  Tealeaf, which records and analyzes visitor behavior to help site owners optimize conversions and return visits.

In a physical space, you can’t record people’s clicks and actions. Or can you?

As reported in a recent Economist article, retailers are starting to video record shoppers’ behavior in the aisles. For instance, here’s how one supermarket used technology provided VideoMining to understand visitor behavior in its juice section:

Another study in a supermarket some 12% of people spent 90 seconds looking at juices, studying the labels but not selecting any. In supermarket decision-making time, that is forever. This implies that shoppers are very interested in juices as a healthy alternative to carbonated drinks, but are not sure which to buy. So there is a lot of scope for persuasion.

These are exactly the kind of metrics that e-commerce sites track to improve their conversion rates. Use of cameras in-store to do the same thing is analogous to tracking visitors to your website.

Personalized Recommendations

Amazon.com really led the movement to provide effective recommendations to existing customers. One report I’ve seen says that Amazon derives 35% of its sales from these recommendations. Amazon’s recommendations are generated from your shopping history, compared to others via collaborative filtering. The success of these recommendations has inspired others to build recommendation engine services, including Aggregate Knowledge, Baynote, MyBuys, RichRelevance and others.

The same thing is happening in-store as well. You know that loyalty card you present to your grocer to get discounts? It’s used to record your shopping history. Historically, grocers have done little with that information. It was more of a device to keep you coming back to the store.

But in the past few years, grocers have been getting hip to the idea that their customers’ shopping history can be used to personalize the shopping experience.

Once, I was product manager for just such a system, called SmartShop. Pay By Touch’s SmartShop used a Bayesian model to compare your purchases against those of other shoppers, and determine whether you exhibited stronger or weaker preferences for a category or product than the overall average. A set of 10 personalized item discounts were then selected for you based on your specific purchase preferences.

On a website, returning customers are presented with a set of recommendations as they shop. In-store, what’s the analog? Kiosks. Kiosks are the in-store interaction basis with customers. SmartShop notified you of discounts via a print-out from a kiosk at the front of the store. This was key – get you the discounts right at the point of decision, when you’re shopping. Not unlike e-commerce recommendations.

Prior to Pay By Touch’s demise, SmartShop was getting good traction among grocers, who were looking for ways to increase basket size, increase loyalty and differentiate themselves. And it wasn’t just SmartShop. Price Chopper and Ukrops use a recommendation system from Entry Point Communications. UK-based Tesco is the granddaddy of personalized recommendations, provided through Dunnhumby.

Teaching Old Dogs New Tricks

While e-commerce benefits from being all-digital and various identification mechanisms, grocery historically lacked these. But that’s changing. Retailer have picked up the best practices of their online brethren. Things are now much more measurable and personalization is no longer the province of the online players.

Looking forward to grocers introducing Twitter into the shopping experience…

*****

For reference, here’s a white paper I wrote about SmartShop when I was at Pay By Touch:

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Supply-Demand Curves for Attention

The basic ideas behind the Attention Economy are simple. Such an economy facilitates a marketplace where consumers agree to receives services in exchange for their attention.

Alex Iskold, ReadWriteWeb, The Attention Economy: An Overview

The attention economy. It’s a natural evolution of our ever-growing thirst for information, and the easier means to create it. It’s everywhere, and it’s not going anywhere. The democratization of content production, the endless array of choices for consumption.

In Alex’s post, he listed four attention services, as they relate to e-commerce: alerts, news, search, shopping.  In the world of information, I focus on three use cases for the consumption of information:

  1. Search = you have a specific need now
  2. Serendipity = you happen across useful information
  3. Notifications = you’re tracking specific areas of interest

I’ve previously talked about these three use cases. In a post over on the Connectbeam blog, I wrote a longer post about the supply demand curves for content in the Attention Economy. What are the different ways to increase share of mind for workers’ contributions, in the context of those three consumption use cases.

The chart below is from that post. It charts the content demand curves for search, serendipity and notifications.

micro-economies-of-attention-3-demand-curves-for-content

Following the blue dotted line…

  • For a given quantity of user generated content, people are willing to invest more attention on Search than on Notifications or Serendipity
  • For a given “price” of attention, people will consume more content via Search than for Notifications or Serendipity

Search has always been a primary use case. Google leveraged the power of that attention to dominate online ads.

Serendipity is relatively new entry in the world of consumption. Putting content in front of someone, content that they had not expressed any prior interest in. A lot of the e-commerce recommendation systems are built on this premise, such as Amazon.com’s recommendations. And companies like Aggregate Knowledge put related content in front of readers of media websites.

