Peggy adds: Just got back from a great meeting with alternative search engines (going mobile!) in Berlin and now off to Switzerland to connect with some super-cool recommender companies. Yes, it is a bit hectic for the next few days – but the excellent (and exclusive!) content I bring back to MSG makes it all worth it!

Regular readers will know I consistently track developments in mobile search, but it’s recommenders (companies and technologies that take the Amazon.com people-like-you-liked this/content-you-liked-is-like-this to the next level) that really excite me. Why? Because mobile search is primarily about delivering users what they want. Recommenders, however, are about picking up the clues we leave behind to suggest content and services we are likely to appreciate. The bottom line: Recommenders encourage cross-sell, up-sell, and the all-important impulse buy. Of course, the combination with mobile search is the most powerful indeed.

But don’t take my word for it. Orange, which has harnessed recommender technology provided by Xiam, a Qualcomm company specialized in this space, reports higher sales in this podcast. Likewise, content retailer/aggregator FoneStarz tells us in this podcast that its in-house recommender technology has led to a significant uplift in content sales.

It’s early days – but that’s why it’s important to watch this space carefully. A “Google” hasn’t emerged yet – but it’s only a matter of time, which is why I am so honored to take part in Recsys 2008 (held this year in Lausanne, Switzerland). Even better: I have been asked to judge the best early-stage project in the area of recommendation technologies. More about these super-cool companies further down in the post.

This bleeding-edge conference, sponsored by companies including Unilever, Telefonica ChangingWorlds and Strands, a recommender company MSG has tracked since the start, highlights recommender trends and technologies sure to have an impact.

I say this from experience since my participation in last year’s Recsys gave me the opportunity to connect with Aggregate Knowledge long before the company made their mark on mobile. In fact, I’m pleased to say MSG had a head start on this one, publishing in-depth analysis of the company and interviews with senior management just weeks before the company announced a tie-up with CBS Mobile.

Knowing the caliber of companies that attend this event, I am confident that I’ll uncover some great material for MSG. I’m also greatly looking forward to demos from the five finalists that have been invited by Strands to present during the conference as part of their first-ever $100K Call For Recommender Start-Ups. True to the name, the winner will go home with a $100,000 investment from Strands. According to the company blog, 68 scientists and entrepreneurs from 24 teams in 15 countries presented 26 projects.

The five finalists are:

Gravity R&D, which has developed a “magic button,” providing TV viewers instant personalized entertainment at any given time with relevant program tips instantaneously on customer demand. It automatically schedules recordings with the highest probability on user’s interest. (Hmm – I’ll have to check if the team is also thinking about mobile TV.)

SentiMetrix, which has designed (and automated) a method to extract and quantify the huge and growing number of text-based opinions expressed by users across online media. Get this right and the implications for all media – including mobile – are profound. Understanding sentiment is the first step to understanding and engaging with people on their terms.

Iletken, which has created a hybrid recommendation engine for services like news and RSS feeds, allowing users to share and pass on relevant information to their friends. In contrast to traditional social networks, it maintains weighted graphs of social proximity among users for different categories of interest.

Reccoon, which harnesses location information to help people discover new places based on their input, current location and current time. Reccoon responds to the simple question: What are my options for tonight?

Commendo, which uses recommendation technologies to optimize the drug design process in the pharmaceutical industry, including speeding up drug development and the minimization of adverse drug reactions.

I also look forward to the opportunity to catch up with Oliver Bremer, VP Mobile, and get the inside track on Strands’ strategy and roadmap. Earlier this week I spoke with Gabriel Aldamiz-echevarria, Strands VP Communications, who filled me in on some new – and very intriguing – developments.

Strands has quietly and cleverly sharpened its focus on life-streaming, developing tools and techniques to sift the clues to our preferences/tastes we leave across platforms, devices and virtual spaces to help us discover stuff we’re bound to like across the Web. At another level, this same technology helps Strands’ clients (banks, retailers, content providers) improve sales, engagement and CRM.

As Gabi put it: The key is to organize all the information we leave across the Web into one integrated profile, and facilitate the sharing of our tastes and behavior. “This way discovery does not only happen in one site, it will take place across the Web.” (The scenario: When I buy a product from an online retailer, I can share that purchase event on Strands.com for my friends to discover. They will be exposed to that product, as well as seeing similar products I liked. I can broadcast my purchases to my friends and we can discover new stuff together. The retailer is also part of the conversation – and there’s a direct trail to the store where it all started.)

It’s easy to imagine that these approaches – when adapted to mobile – will go a long towad solving some of the problems we face in mobile advertising. Could recommenders allow brands to be part of our conversations without dominating them?

Mobile advertising evangelists Jonathan MacDonald and Andrew Grill remind us that brands must ask our permission and preferences before they deliver advertising. My take: Maybe intuiting our preferences (by following the clues we leave behind) and making some helpful suggestions based on this insight (with user opt-in, of course) is a great way to get the dialogue started…

This entry was posted on Thursday, October 23rd, 2008 at 2:47 pm and is filed under Content Discovery, Local Search, Location-based services, Mobile Advertising, Mobile Music, Mobile Search, Mobile Social Networking, Personalization, Recommendation, Web 2.0. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.