Enterprise search is more than just technology: it relies on users knowing what information they need and how to search for it. I discussed this in more detail in a previous blog post here.

Internet search and enterprise search (searching in the organization’s content) have many similarities at first sight, but actually even more differences and challenges.

Three primary elements differentiate Google search from enterprise search:

  • Type of content
  • Resources
  • Relevancy

 

Type of Content

Google search crawls the whole web for public information across different URLs. Findable public content needs SEO to rank in searches. When someone uploads content to the internet, he/she is interested in having the best possible ranking (a high degree of motivation) – hence the huge investment people and organizations put into SEO of their content.

Enterprise content is no equivalent. Organizations may have a large volume of confidential and sensitive information such as partner and employment contracts, top-secret research data and financial reports, which only a few members of staff are allowed to access. Content permission levels need to be managed correctly.

Furthermore, file types can be very different (for example, .doc and .ppt) and reside in separate repositories.

Enterprise search has to reflect these specific data requirements as well as permission restrictions.

 


 

Resources

Google has ten thousands of employees working on search, while the average company may only have one member of staff in charge of search (or even less).

In enterprise search, while solutions like Microsoft Graph can work with unstructured data, in many cases organizations need to manage and index their structured content with limited resources.

Also, users may not be motivated to optimize their content, compared to their SEO counterparts, as they only care about getting their job done – and jump to the next task (or go home) as soon as their document is uploaded to the proper content management library.

 

Relevancy

Google’s proprietary algorithm calculates relevancy on the basis of how many external links point to the source, as well as zillions of other factors which are not even known to the public.

In enterprise search, however, content may not be optimized at all, search volume may not be applicable and predictable, and search results cannot be relevant out of the box in most cases.

 

Trends and New Directions

In terms of new trends for enterprise search, it is worth looking at some new trends:

  • Intelligent insights
  • Cognitive search
  • Graph search
  • Machine Learning

 

While there is more and more investment into these technologies, there are still ongoing discussions and debates about these trends, even amongst us, search professionals. Will these really help? Or will the new challenges rising with these new age tools make more headache than the overall benefits of these new emerging technologies?

Keep in mind: the priority in enterprise search is always to see an increase in search results quality. This requires some input from the users themselves, too.