Notifications are content you have expressed a prior interest in, but don’t have an acute, immediate need for like you do with Search. I use the Enterprise 2.0 Room on FriendFeed for this purpose.

The demand curves above have two important qualities that differentiate them:

  • Where they fall in relation to each other on the X and Y axes
  • Their curves

As you can see with how I’ve drawn them, Search and Notifications are still the best way to command someone’s attention. Search = relevance + need. Notifications = relevance.

Serendipity commands less attention, but it can have the property of not requiring opt-in by a user. Which means you can put a lot of content in front of users, and some percentage of it will be useful. The risk is that a site overdoes it, and dumps too much Serendipitous-type content in front of users. That’s a good way to drive them away because they have to put too much attention on what they’re seeing. Hence the Serendipity curve. If you demand too much attention, you will greatly reduce the amount of content consumed. Aggregate Knowledge typically puts a limited number of recommendations in front of readers.

On the Connectbeam blog post, I connect these subjects to employee adoption of social software. Check it out if that’s an area of interest for you.

*****

See this post on FriendFeed: http://friendfeed.com/search?q=%22Supply-Demand+Curves+for+Attention%22&who=everyone

Improving Search and Discovery: My Explicit Is Your Implicit

Two recent posts on the implicit web provide two different takes. They provide good context for the implicit web.Richard MacManus of ReadWriteWeb asks, Aggregate Knowledge’s Content Discovery – How Good is it, Really? Aggregate Knowledge runs a large-scale wisdom of crowds application, suggesting content for readers of a given article based on what others also viewed. For instance, on the Business Week site, you might be reading an article about the Apple iPod. Next to the article are the articles that readers of the Apple iPod article also viewed. MacManus finds the Aggregate Knowledge recommendations to be not very relevant. The recommended articles had no relationship to Apple or the iPod.

Over at CenterNetworks, Allen Stern writes that Toluu Helps You Like What Your Friends Like. Toluu lets you import your RSS feeds and friends who have also uploaded their RSS feeds. It applies some secret sauce to analyze your friends’ feeds and create recommendations for you. Stern finds the service a bit boring, as all the recommendations based on his friends’ feeds were the same.

In the case of Aggregate Knowledge, the recommendations were based on too wide a pipe. The implicit actions – clicks by everybody – led to irrelevant results because you essentially the most popular items. In the case Toluu, the recommendations were based on too narrow a pipe. The common perspectives of like-minded friends meant the recommendations were too homogeneous.

Both of these companies leverage the activities of others to deliver recommendations. The actions of others are the implicit activities used to improve search and discovery. A great, familiar example of applying implicit activities is Google search. Google analyzes links among websites and clicks in response to search results. Those links and clicks are the implicit actions that fuel its search relevance.

Which leads to an important consideration about implicit activities. You need a lot of explicit activity to have implicit activity.

Huh?

That’s right. Implicit activities don’t exist in a vacuum. They start life as the explicit actions of somebody. This is a point that Harvard’s Andrew McAfee makes in a recent post.

Let’s take this thought a step further. Not all explicit actions are created equal. There are those that occur “in-the-flow” and those that occur “above-the-flow”, a smart concept described by Michael Idinopulos. In-the-flow are those actions that are part of the normal course of consumer activities, while above-the-flow takes an extra step by the user. A couple examples describe this further:

  • In-the-flow: clicks, purchases, bookmarks
  • Above-the-flow: tags, links, import of friends

Above-the-flow actions are hard to elicit from consumers. There needs to be something in it for them. Websites that require a majority of above-the-flow actions will find themselves challenged to grow quickly. They better have something really good to offer (such as Amazon.com’s purchase experience). Otherwise, the website should be able to survive on the participation of just a few users to provide value to the majority (e.g. YouTube).

So with all that in mind, let’s look at a few companies with actual or potential uses of the explicit-implicit duality:

Google Search

In an interview with VentureBeat, Google VP Marissa Mayer talks about two different forms of social search:

  1. Users label search results and share labels with friends. This labeling becomes the implicit activity that helps improve search results for others. This model is way too above-the-flow. Labeling? Sharing with friends? After experimenting with this, Mayer states that “overall the annotation model needs to evolve.” Not surprising.
  2. Google looks at your in-the-flow activity of emailing friends (via Gmail). It then marries the search histories of your most frequent email contacts to subtly alter the search result rankings. All of this implicit activity is derived from in-the-flow activities. For searches on specific topics, the more narrow implicit activity pipe of just your Gmail contacts is an interesting idea.

