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The personal nature of the mobile phone, the form factor of the mobile device (small keypad, tiny screen), and the obvious shortcomings of PageRank algorithms play in favor of a new approach to mobile search that puts people back in the equation.

People helping people is not just about idealism; it can form the basis for an ideal business model proven by the new popularity of approaches that harness crowdsourcing to develop products and game-changing concepts. In mobile search-where algorithmic approaches can deliver neither personalized results nor peer recommendations-social search and variations that deliver the right mix of answers and entertainment have a clear competitive edge over the plain-vanilla search we know from the PC.

My research into companies and models pushing the envelope in social and socially assisted search-mobile search schemes that either use people or index people-powered communities to improve search results-recently earned me an invitation to deliver the keynote address at Exploring the Future of Mobile Search, a workshop and think tank organized by JRC IPTS (Institute for Prospective Technological Studies), part of the Joint Research Centre of the European Commission.

During my opening, I presented updates to my list of innovative mobile search players and extensions to my list of mobile search categories. I have grouped mobile search into three main categories: interface search, based on how people interact with the search engine (via text, voice, and a variety of schemes that harness the camera phone to input queries); actionable search, focused on the interplay between what the individual wants and the results delivered (for example, vertical mobile search services that index downloadable content, such as music and video, and local search providers that provide the individual answers as opposed to a long list of links); and social search, approaches that infuse human preferences and judgments into a computer to pinpoint truly relevant information and better answers.

While this methodology was well-received, the lively conversations that started during the coffee break and continued into the evening emphasized the importance of hybrid approaches to mobile search that correctly and cleverly engage in conversations with us via our mobile devices to vastly improve the end-user experience.

So, after connecting with senior execs from mobile search companies still in stealth-mode, a new approach to mobile search-one I'll call precision personalized search-is high on my radar. This new breed of mobile search harnesses artificial intelligence (AI) to deliver an intelligent search that takes its cues from people to deliver a personal feed of relevant results.

A company to watch is ExpertMaker, a Swedish startup impacting mobile search. To date, the company insists on keeping its strategy and results (such as an impressive pilot with a major European mobile operator) under wraps. However, a demo of the patent-pending technology convinces me that this new flavor of mobile search could make mobile search as we know it passé.

This is because ExpertMaker has combined parameterized search and keyword search, allowing people to effectively have a conversation, rather than run a search. As a result, searching becomes finding as people interact with the search engine, refining queries (enhancing precision) in response to helpful suggestions (parameters). High precision is possible because the technology is designed to predict optimal matches for each individual customer based on their personal needs.

Essentially, the patent-pending AI comes up with the match for the search query. But it's the individual interaction with people that enables the delivery of personalized search results aligned with the individual's personal profile (which the technology "learns" over time like a trained electronic concierge).

Yet the scenario I find most exciting (and potentially lucrative) is one in which ExpertMaker can offer truly expert advice. Consider health advice: Do you have a cold or the flu? A pop-up "menu" of options on the mobile phone allows users to define and limit their search by filling in key variables such as their body temperature; the degree of nasal discharge; the type of cough; and the duration of the illness. Based on this input the user receives a diagnosis and some treatment suggestions. A doctor provides the knowledge behind the service.

Several important technologies, including voice recognition and image recognition, are poised to profoundly impact the future of mobile search. However, the real leap forward might be made when companies such as ExpertMaker introduce mobile search services that learn from us to deliver precise and personalized results. After all, on a mobile phone, asking is the best way to understand our intentions and optimize our results.