The Software Abstractions Blog

Does Web Advertising Work?

Do Web Ads work? Does the vaunted Freemium model actually produce meaningful revenues for anyone but the largest services and content sites? How should Web 2.0 be monetized?

Many Perspectives

There has been a lot of discussion about these and related questions in the past few days among the Techmeme crowd. Here is a cross-section of perspectives from some of the thought leaders in this discussion:

• Unsurprisingly, this discussion was kicked off by Tim O'Reilly, the same ultra-smart observer, blogger and publisher, who originally coined (or at least, evangelized) the term "Web 2.0".
• The Financial Times ran an article provocatively titled: Web 2.0 fails to produce cash , in which the authors question whether popular Web 2.0 companies have actually produced any revenue, and predict a big shake-out in the next year or two.
• The always-interesting Robert Scoble led a widespread discussion, referring to posts by Om Malik and Dare Obsanjo, on whether Twitter (that highly popular micro-blogging service, and train-crash-currently-under-way) should be charging super-users like him, while continuing to keep the core service free for most casual users
• Alexander van Elsas has a wonderful post, referring to an earlier post by Scott Karp of Publishing 2.0, explaining how advertising does not usually provide the user with any value; van Elsas feels that the real value should be created outside the network.
• Coming up on May 30th is a discussion on this topic at TiECON East: "Web 2.0: Viable Business Model or Bursting Bubble?". The discussion includes two prolific and highly popular bloggers among its participants, both of whom have (inevitably) blogged about it - Fred Wilson (Discussing Web 2.0 ) and Don Dodge (Web 2.0 = Bubble 2.0? ).

When Ads Attack!

Clearly, web ads do work under certain circumstances. The poster child, of course, is Google - in addition to ads on its own search results page, Google commands revenues from millions of long-tail publishers via AdSense. Although most of the small publishers in this group actually make very little money, the total revenue in the aggregate for Google is very high.

Web Ads work better in certain situations than in others. At a VLAB event last week, Bill Reichert, Managing Director of Garage Technology Ventures, summed up perfectly the virtuous cycle of content and advertising:
    "If the paid content enhances the product, as in the case of Google, then that attracts more users to the site, which in turn enables more income, which allows the site to further enhance its content. Thus, the ad content should fit the users' actions to be effective; otherwise, as is the case with Facebook, the ads just get in the way."

Monetization Options

Once a web site or service gains traction and gets a sizeable following, there are potentially many creative models for monetization. In a much older post, Fred Wilson wrote about the The Long Tail Of Business Models , working off an initial post on Media Business Models by Chris Anderson (and I've added my take ).

Web 2.0 monetization works especially well in specific situations, and it's likely that totally new models will emerge in the future. One such model is advertisers who create meaningful content for web users, a by-product of which is to drive sales; this type of content can include informative articles, useful services or immersive experiences. Examples of this type of model are:

• Pharmaceutical companies that educate doctors on how to utilize new types of medical devices
• Lawyers who explain the law or provide status updates on government activities
• Home improvement stores that sponsor how-to seminars and then provide discounts on materials

Clearly, the web is a different medium, and simply transposing print ads to the web will not work; the big winners of the future will be those companies that can take some of these radical new models for monetization and make those work for their own use cases.

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Happy Birthday, Alt Search Engines!

June 2 is the first anniversary of Alt Search Engines, a blog that needs no introduction in Web Search circles; neither does Charles Knight, editor of ASE, who has been a tireless promoter of alternate search engines - big, small and obscure!

So I just wanted to say ...

Happy Birthday, Alt Search Engines!

I've had a blast reading ASE and collaborating with you, Charles, and it's been a great ride! I think ASE is doing a lot for the Alts by serving as a platform and a forum for their cause. I'm looking forward to what ASE's second year will bring. Best of luck!

VLAB Event: The Rise of Crowdsourcing

Last week I attended an event on Crowdsourcing, presented by the MIT/Stanford Venture Lab (VLAB). Given the high caliber of the speakers and panelists, it was no surprise that it was a sell-out!