ThisNext

ThisNext is a platform for users to build out their own product recommendations. They find products on the web, grab an image, and rate and write about the product. Power users emerge as style mavens. The site is open to non-members for searching and browsing of products.

ThisNext probably relies a bit too heavily on above-the-flow activities. It takes a lot of work to find products, add them to your list of products and provide reviews. It also suffers from being a bit too wide a pipe in that there’s a lot of people whose recommendations I wouldn’t trust. How do I know who to trust on ThisNext?

Amazon Grapevine

Amazon, on the other hand, has a leg up in this sort of model. First, its recommendations are built on a high level of in-the-flow activities – users purchasing things they need. This is the “people who bought this also bought that” recommendation model. Rather than depend on the product whims of individuals, it uses good ol’ sales numbers (plus some secret sauce as well) for recommendations. This is a form of collaborative filtering.

Amazon Grapevine is a way of setting the pipe for implicit activities. The explicit activity is the review or rating. These activities are fed to your friends on Facebook. One possibility for Amazon down the road is to use the built-up reviews and ratings of your friends to influence the recommendations it provides on its website. Such a model would require some above-the-flow actions – add the Grapevine application, maintain your account and connections on Facebook. But these aren’t that onerous; the Facebook social network continues to be an explicit activity that has high value for individuals.

Yahoo Search

Yahoo bought the bookmarking and tag service del.icio.us back in 2005. It’s hard to know what, if anything, they’ve done with that service. But one intriguing possibility was hinted at in this TechCrunch post. The del.icio.us activity associated with a given web page is integrated into the search results. Yahoo search results would be ranked not just on links and previous clicks, but also on the number of times the web page had been bookmarked on del.icio.us. And, the tags associated to the website would be displayed, giving additional context to the site and enabling a user to click on the tags to see what other sites share similar characteristics.

This takes an above-the-flow activity performed by a relative few – bookmarking and tagging on del.icio.us – and turns it into implicit activity that helps a larger number of users. But with the Microsoft bid, who knows whether something like this could happen.

The use of implicit activity is a powerful basis to help users find content. Just don’t burden your users with too much of the wrong kind of explicit activity to get there. Two factors to consider in the use of implicit activity:

  1. How wide is the pipe of implicit activities?
  2. How much above-the-flow vs. in-the-flow activity is required?

Facebook Beacon Is Dead. Long Live Amazon Grapevine.

Amazon has just come out with two new Facebook apps, as reported by Erick Schonfeld on TechCrunch. One is Amazon Giver, which lets friends share wish lists. The other is Amazon Grapevine, which lets you broadcast your activities on Amazon back to the Facebook newsfeed.

Pardon me…but isn’t that the basis of Facebook Beacon? Well, sort of. There are a few differences.

Amazon made this completely opt-in, which differs from the opt-out philosophy of Beacon. Also, product purchases are not included in Grapevine, but they were an important part of Beacon.

Personally, Beacon doesn’t bother me that much. I did not experience the early versions of Beacon with the too-fast notice that popped up on e-tailers’ sites. No accidentally revealing an engagement ring purchase. But there are times a purchase says something about you.

In fact, I think the idea of sharing your purchases with your friends has a lot of interesting potential. I can think of three different reasons people would share purchase information with friends and check out what their friends have purchased:

  1. Self-expression
  2. Product discovery
  3. Friends’ reviews

I’ve mapped those reasons to several different retail sectors.

  • Apparel = self-expression
  • Computer Hardware/Software = friends’ reviews
  • Consumer Electronics = friends’ reviews, self-expression
  • Home & Garden = self-expression, friends’ reviews
  • Sporting Goods = self-expression, friends’ reviews
  • Baby Products = product discovery, friends’ reviews

For instance, I think broadcasting your Apparel purchases is more a form of self-expression. People’s fashion tastes are an extension of themselves. Participation in some sort of Beacon-like program for Consumer Electronics, on the other hand, would be a chance to provide reviews to friends and read the reviews of your friends. And Baby Products would have a lot of discovery and reviews. See what your friends have purchased for their infants. Anyone who is a first-time parent knows the challenges of figuring out what to buy.

But, Beacon is still controversial, and Amazon doesn’t go as far as broadcasting purchases. So for now, we broadcast our ratings and reviews. This is pretty good. I can learn a lot from that.

The only problem is, the opportunities to share this way are still quite limited. Not too many e-tailers are doing this yet. However, Amazon has a rich history of driving innovation in e-tail. It was the early leader in e-tail. It was among the first to set up an affiliate program (Amazon Associates). It pioneered product recommendations.

So now it’s experimenting with the sharing of product-related information on social networks. Probably won’t be long before other e-tailers get on board.

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