Mining the Web to Map a Competitive Landscape

Posted: 16th December 2011
Mining the Web to Map a Competitive Landscape

One common, challenging task we’ve heard from business analysts is their need to regularly sift through loads of RSS feeds, news channels, and social platforms just to aggregate the relevant web discussion about their competitors. We’re working to make this compilation of web material simple, and take it further by presenting the contents of that material in a way that’s immediately valuable for contextualizating competitor activity.

In the three steps described below, you’ll find how RecordedMicrosoft-Co Future can quickly find answers to otherwise labor intensive, time-related questions:

  • What products are known or rumored to be released by competitors during the next twelve months?

  • What legal issues have competitors faced during the last thirty days?

  • Where are competitors known to be expanding during the next decade?

Map Out the Competitive Landscape


What we’ve done, using Microsoft as the focal point,  is identify companies mentioned as competitors to Microsoft during the last twelve months. Phrases that generate this network include: “Microsoft’s not the only recent PhoneGap backer: Rivals Salesforce and Adobe already have been doing mobile-development work…” and “HP’s intentions… represented a particular challenge to longtime partner Microsoft Corp…”

Establish a Competitor Bucket


We can pull the full list of companies from the results depicted in the first network graph and populate a ‘Watchlist’ containing each competitor. You can trim this list or add to it as needed and then include the full set of included companies in a time-related query.

Understand Competitor Activities

Now, the good stuff. Since we have the entire set of competitors (and their synonyms, stock ticker symbols, etc.) batched together in a Watchlist called “Microsoft Competitor List”, we can couple it with any of the event parameters available in Recorded Future and run this request across any timeframe.**

Say we want to first understand what products from each of these companies are rumored or planned for launch during the next twelve months. Here’s a network graph of those products:


But since these are aggregate predictions over time, maybe it’s also valuable to consider the lawsuits affecting these companies during the last month and see if they might affect the impact of any above mentioned products.


And finally, we can turn this analysis toward some really “big picture” issues such as where the competitor companies are expected to expand their operations during the next decade:


The key is that once you’ve established a customized list, there are lots of ways to slice up the index of web information that we’re structuring in order to gain a more comprehensive, forward looking view of any competitive landscape. Get signed up for a trial account today, and try it yourself!