Deliberate Ambiguity

Product Messaging Basics

Even assuming a world of conversational marketing where the masses shape your message, it's important to seed that conversation with something coherent.  A tight message shows why your solution is unique and useful, what your competitive position is, and tells users what problem you are going to solve for them.

Messaging discussions tend to fall on two sides of a spectrum.  On one hand, nebulous high-level documents, endless wordsmithing of simple phrases, and jargon can create a jumbled, confusing message.  On the other hand, slapping a few sentences together in a press release can sound unfocused and unclear.

A product manager's job doesn't end with creating a great product.  It's also our job to tell the world why they should care.  So what's the best way to create a messaging document?  And what should the end product look like?  Every company, product, and situation, but here's a few guidelines that have helped me:

1. Stick to basics - One of the classic formulations of messaging goes something like: "For [target user], who needs [reason to buy your product], [product name] is a [category] which [benefit], unlike [main competitor], which [differntiation]."  You should be able to rattle off something like this statement about your product without thinking twice.
2. Don't spend all of your time fixing words - Don't confuse messaging work with copy editing.  If you've a clear message conceptually, then the words can always be honed later.
3. Find a great template  - Whenever I do messaging, I e-mail a few of my marketing colleagues at other companies to see what they're using.  My favorite template is the Marketecture from Practical Product Management.  It starts off with a problem and solution statement, which helps you to frame how you talk about your product.  Also, the product statement is supposed to be short (under 25 words!) and I recommend making that an absolute upper bound.
4. Run it past someone non-technical - this is certainly true in the consumer space, but even in enterprise software.  I realized there was a problem with "natural language search" when I had to explain it to my well-educated hair artist.  Powerset's About page now contains almost no technical jargon (and I'm happy to entertain ideas about how to make it better).
5. Avoid meaningless words - This is a corrolary to the above.  Even if you think a word or phrase has meaning (e.g. "best of breed" or "highly scalable") think about a simpler way to say it.
6. Write something functional - This could be your About page, your press release, or even try your hand at the article you'd like someone from the press to write about your product.  Some might argue that you need your messaging in place before you effectively write a press release, but I think the two are informed by each other.

Anything I'm missing?  Anyone else have experience in creating a great messaging document?

Falken's Maze Podcast v2 with Andraz Tori

Podcasting is fun, especially now that I have an iPod shuffle!  Falken's Maze, a collaboration of me, Josh Dillworth, and Carla Thompson, is happy to present our second podcast, with a third to follow soon.

This edition features Adraz Tori of Zemanta talking about what Zemanta currently does, the technology underlying it, where Zemanta might go in the future, and his thoughts on the semantic web, in general.

We're looking for more guests connected with the Semantic Web, so hit me up if you're interested.

Liberty Salon with David Boaz of Cato

Last November, I threw a party for Bob Barr, who is now the Libertarian Presidential Candidate.  Last weekend, I hosted another party for Wayne Allyn Root, the Libertarian VP Candidate.  Throwing parties is fun, so next Tuesday, July 7, I'm going to host a fundraiser for the David Boaz, Executive Vice President for the Cato Institute and one of the leaders of the libertarian movement.  Unlike my other parties, we're requiring a $100 minimum donation to Cato to attend.  Given all of the talk about "change" in this election from NObama, it's important that we liberty-loving folks spread the message about the right kind of change.  Cato is a leading policy think-tank and often gets air time on national TV.

If you'd like to come, make a donation (and print out your receipt) and RSVP at the event's Upcoming.org page and the event's Facebook page.

I'm going to be doing these once a quarter with a prominent figure in the libertarian movement, so if you have to miss this one, look for more!

Microset. . . Powersoft? Whatever, Powerset is acquired

I must be lucky (at least, that's what I keep telling myself).  In December '07, SideStep was acquired by Kayak (I worked for SideStep a few years ago and launched SideStep.com in January '05).  Today, I'm excited to announce that my current employer, Powerset, was acquired by Microsoft.

