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The Importance of Context in Business Intelligence

Date posted: October 29, 2015

A recent article on Information Week points to how contextual awareness is redefining business intelligence. Contextual analysis— aided by mobile devices and the Internet of Things (IoT)— is providing enterprises what they need to reach consumers in relevant and meaningful and profitable ways:

Contextual analysis helps answer the “why” questions. With it, organizations are gaining deeper insight into the behavior of their customers, employees, equipment, situations, and trends. Marketers can deliver relevant messages and user experiences, and business leaders can make accurate decisions. Although contextual analysis isn’t a new concept, it’s being applied to a variety of cases to improve bottom-line performance.

The article points to a number of specific ways in which contextual analysis is helping business intelligence achieve new benefits:

  1. Decrypting purchasing behavior.
    “Context is key because low engagement is not necessarily a suppression of intent to purchase,” said Dean Abbott, chief data scientist at customer marketing intelligence platform provider SmarterHQ, in an interview. “Context allows you to understand intent. You can refine the message and identify an audience that might otherwise have gone unnoticed.”
  2. Predicting effects on stocks
    “There are ways to measure context in real time so you can predict much more than you could before,” said Luca Scagliarini, VP of strategy and business development at semantic intelligence platform provider Expert System USA. “Board members are usually board members of other companies. If you look at the votes each member expressed on similar issues in other companies, you can estimate the vote. [And] public opinion about a certain issue or important news [may influence how] the board votes around environmental issues.” Analyzing public company financial statements, such as annual reports, can provide insight into board members and their past voting behavior. Public sentiment can be monitored via newsfeeds, blog posts, and social media. All of that can help explain the context in which a decision will likely be made.
  3. Keeping Energy Flowing
    When an oil field or an oil well isn’t producing, millions of dollars are lost in a single day. To avoid unnecessary disruptions, oil and gas companies are performing contextual analyses of their operating environments using unstructured content, including maintenance notes, drilling reports, and other sources, to gain qualitative insights about non-production time.
  4. Improving Return on Investment of eMail
    The idea here is to deliver eMail that is contextually relevant at the time it is opened, rather than at the time it was sent, using various types of data such as geolocation, device type, time, and weather conditions, among other factors.
  5. Fine tuning cybersecurity
    Without context, anomalous behavior can be misunderstood and misclassified. For example, if an employee downloads a 1GB file at midnight, the event alone suggests malfeasance. However, viewed in the contexts of the employee’s historical behavior, the behavior of the group in which she works, her role, and the behavior of the organization at large, it may become clear that the act had a legitimate purpose.
  6. Improving the quality of BI
    “Without context, data is almost useless,” said Marius Moscovici, CEO of push intelligence software provider Metric Insights.. “If a number lacks context, it just leads to a lot of analysis to try to work it out. With context, you can take appropriate action right then and there.”
  7. Managing potential disasters
    Consider this example: The city of Buenos Aires, Argentina, is analyzing contextual data from sensors to determine in real time which areas need immediate support. In 2014, the city and its citizens were preparing for the largest downpour in history. In such a situation, flash flooding can occur simply because trash and debris are clogging storm drains and city sewers. “In Buenos Aires, you have the ability to use sensors in water tunnels underneath the city to map the water flow, the rate of the water flow, and how fast it’s rising. But if you don’t have the contextual analysis of an inspector using a mobile device entering the information about the inspection, then you’re not going to be able to alleviate the issue. You need both sides of the equation,” said Dante Ricci, lead global public services and healthcare marketing and communications at SAP. Because the maintenance crews knew when and where to clear the storm drains and sewers, a lot of damage was prevented.
  8. Delivering more timely user experiences
    Contextual mobile marketing has been on the lips of marketers since before the turn of the millennium, but the technologies and economics necessary to deliver it have taken many more years to develop. Finally, it’s possible to sense the location of an individual and her proximity to a possible destination, whether that’s a retail store or a coffee shop. Armed with that and other information about the customer, marketers can target an offer that is relevant to the person, place, and time. The same technologies can be used to alert employees to potentially dangerous situations or to turn app features on and off based on a context such as driving.
  9. More intelligent management
    “Context greatly improves performance management. It can help us sort through piles of data around people, how we’re managing people, what we’re getting done at work, and what will happen in the years ahead,” said Kris Duggan, CEO of goal-setting platform provider Betterworks.
  10. New perception
    Wearables are the new, new thing, capable of providing context that may not have been previously available. Instead of relying only on location to infer what might be relevant, it is possible to “see” what the wearer is perceiving when she is perceiving it. The benefit to marketers is finer-grained targeting and higher degrees of relevance, but the applications span everything from surgery to law enforcement to military operations. The same capabilities are being used in a variety of sports stadiums on the sidelines and in the stands.

Bottom line, contextual analysis can help organizations better understand why certain things are happening, not happening, or happening not in the way anticipated. What qualifies as relevant context varies based on the use-case, the environment, and the particular circumstances, but the use of context clearly furthers the application of business intelligence.