Using Crowdsourced Content in the Competitive Intelligence Process
Jinfo Blog

By Elizabeth Trudell

Abstract

Crowdsourced content, which is created by large numbers of contributors with a range of levels of expertise, can produce content of value for enterprise research needs. Mining social media sites for information can be of particular value for competitive intelligence activities. For crowdsourced content of all kinds, an assessment process can be applied to assess the credibility on the information.

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Basic company information was traditionally gathered by database providers through a painstaking process which involved contacting many organisations and collecting it from them. The nature of the collection process meant that it was often outdated or incomplete.

Now, new sources of aggregated company information are available, in which the content updates are directly contributed by thousands of participating individuals and organisations. While there still may be gaps and errors, the sheer scale of contributors generates useful sources that can play an important role in the competitive intelligence process.

Crowdsourced Company Information

LinkedIn offers a striking example of crowdsourced content aggregation, with profiles contributed by more than 300 million members encompassing the professional experience in all sorts of organisations. It has moved beyond its origin as a job matching service and become a viable resource for finding information about the background of the management and technical teams for competitors, partners, customers or suppliers.

With a data mining approach, it is possible to glean competitive intelligence by tracking how many new positions of what type are being posted by companies, which can suggest areas of growth; and whether employees are leaving companies, which may indicate layoffs, restructuring or management changes.

Competitive Intelligence

Owler, a new service specifically targeting the competitive intelligence space, has recently begun operating under the same management team which created InfoArmy. Michael Levy's recent Mini Review of Owler for FreePint notes that the content is being created by a combination of company-specific newsfeeds plus data contributed by a large cadre of participants.

It also deploys polls to gather consumer sentiment and market perspective about the companies and markets from users. While still small by LinkedIn standards, it is a new model for aggregating competitive intelligence content.

Evaluating Crowdsourced Content

The recent FreePint Subscription Article, "Crowdsource: Creating Credible Content through Scale", identifies a number of crowdsourced content collections which have potential use for enterprise-wide research use. These include free sites for scholarly research papers and collections of historical documents that were edited or tagged by large numbers of volunteers, as well as social media sources.

Scale alone doesn't determine the quality of crowdsourced content. Look for:

• The identity of the organisation sponsoring or aggregating the content
• How is the content is funded or monetised
• How contributors benefit from participating.

With careful evaluation, crowdsourced content can be a useful component of competitive intelligence and other enterprise research activities.

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