As I'm sitting here on briefing calls with reporters, I'm just in awe.  I joined Powerset because I had big dreams about transforming search, but I've always been realistic: most big dreams like that just don't pan out.  Another round (or two?) of funding is seductive because we'd have the chance to be the next Google or Microsoft, but the risk is incredibly high.

That's why I'm so freakin' stoked to be teaming up with Microsoft.  Suddenly, concerns about scale, spam, capital expenditures, runway, servers, marketing, computation, distribution, etc. aren't our concern.  Powerset can focus on what we do best: creating a phenomenal product based on deep scientific advances.

Much more news to come soon, but for now, I'm off to finish press briefings and then to celebrate.

Finding Powerset Factz

Obviously, I don't need any more Powerset t-shirts, but I thought I'd show off some of the fun queries that I found and talk a little bit about the process I went through to find good queries.

Some knowledge about how Factz show up are helpful in finding them.  First, Factz are currently very simple "triples" of subject:verb:object. So, if you start asking questions with prepositional phrases (Who starred in Six Degrees of Separation?), a when (when did Mount St. Helens erupt?), or any other construction, you will get search results, but no Factz results.  Also, Factz most often return about popular subjects, because they are written about in many places in Wikipedia, not just their own Wikipedia article.

With that out of the way, let's look at an example.  I like chess, so a good starting point is a chess query: bobby fischer.

The Factz are grouped by relation and, even though by default Powerset only shows three results, there over 100 relations featuring Bobby Fischer as the subject.  Just click "more" to see all of the relations. 

The third relation is about Bobby Fischer defeating, which in turn suggests a simple question: who did bobby fischer defeat? (yes, I know that it should be "whom")

Though this isn't a complete list, it's a list of all of the sentences in Wikipedia that have Bobby Fischer as the subject for the verb defeat.  So, one way to get a good Factz query is to type in the name of a topic, look at the top relations, and then turn that relationship into a question.

However, sometimes Factz can also be used to get a list of subjects.  In this case, you can flip the question around to see who defeated Bobby Fischer.

Another good general principle about great Factz queries is thinking about a question that will generate a long list.  I watched The Incredibles for the first time last night.  This got me thinking about the query, who saves the world?

If you click "more" you'll see that this is a really long list with some that are expected (lots of heros saved the world), logical (Christ), funny (Godzilla), and wrong (Nova Scotia).  Note that Powerset always shows the sentence from which the Factz were derived, allowing you to double check whether the assertion is true.

Sometimes Factz can reveal things that are either not true or "almost" true.  For the query, who invaded Mexico, I was curious about Japan, since that bit of history evaded my memory.  Sure enough, it wasn't my memory that was deficient, but the sentence was: "On June 3, 1942, Patton believed the Japanese were on a course to invade Mexico."  Powermouse ignores these types of modalities and negations, even though Powerset indexes them properly.  We do this because we err on the side of giving users too much information, rather than too little.

Hopefully this will help you find some good Factz for Powerset's t-shirt contest.  If you have any questions, you can comment on my blog or drop us a line at feedback@powerset.com

Introducing: Falken's Maze

Carla Thomson, Josh Dilworth, and I are going to start regularly recording a podcast.  Since we all share a fetish for semantic technology companies (a better name for said group forthcoming) and we all like to talk and we all like to talk with each other, what better idea than a podcast?  We've called it Falken's Maze, after the elusive game from WarGames.  Given that it was our first stab, it might be a little bit long and rambley, but we'll try to reign that in for future episodes.  And, if you know of any experts in this "semantic technology" field, send 'em our way.

The Rising Stars of the Semantic Web (SemTech2008 Keynote Panel)

Here's my verbatim-ish transcription of the keynote at the Semantic Technology Conference in San Jose: The Rising Stars of the Semantic Web.