The panel moderator was Jeff Howe, who is a contributing editor at Wired magazine, and the person who has been evangelizing the Crowdsourcing phenomenon through articles and on his blog. In his opening remarks, Howe explained the definition of Crowdsourcing, giving particular emphasis on the fact that it involves an undefined group of people, gathered together through an open call. One rationale, he explained, is that crowdsourcing allows us to tap into the expertise of a distributed group of people; he referred to a quote by Bill Joy:  "Wherever you work, most of the smart people work somewhere else!".

As a framework for thinking about Crowdsourcing, Howe explained the four ways it's manifested:

1. Collective Intelligence, aka Wisdom of the Crowds
2. Participation of the Crowd
3. Opinions of the Crowd
4. Crowd-funding
    

The Predictify model

Mike Agnich, co-founder and CTO of Predictify, described their business model. He classified Predictify users into two types: Information Seekers - who pose deterministic questions about future events, events with finite measurable outcomes; and Predictors - who research and discuss events, then submit predictions. Predictors are scored and rewarded on accuracy, enabling them to build a reputation over time. In turn, Information Seekers get a data set of predictions, as well as the demographics of the voting. This allows companies to track the distribution of beliefs, how things trend over time.

The most interesting part of the presentation for me, was Agnich's observation that it wasn't purely for the data that companies engage in these types of activities, although Prediction Markets are traditionally considered to be part of Market Research. Instead, companies may promote these prediction activities to engage users into the brand message and create buzz about their brand and their new products.

The Panel

There were some amazing people on the panel, and they discussed Crowdsourcing from various perspectives.

• Mitchell B. Fox, President & CEO of 8020 Publishing, explained their unusual business model (hint: it's similar to that of threadless ). 8020 has a large and vibrant user community that submits all types of original content and then votes on the best ones; the company then publishes and sells glossy magazines that include this content. What struck me was how strongly Fox was focused on supporting his community and providing its members with the best user experience possible; practically every comment he made on the panel reaffirmed his faith in letting the community make all the choices and control its own destiny.
• Michael Sikorsky, CEO of Cambrian House, was his usual articulate self, a passionate advocate and evangelist of Crowdsourcing. At the event, he announced an agreement to sell certain assets to Spencer Trask, and that Cambrian House would be directly supporting several "portfolio companies" in future.
• Bill Reichert, Managing Director of Garage Technology Ventures, explained the virtuous cycle of content and advertising: if the paid content enhances the product, as in the case of Google, then that attracts more users to the site, which in turn enables more income, which allows the site to further enhance its content. Thus, the ad content should fit the users' actions to be effective; otherwise, as is the case with Facebook, the ads just get in the way.
• Saar Gur, VC from Charles River Partners, touched upon people's fundamental need to contribute; Crowdsourcing is successful because it recognizes this need. His focus in investing is to look for companies with a compelling, driving advantage, whether for the team, company, product or something else. In other words, is this an inevitably successful company?
   

Overall, it was a very interesting and informative evening. One of the main conclusions I came away with: regardless of how companies in this space do in the short term as business models are still getting worked out, Crowdsourcing is here to stay!

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Comparing Search Relevance: The Relona Project

Recently I worked with Charles Knight of the Alt Search Engines blog on a project to compare the search relevance of two major search engines - Google and Yahoo! - and to measure the improvement in relevance by adding a search engine technology called Relona into the mix.

Background

Relona Research Labs is a unique technology targeted at enhancing the relevance of search results by suggesting changes to the search query spec - such as adding keywords, enclosing phrases within double quotes, or even reducing the number of search terms. In future, this type of technology could be plugged in into the search engine back-end to automatically refine the user query and produce better search results.

Procedure

We started with a large number of actual user queries from the AOL open data set, provided to us by Relona. Out of these, we picked a substantial set of queries at random as our test search strings.

For each selected search string, we ran two tests:
    (a) comparing the search results from a raw Google search and a raw Yahoo! search to score the more relevant of the two, and
    (b) comparing the search results from a raw Google search with the results of a Yahoo! search for Relona-optimized queries, again to find the more relevant of the two
     [Deciding which results were the "more relevant" was done manually by eye-balling the results]

The idea was to evaluate whether the addition of Relona optimization for user queries made the Yahoo! results more relevant, relative to Google results.

