Context-based search: the next phase of personalization

Our cellular phones know us better than ourselves and 'open doors' for us even before we request them to do so.
Let's say I'm searching for a restaurant for dinner. Searching for the phrase 'Italian restaurant' might seem at first too general, yet Google already knows to filter the search according to my needs and offer restaurants located nearby -using location technologies and restaurants I've tried before- based on my search history, etc.
The widespread use of mobile detection features has been beneficial to us users as it allows us to not only locate restaurants located nearby but also find the fastest route to each one (including when the bus will arrive or how to best avoid traffic). When searching for some businesses, Google can warn us that it is rush hour and perhaps it is better to return later or choose another chapter of this chain (located nearby as well).
Businesses profit this technology quite a bit, assuming they utilize its abilities correctly. Beside pushing ads on Google according to user location, businesses can improve their time management by analyzing rush hours. Businesses in the field of communication or infrastructure can use location detection technology. For example, companies which employ technicians that arrive at customers' houses can identify the technician's location and present to him local or regional malfunctions (typical or real-time).
Back in April 2016, journalist Aaron Friedman foresaw in an article titled "The Future of Search Engines is Context" that the future of search engines is the context-based search. In other words, matching search results to the users' needs at time of said search. This isn't personalizing UX; this is the next step- fitting the search for a specific user at a specific time and specific place.
Recently, Google has coined the term "micro moments", i.e. moments in which people turn to their cell phones in order to learn, watch, buy or discover something. During those moments the user expects to receive the most relevant information; this calls for a context-based search. Google must guess the user's intentions.
The transition to the new phase of context based search requires the ability to retrieve and adapt data from several sources. For example, if devices contain a specific credit card's app, the search engine might suggest restaurants which offer a discount for card holders. If my schedule features a meeting in Jerusalem the same evening, restaurants in Jerusalem would be preferred. If my device features a diet app the restaurants offered would be only those which offer a dietetic menu. The moment we enable this connection (for the price of some part of our privacy) we allow the app to guess our will and intentions.
How can this be applied in the world of Knowledge Management? As Ella Antes wrote in the October 2Know issue, this is the age of the mobile organizational portal. This is an advanced platform for promoting intra-organizational communication. Organizations which implement this solution should probably consider using location detection technology for context based search in order to provide workers with an optimal UX.

 

 
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