Powerset (Dr. Barney Pell, founder & CTO)

Powerset is organizing and indexing content from Wikipedia and Freebase.  First query is Henry VIII.  For topical queries, Powerset provides a dossier of.  Factz: automatically extracted triples from across Wikipedia articles.  For a famous person like Henry VIII, there are assertions all over Wikipedia about Henry VIII.  Second query: what did the fda approve?  Powerset doesn’t have any special domain knowledge (English history or medicine) that allows it to pull out information from text.  Search results are taking advantage of both semantic features and traditional search features. Now off to articles: Tim Berners-Lee.  Powerset republishes Wikipedia articles with some additional features, like the Article Ouline that follows you as you browse.  By looking at the Explore Factz, you can see all of the concepts in the page and the relations.  Clicking on a concept shows all of the Factz in the Article Outline.  Final query: what did tom cruise star in?  An NL query translated into a Freebase query, which shows all of the movies that Tom Cruise starred in. 

AdaptiveBlue (Alex Iskold, founder & CEO)

A network on top of the existing Web.   Basic bits of the web are understood by AB’s technology, e.g. books, stocks, addresses, etc.  Stop visualizing the Web as a collection of pages but as a collection of things.  For example, "The Kite Runner" may show up on both Amazon and Barnes&Noble.com, but they both refer to the same book.  Why is this different?  Bringing semantics to the Web as it exists now, not creating a new semantic Web.  This allows the content to evolve with the Web itself.  Two primary products are BlueOrganizer (a browser plug-in) and SmartLinks (semantic improvements to links on your blog).

Twine by Radar Networks (Nova Spivack, founder & CEO)

Actually this was a video made by a high school student who is now an intern at Radar Networks.  The video is to the tune of Radar Love and a fast-paced tour through Twine.  Unfortunately, there was so much going on that my limited human brain couldn't absorb it all: making new Twines, e-mailing things to a Twine, adding Google videos to Twine, history of video games, oh my!  Kids these days.  They just click them mice and keyboardz so fast.  Video ends with "Twine: How have we lived without it."

Talis (Ian Davis, CTO and creator of RSS 1.0)

Privately owned, well-established and innovative software company that's been around for 40 years,> all of the other companies on the panel combined.  Talis wants to be critical infrastructure to the semantic Web, such as applications for libraries, education, learning and community.  

Stealth-Company.com (Tom Gruber, CTO and founder)

No particular product to pitch ('cause they're still a stealth company).  The killer app isn't search, maps, e-mail, videos, etc.  It's intelligent design that brings together all of that cool stuff.  The iPhone is an example of this.  The killer app is your life (online): applying the best of the internet technologies (intelligently) to your life.  It's closer than we think (um gottes willen).  Paradigm shift.  Paradigm 1 is the hyperlink (user finds links, computer connects).  Paradigm 2 is the portal (user chooses your channels, computer delivers).  Paradigm 3 is the search engine (user states the query, computer finds relevant documents).  But why do we need to find the "magic" words to find what we want?  The next level will anticipate our needs.  I'm anticipating Stealth Company!

Q&A Session

• "What is the best opportunity that would get you a quote from Carla Thompson in the New York Times"
• • Nova - unsexy=a store of trillions of triples  sexy=x-rated "sementic" application
  • Alex - intersection of iPhone and the semantic Web, i.e. an application that understands your contexts as you move around
  • Tom - "the interface" companies need to address basic human needs.
  • Ian - similar answer to above.  Concrete example: something around travel.
  • Barney - search advertising and publishing.
• "Once you get Carla's attention, what do you do next.  How do you get to Gartner, Jupiter, and Forrester to notice?"
• • Alex - 2008 is the year of the semantic web, with or without Garner. 
  • Barney - "I think it's perfectly adequate that Guidewire is here: we don't need Gartner."  A big question is: what is the category that we're creating?  For example, what happens when we're able to join different pieces of content. . . new interface paradigms. . . new ways of consuming information. 2 or 3 categories will be created by the time of this conference next year.  "This conference next year will be twice the size and half of the companies will be consumer companies."
  • Nova - these firms don't think of "semantic web" as a space.  They just want to know how it's going to help the categories that they already track.  Maybe the name "semantic web" isn't really a good term anyway, since there are so many different companies, products, and underlying technologies.  Big analysts are playing catch-up.  The people in this room should define the category and educate the market.