Observations

Personally, the biggest surprise I found was in the comparison of raw Google and Yahoo! search results. I had always imagined these two leading search engines to be comparable in terms of search relevance. But that wasn't the case; while the results were comparable in about a third of the cases, Google's results were significantly better in about half the cases - the Yahoo! results were better in the remaining cases. Often, 8 or 9 out of the top 10 results from Google would be highly relevant, as compared to 4 or 5 from Yahoo!.

Using Relona's beta solution to improve the search results - often by constraining the query or adding keywords - did appear to enhance the relevance of Yahoo!'s results and help bridge the gap. (For access to the raw data, please send me an email and we can share it with you.)

One limitation of the existing Relona search is that the engine comes up with several suggested improvements to the query, only some of which enhance relevance of results. But in order to be usable in the real world, the technology needs to come up with one "best" query suggestion. Kumar Ramanathan, co-founder of Relona, assures me that they are currently working on improving their solution along these lines.

Conclusions

Based on this limited test (more comprehensive testing is needed), Relona clearly helps in improving the relevance of search results!

Also, based on this constrained data set, Google's dominance as the premier search destination seems well-justified; matching or beating their formidable relevance in Web search is going to be increasingly difficult in the future (especially since web sites may themselves be changing to suit Google's algorithms as well ).

At the same time, this project convinced me that a more systematic approach to measuring search relevance is sorely needed; all the search engines I've talked to so far seem to measure their own relevance using large data sets, manual measurement ("eye-balling") and statistical results. This is certainly one way to measure relevance, but it ignores other dimensions of search relevance, such as breadth, depth and so on.

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Yahoo! SearchMonkey - Released to Developers

The good folks from Yahoo! unveiled their new open search platform Yahoo! SearchMonkey, at a developer launch party today at their Sunnyvale headquarters. In some ways, the SearchMonkey platform is revolutionary and a major step forward in search, allowing publishers to participate directly in improving the quality of their own information presented on the Yahoo! search results page (this is also implicitly a push for the bottom-up approach to the Semantic Web, which most industry observers have given up on in favor of a top-down approach). The platform also lets publishers and third-party developers build applications aimed at improving the search experience. Finally, and most important, if enough publishers and app developers participate in the program, it promises to improve the quality of search results for end users.

Features

At the simplest level, you can think of SearchMonkey as a community-powered set of rich information boxes (similar to the Google OneBox) that appear on the Yahoo! search results page. Publishers can provide this rich data to the Yahoo! search index in a variety of ways: through structured data feeds (RSS), through RDF or Microformat markup on web pages, or through simple page extraction. The "Information Bar" shows up underneath the main search results. The Yahoo! search team has also provided tools to enable developers to build search-based applications very simply and easily.

Powerset Launches Wikipedia Search

Semantic search engine Powerset, which we've written about here before, has just launched its initial release. The current release is limited to indexing Wikipedia content, but it provides a great showcase for their technology and user experience.

For example, my search for "Alexander the Great" provided the following results page:

Cognition Technologies recognized by KMWorld as one of "100 that matter"

Cognition Technologies, which focuses on Semantic natural language processing technology, was named by KMWorld as one of the top 100 Companies That Matter in Knowledge Management for 2008.

Says Cognition CEO Scott Jarus:

One of the biggest barriers to building a natural language understanding system is to build the semantic map and the dictionary with details of the syntactic behavior of words (i.e. how words behave within context).  Cognition's team has spent more than 20 years building this capability into Cognition’s Semantic NLP for the English language ...  and our technology is commercially available today!

Semantic search and NLP technologies seem to have arrived - they are generating a lot of buzz lately. In addition to mainstays Hakia and Powerset, there is a spate of new entries, including Cognition, BooRah and eeggi. We will be reviewing some of these new alternate search engines on this blog in the near future.

Congratulations, Scott and the Cognition team!

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