Data storage and retrieval is a tricky business. Information is one of the few things your company owns that continues to grow exponentially. In fact, the longer you remain in business and the more people you employ, the more complex your data repositories become.

And as technology continues to evolve and progress, allowing us to store peta-size archives of structured and unstructured data, the amount of information that needs to be accessed requires a powerful search mechanism. It’s not just about speed however, search technologies need to be smart; combining the ability to access numerous records at lightning speed while still thinking like the human mind would.

To that end, search technology delivers a powerful punch to your organization. Because technology can rapidly search through immense amounts of data, correlations are often found which go beyond human reasoning. Take for example a recent study conducted by a Dutch investment firm, who wanted to better understand their investment customer. The research uncovered a correlation between investment behaviors, location of home and vehicle owned. The company discovered that the most successful investor is 35, has 3 children and drives a Volvo, among other things. Given the wide variety of data points available on the entire investor population, it would be nearly impossible without the aid of technology to find these correlations.

These unique associations, found using traditional search technologies, offer your organization a smarter way to understand your customers, your product, and the market as a whole. But traditional search technologies still fail to truly utilize the data available in the way that a human could, learning from the past to help predict the future for example, or understanding affinities and taxonomies.

There is no denying that, in most search circumstances, there exists a core human element such as preference or prejudice which plays a significant role in determining the outcome of the search. For example, a study found that when using a dating site, most respondents used the same type of words to describe themselves, or to express what they would like to find in a potential mate. These included words such as “nice,” “honest,” “social,” and “funny.” The problem then becomes one of overuse – if everyone is using the same words to describe themselves, how do you determine who would make a proper match? And do our innate, perhaps even subconscious, preferences play a role in the results we get?

One obvious answer to this dilemma, perhaps, is to gather more specific data. Rather than ask questions that tend to receive similar answers, require users in the online dating scenario to give more specific information about hobbies, likes/dislikes, personality and lifestyle. But this presents its own stumbling block. The more users are prompted to enter concrete criteria about themselves and what they desire in a mate, the more limiting the options and the more potential for error in results.

What is needed is smart search and match, the ability to engage with the user in much the same way a real human interaction does. This is the driving force behind ELISE, WCC’s highly-scalable, multi-media search and match platform. Using a variety of capabilities such as universal and multi-modal search, weighted criteria, affinities, gliding scales and bi-directionality, ELISE is able to search today’s peta-size archives in sub-second response time and provide meaningful, ranked results. At the very core of our technology development is the desire to consistently work like the human mind does, ensuring a successful search transaction each and every time.

At WCC Smart Search and Match, we believe technology should work for your business, not against it. We’re dedicated to providing a search experience that not only meets your needs and expectations, but surpasses them. Log on to www.wcc-group.com to learn the secret behind searching smart, and unlock a wealth of possibility for your organization.