Whew!  That was fun :)

Report from SemTech 2008 & the SD Forum Semantic Web SIG

Carla already did a great writeup of the panel I was on yesterday, so I won't bother taping out my disjointed thoughts.  However, I was at the SD Forum Semantic Web SIG panel last night (hosted at the Semantic Technology Conference) entitled, Will Semantics Give Web Search a Face Lift.

A common theme at this conference seems to be on the semantics of "semantic," and I found the problem to be especially apparent on this panel.  Oddly enough, there were no demos, but here's a summary of the panelists' opinions.  Consider the following:

• Healthline (Dr. AJ Chen) - since Dr. Chen was moderating, his brief slides focused on what a semantic search solution looks like under the hood.  Specifically, Healthline has health-specific ontologies that they're using for refinement, improved results, and improved ads.  Though I think Healthline's solution is very intersting, this is a pretty much the standard ontology implementation for vertical search companies. Semantic web = vertical ontologies used in a vertical domain.
• Google (Dr. Fernando Pereira) - Dr. Pereira seemed to have been sufficiently brainwashed by Google's Borg culture.  Though he admitted that Google is looking into next-generation technologies, his slides were a laundry list of why-not reasons: lexical information always lags behind real world usage, ontologies are messy, categorization schemes are difficult (impossible?) to create, annotations are noisy and potential spam channels. He cited utilitarian philosophy as Google's mantra: the greatest good for the greatest number of people.  Semantic web = interesting ideas, but I don't care unless it shows a marked improvement in horizontal results and can scale immediately to the entire Web.
• Yahoo (Dr. Peter Mika) - this talk was the closest to the standard W3C version of the Semantic Web.  Through Search Monkey, Yahoo is enabling content publishers to produce rich abstracts in their search results.  The idea is to provide a better user experience in search results, allowing users to get from "do to done faster."  Semantic Web = encouraging publishers to use standards and using them to improve search result listings.
• Hakia (Dr. Christian Hempelmann) - Dr. Hempelmann's slides began with a sigh about needing beer.  Fair enough.  His slides then talked about what he doesn't consider semantics: proximity, syntax, 80% solutions, small incremental improvements.  In contrast, he argued that Hakia's extensive ontology was the only way to get to true semantics. Semantic Web = our way or the highway.

Wow!  Four people on a panel, essentially talking past each other.  Luckily, Dr. Ron Kaplan, our beloved Chief Science Officer from Powerset, made some important comments.  First, he noted that his (admittedly biased) version of the Semantic Web could be called the "Syntactic Web," i.e., that structural relationships are a necessary condition for finding meaning.  He worried that some of the panelists were saying "Search is good enough. Semantics can't get us to God's Own search engine.  Therefore, Semantics isn't worthwhile."  Ron pointed out that if semantics can get us better search results, the real question is whether it's good enough for users to appreciate the difference without them rebelling because it isn't perfect.  My favorite quote related to this point was: "We know that stupidity scales.  That's not the problem.  The question is: can we do better than that?" (thanks to Uldis for capturing this on Twitter)

So, the panel was basically four people talking past each other, plus some pointed comments from Ron to keep things lively.  On one end of the spectrum, Google seems to poo-poo semantics and NLP, generally. On the other side, Hakia seemed to be promoting a dogmatic view of what semantics is supposed to be.  Yahoo sits somewhere in the middle, trying to use approved technologies to improve results incrementally.  Healthline uses targeted ontologies to improve their vertical, but with little chance to improve Web search generally.

