The main purpose of a search engine is to provide the most relevant results with ease. However, searchers using the same keywords can often be looking for different things. For instance, a searcher may use the word ‘java’ to look for a type of coffee, while someone else may use the same term to look for information on the Java programming language. In such cases, effective personalization based on various factors can help search engines offer results that are most relevant to a particular user. This means that even if searchers use the same keywords, the search results can be different based on their relevance.
Search Engines are Constantly Evolving
Over the years, many changes have come in the way search engines offer results for queries. Initially, the only criterion for offering results was an exact match between the keywords used and the documents in the search engine database. This means, if you searched for ‘Florida beaches’, you would only see the pages that had these exact terms with no more than a word in between them. As this was not very effective in offering the most relevant results, search engines started trying to track and learn from linking patterns on the web as well as the search behavior of users. The information gathered helped search engines in predicting the intent of users to some extent.
Personalization of Search Results
The latest buzz in the field of search engines is personalization. Effective personalization can help search engines take the actual interests of individual users into consideration to offer them relevant results. Popular search engines are already working towards better personalization, because users are more likely to stick to the search engine that offers the most relevant results. So how do search engines actually personalize the results. Although search engines guard their secrets closely and we do not know the exact criteria used by them for personalization, the consensus is that they track various user patterns to arrange search results based on their probability of being relevant.
Search engines most likely track the following patterns to offer personalized results. Personalization based on geographical location: Personalization based on the country of origin helps search engines offer results that are most relevant to the users of a particular nation. For instance, a search for the keyword ‘football’ will give different result for users in the US and the UK. Searchers in the US are likely to be looking for the latest news on American football rather than the stats of an English football club. Country determines is the first level of location based personalization. Today, search engines do not stop at this level. Personalizing results based on your current locality or city enables search engines to offer results that are more helpful. For instance, if a person located in California looks for the term ‘restaurants’, he/she is likely to get the names of restaurants based in California rather than those in London.
Website owners need to understand this because unless their site clearly identifies the location of their business, it may not get a place in the top search results.
Personalization based on web history: A person’s search history is another important criterion for the personalization of search results. The sites regularly visited, pages bookmarked, Facebook likes and similar information about a person’s web activities can be used by popular search engines to offer useful results. For instance, if you have been looking for information on islands in Indonesia, a search for ‘Java’ may offer information about the Java Island rather than java coffee beans.
Personalization based on user interface: Based on the device or interface used to conduct a search, the results may be personalized. For instance, a person searching for ‘New York theaters’ from a mobile is most probably looking for the ones located closest to his current location, unlike a person conducting the same search from a PC. So based on the interface used, search engines may be able to offer more helpful results.
Personalization based on social activities: Information gathered from social activities and social connections of a person on sites like Facebook or Twitter can also help search engines in personalizing search results. For instance, search engines can make use of reviews offered by your friends about different sites and ensure that the websites with the best reviews are featured in the top results. Many other factors like the time of search and the demographic profile of the user may also be used by search engines for greater personalization.
The search engine that comes up with the most effective way to use all these factors in combination will be able to offer the best results to its users, and so far Google seems to be far ahead of the competition in this respect.