September 1, 2021
A major barrier to successful enterprise search is ensuring the content is findable in the first place. Across the organization people generate a wide variety of data in the form of documents, videos and podcasts, presentations, images, email content. The internal pool of information grows every day. Unfortunately, the ability to make sure all this data is easy for others to access isn’t the top priority for the content creators most of the time.
For example, imagine that each year your company puts out a thorough annual report with helpful graphs, insights, and quotations. You know there’s one chart you’d love to include in your next team update but can’t remember which year it’s from. Unfortunately, when you go to your enterprise search service, the only thing that comes back are a bunch of documents with the same title: “Annual Report.pdf.” Without more context, the search engine can’t produce the information you’re looking for, even though it is certainly there.
The meta data descriptions are lacking: in order to “match” searches with results’ metadata needs to be specific and differentiated from other forms of content on similar topics. In addition to being too vague or general, metadata often simply doesn’t exist, because creating it isn’t part of the protocol (or was ignored) when new content was added to the network.
Language across the organization isn’t the same: what one department calls a “report” another may call a “data sheet.” It’s also common for a subject matter expert to have or use technical terminology or jargon while the general user searches in plain English. It’s challenging to index content in a way that ensures access for all.
The content doesn’t exist in the first place! Unless the end user reports every time they come to a dead end in search, there’s no easy way for knowledge managers to identify what users are searching for but not finding.
Combined, these issues leave tons of institutional knowledge and intellectual property untapped. Moreover, it means customers and team members are spending time unproductively searching, walking away from your site feeling frustrated, or both.
Traditionally, going behind all the content creators to make the content findable by an enterprise search engine requires more manpower than most companies are willing to invest. It’s here that machine learning, like SearchBlox PreText™ Natural Language Processing (NLP), steps in to create a significant and immediate impact in the enterprise search experience.