My Powerset-influenced opinion is that either extreme is wrong; that a general solution over incremental vertical improvements is key to overhauling Web search; that being open is better than being dogmatic; that a "semantic" web search will include semantics, syntax, statistics, and god knows what else; and that none of the major players seems are outwardly focused on this direction.

*Update* - Reposted on AltSearchEngines.

Powerset crosses the Uncanny Valley

In case you haven't heard the news, Powerset launched today.  Since I can't sleep due to launch adrenaline, I suppose it's time to weigh in on Powerset unofficially.  It's fun to write a press release, but it's more fun to philosophize on my own time!

Last year, I came across the concept of the Uncanny Valley though an employee of PARC.  The basic concept runs something like this: as you make a robot more like a human being, people tend to respond with more empathy.  However, there's a dip in the empathy curve when the robot looks enough like a human, but has behavior incongruent with what we'd expect from a real human being.  We tend to forgive weird mannerisms (jerkiness, oddities in speech, etc.) when a robot looks like a robot.  When a robot looks like a human, we expect it to act like a human.

As an example, cartoon characters are usually more believable than computer generated characters, unless the CG is so perfect as to be indistinguishable from reality.

Keyword search engines sit somewhere on the left of the curve.  We're willing to accept the choppy "keywordese" language of a search engine because we appreciate the results that come back and we can make excuses when it goes awry: "It's just a computer.  It doesn't really understand me."  As with most technology products, the utility curve and the expectation curve are aligned exactly because we treat keyword search engines as an unfeeling technology.

Oddly enough, when a system is endowed with an understanding of meaning (call it "semantics"), we suddenly demand that the system act, think, infer, and comprehend just like another human.  Instead of just being a cold of technology, we begin to treat the system with agency and want it to act like other agents (i.e., humans). 

The question shouldn't (and can't) be about releasing a system that has a perfect understanding of language, because that perfect understanding is many years down the road.  How is it that companies like Radar, TrueKnowledge, and Powerset believe that we can create products based on imperfect technology?

There are two ways to stay out of the Uncanny Valley.  First, create unique features that are so compelling that users are willing to deal with imperfection.  Keyword search hasn't survived because we always get the right answer - plenty of searches yield nothing.  But, though we may get wrong answers, we often enough get answers that would never have been possible before keyword search.  Second, access to semantic features shouldn't require a significant change in user behavior.  No matter how good (or "natural") a feature is, if a user has trouble finding it, it won't get used.

People often think that NL search is doomed to failure both because computers don't understand enough and, even if they did, users won't start entering natural language queries.

I think Powerset has scored on both counts.  As an example, for topical queries like moses or machiavelli, Powerset assembles a summary of Factz based on our deep linguistic analysis of each sentence.  This kind of automatic aggregation of content just wasn't possible before Powerset.  But, users don't have to do anything special.  They just get Factz "for free" by using their keyword usage paradigm.

I'm really proud of Powerset's first product.  The debate on whether or not we've crossed the valley will continue, but one thing is certain: a better, more natural way of interacting with technology is coming. (Of course, whether we sit to the left or the right of the Uncanny Valley is the subject for another post.)

Bed time, finally!

The Cashmore Effect

  Pete Cashmore modeling for Apple 
  Originally uploaded by philosophygeek

Is it the wry smile or the foreign accent?   The suave clothes or the sexy scruff?  His techie tools or vibrating strings?  Maybe it's just that je ne sais quoi? 

The elements making up Peter Cashmore may be under debate, but his effect is clear to the throngs begging for his attention.

Therefore, I conjecture, The Cashmore Effect: Pete Cashmore doubles the activity in his immediate area.

As proof, putting his picture on my puny blog will double my traffic tomorrow, which will be irrefutable empirical evidence of my theory.