Category: programmableweb

The useful convergence of data

I have only one prediction for 2008. I think we’re finally about to see the useful combination of the 4 W’s – Who, What, Where, and When.

Marc Davis has done some interesting research in this area at Yahoo!, and Bradley Horowitz articulated how he sees the future of this space unfolding in a BBC article in June ’07:

“We do a great job as a culture of “when”. Using GMT I can say this particular moment in time and we have a great consensus about what that means…We also do a very good job of “where” – with GPS we have latitude and longitude and can specify a precise location on the planet…The remaining two Ws – we are not doing a great job of.”

I’d argue that the social networks are now really honing in on “who”, and despite having few open standards for “what” data (other than UPC) there is no shortage of “what” data amongst all the “what” providers. Every product vendor has their own version of a product identifier or serial number (such as Amazon’s ASIN, for example).

We’ve seen a lot of online services solving problems in these areas either by isolating specific pieces of data or combining the data in specific ways. But nobody has yet integrated all 4 in a meaningful way.


Jeff Jarvis’ insightful post on social airlines starts to show how these concepts might form in all kinds of markets. When you’re traveling it makes a lot of sense to tap into “who” data to create compelling experiences that will benefit everyone:

“

  • At the simplest level, we could connect while in the air to set up shared cab rides once we land, saving passengers a fortune.
  • We can ask our fellow passengers who live in or frequently visit a destination for their recommendations for restaurants, things to do, ways to get around.
  • We can play games.
  • What if you chose to fly on one airline vs. another because you knew and liked the people better? What if the airline’s brand became its passengers?
  • Imagine if on this onboard social network, you could find people you want to meet – people in the same business going to the same conference, people of similar interests, future husbands and wives – and you can rendezvous in the lounge.
  • The airline can set up an auction marketplace for at least some of the seats: What’s it worth for you to fly to Berlin next Wednesday?

“

Carrying the theme to retail markets, you can imagine that you will walk into H&M and discover that one of your first-degree contacts recently bought the same shirt you were about to purchase. You buy a different one instead. Or people who usually buy the same hair conditioner as you at the Walgreen’s you’re in now are switching to a different hair conditioner this month. Though this wouldn’t help someone like me who has no hair to condition.

Similarly, you can imagine that marketing messages could actually become useful in addition to being relevant. If CostCo would tell me which of the products I often buy are on sale as I’m shopping, or which of the products I’m likely to need given what they know about how much I buy of what and when, then my loyalty there is going to shoot through the roof. They may even be able to identify that I’m likely buying milk elsewhere and give me a one-time coupon for CostCo milk.

Bradley sees it playing out on the phone, too:

“On my phone I see prices for a can of soup in my neighbourhood. It resolves not only that particular can of soup but knows who I am, where I am and where I live and helps me make an intelligent decision about whether or not it is a fair price.

It has to be transparent and it has to be easy because I am not going to invest a lot of effort or time to save 13 cents.”

It may be unrealistic to expect that this trend will explode in 2008, but I expect it to at least appear in a number of places and inspire future implementations as a result. What I’m sure we will see in 2008 is dramatic growth in the behind-the-scenes work that will make this happen, such as the development and customization of CRM-like systems.

Lots of companies have danced around these ideas for years, but I think the ideas and the technologies are finally ready to create something real, something very powerful.

Photo: SophieMuc

The Internet’s secret sauce: surfacing coincidence

What is it that makes my favorite online services so compelling? I’m talking about the whole family of services that includes Dopplr, Wesabe, Twitter, Flickr, and del.icio.us among others.

I find it interesting that people don’t generally refer to any of these as “web sites”. They are “services”.

I was fortunate enough to spend some time with Dopplr’s Matt Biddulph and Matt Jones last week while in London where they described the architecture of what they’ve built in terms of connected data keys. The job of Dopplr, Mr. Jones said, was to “surface coincidence”.

I think that term slipped out accidentally, but I love it. What does it mean to “surface coincidence”?

It starts by enabling people to manufacture the circumstances by which coincidence becomes at least meaningful if not actually useful. Or, as Jon Udell put it years ago now when comparing Internet data signals to cellular biology:

“It looks like serendipity, and in a way it is, but it’s manufactured serendipity.”

All these services allow me to manage fragments of my life without requiring burdensome tasks. They all let me take my data wherever I want. They all enhance my data by connecting it to more data. They all make my data relevant in the context of a larger community.

When my life fragments are managed by an intelligent service, then that service can make observations about my data on my behalf.

Dopplr can show me when a distant friend will be near and vice versa. Twitter can show me what my friends are doing right now. Wesabe can show me what others have learned about saving money at the places where I spend my money. Among many other things Flickr can show me how to look differently at the things I see when I take photos. And del.icio.us can show me things that my friends are reading every day.

There are many many behaviors both implicit and explicit that could be managed using this formula or what is starting to look like a successful formula, anyhow. Someone could capture, manage and enhance the things that I find funny, the things I hate, the things at home I’m trying to get rid of, the things I accomplished at work today, the political issues I support, etc.

But just collecting, managing and enhancing my life fragments isn’t enough. And I think what Matt Jones said is a really important part of how you make data come to life.

You can make information accessible and even fun. You can make the vast pool feel manageable and usable. You can make people feel connected.

And when you can create meaning in people’s lives, you create deep loyalty. That loyalty can be the foundation of larger businesses powered by advertising or subscriptions or affiliate networks or whatever.

The result of surfacing coincidence is a meaningful action. And those actions are where business value is created.

Wikipedia defines coincidence as follows:

“Coincidence is the noteworthy alignment of two or more events or circumstances without obvious causal connection.”

This is, of course, similar and related to the definition of serendipity:

“Serendipity is the effect by which one accidentally discovers something fortunate, especially while looking for something else entirely.”

You might say that this is a criteria against which any new online service should be measured. Though it’s probably so core to getting things right that every other consideration in building a new online service needs to support it.

It’s probably THE criteria.

Where are the best answers to business questions?

Reid Hoffman reminded me the other day that I needed to take a look at the LinkedIn Answers service, the peer-to-peer Q&A service for business. It obviously emulates much of the Yahoo! Answers product, particularly the user experience, so I thought I’d do a little test.


It surprised me in a way that I didn’t expect…

I wondered what would happen if I posted the same question in both LinkedIn Answers and Yahoo! Answers. Of course, I posted a work-related question. This would make the test as nearly apples-to-apples as it could be.

I’ve been wanting to know more about the API market, size, share, segmentation, and all that good market data that defines an industry. The web services market is pretty loosely defined still, and I want to know where the best research is. So here’s what I asked on both sites:

“Where is the best market research on APIs and web services?”

LinkedIn:
– 2 answers within a day
– Both pointed to John Musser’s ProgrammableWeb
– The 3rd post came in 5 days later listing a few relevant blogs in addition to ProgrammableWeb

Yahoo!:
– 2 answers in less than an hour
– The 1st answers also pointed to ProgrammableWeb
– The 2nd listed 3 more sites that were sort of relevant

I kind of expected this behavior, but I certainly didn’t expect that I would get the same answer in the end. Yes, ProgrammableWeb is very good. It’s a highly relevant answer to my question, though not exactly the answer I was hoping for.

In some ways, I expected LinkedIn to give me better answers given both the focus and also how broad the Yahoo! Answers demographic must be, but this shows how participatory media can reach incredibly deep into the micro niche even when it’s a mass consumer service.

So, who won this test? I’m inclined to believe that speed matters more, particularly if the answers turn out to be the same. What do you think?