Here Are Five Business Intelligence & Analytics Cross-Industry Case Studies

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When businesses make investments in new technologies, they usually do so with the intention of  creating value for customers and stakeholders and making smart long-term investments. This is not always an easy thing to do when implementing cutting-edge technologies like artificial intelligence (AI) and machine learning. Business intelligence case studies that show how these technologies have been leveraged with results are still scarce, and many companies wonder where to apply machine learning first (a question at the core of one of TechEmergence’s most recent expert consensuses.)

Artificial intelligence and machine learning have certainly increased in capability over the past few years. Predictive analytics can help glean meaningful business insights using both sensor-based and structured data, as well as unstructured data, like unlabeled text and video, for mining customer sentiment. In the last few years, a shift toward “cognitive cloud” analytics has also increased data access, allowing for advances in real-time learning and reduced company costs. This recent shift has made an array of advanced analytics and AI-powered business intelligence services more accessible to mid-sized and small companies.

In this article, we provide five case studies that illustrate how AI and machine learning technologies are being used across industries to help drive more intelligent business decisions. While not meant to be exhaustive, the examples offer a taste for how real companies are reaping real benefits from technologies like advanced analytics and intelligent image recognition.

1 – Global Tech LED: Google Analytics Instant Activation of Remarketing

Company description: Headquartered in Bonita Springs, Florida, Global Tech LED is a LED lighting design and supplier to U.S. and international markets, specializing in LED retrofit kits and fixtures for commercial spaces.

How Google Analytics is being used: 

  • Google Analytics’ Smart Lists were used to automatically identify Global Tech LED prospects who were “most likely to engage”, and to then remarket to those users with more targeted product pages.
  • Google’s Conversion Optimizer was used to automatically adjust potential customer bids for increased conversions.

Value proposition:

  • Remarketing campaigns triggered by Smart Lists drove 5 times more clicks than all other display campaigns.
  • The click-through rate of Global Tech LED’s remarketing campaigns was more than two times the remarketing average of other campaigns.
  • Traffic to the company’s website grew by more than 100%, and was able to re-engage users in markets in which it was trying to make a dent, including South Asia, Latin America, and Western Europe.
  • Use of the Conversion Optimizer allowed Global Tech LED to better allocate marketing costs based on bid potential.
2 – Under Armour: IBM Watson Cognitive Computing

Company description: Under Armour, Inc. is an American manufacturer of sports footwear and apparel, with global headquarters in Baltimore, Maryland.

How IBM Watson is being used:

  • Under Armour’s UA Record™ app was built using the IBM Watson Cognitive Computing platform (see app screens above). The “Cognitive Coaching System” was designed to serve as a personal health assistant by providing users with real-time, data-based coaching based on sensor and manually input data for sleep, fitness, activity and nutrition. The app also draws on other data sources, such as geospatial data, to determine how weather and environment may affect training. Users are also able to view shared health insights based on other registered people in the UA Record database who share similar age, fitness, health, and other attributes.

Value proposition:

  • The UA Record app has a rating of 4.5 stars by users; based on sensor functionality, users are encouraged (via the company’s website and the mobile app) to purchase UA HealthBox devices (like the UA Band and Headphones) that synchronize with the app.
  • According to Under Armour’s 2016 year-end results, revenue for Connected Fitness accessories grew 51 percent to $80 million.

Read the source article in TechEmergence.