Northern Light’s deep tagging and text analytics make every content collection more valuable to users
As we have noted many times, a market and competitive intelligence portal lives and dies by the content it contains. Invariably that’s a combination of internally and externally generated research reports, probably an industry news feed, perhaps government and industry databases, and most likely other specialized content sources specific to the company, industry, and use case.
Northern Light clients typically supply much of the content that resides in their portals. In addition, Northern Light itself supplies a number of proprietary content collections to its SinglePoint clients. Just this month we announced a new one: Financial Reports, which contains more than 700,000 documents, including quarterly investor presentations and annual reports for some 4,000 public companies, in addition to filings accessible in the U.S. Securities & Exchange Commission’s EDGAR database. Another example is Northern Light Life Sciences Industry Conference Abstracts, a grey literature database that provides unique access to more than 3.5 million abstracts and posters from 4,300 medical and life sciences conferences across the globe dating back to 2010.
But every content collection, proprietary or not, is only useful if its contents can be easily found. And a user’s ability to find meaningful content within their organization’s knowledge management system is largely a function of how documents have been indexed, and the search engine within the system. When all documents are deeply and consistently tagged according to relevant industry-specific taxonomies, text analytics can be applied, enabling users to discover relationships between the concept areas revealed in search results and uncover relevant business issues hidden in content.
Northern Light’s text analytics, called MI Analyst, is an automated meaning extraction application designed specifically for market intelligence, business analysis, product research, and market research, to help researchers discover new insights and drill down into the most relevant documents for purposes of their specific inquiry. The key to meaning extraction is identifying and labeling “meaning loaded entities”: Events, conditions, situations, outcomes, actions, relationships, and trends that imply significance for the professional purpose of the search. For example, in a market intelligence search application, meaning-loaded entities might be price cut, change in market share, or strategic partnership. In a pharmaceutical setting, meaning-loaded entities might be clinical trial, patent lost, or generic drug.
Northern Light has been doing this for years, which is what enables SinglePoint to flag for users not only companies, products, and technologies named in documents on a search result list, but also more complex concepts such as “business strategies.” And with this foundation, even more advanced automated insights presentation, made possible by SinglePoint’s AI-based machine learning, is a natural next step.
So whatever content collections you include in your Northern Light market and competitive intelligence research portal – whether they are from internal sources, licensed third-party subscriptions, or Northern Light – know that each will be maximized to the fullest, thanks to the advanced technology embedded in SinglePoint.
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To learn more about how SinglePoint adds value to all your organization’s content, contact Northern Light.