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Posts tagged ‘Mobile BI’

24
May

Data Visualization, Discovery and Visual Analytics – Use Cases, Tools, CoE, Vendors


DataVisualizationNumerical quantities focus on expected values, graphical summaries on unexpected values.” – John Tukey, Exploratory Data Analysis, 1977.

 

Decision support needs better visualization. Scorecards, Dashboards, Heatmaps, Alerts, Management Reporting, Operations and Transactions Reporting are all enterprise example of data visualization outputs.

Some data visualization examples include:

  • Data Scientist — uses “R”, a programming language used for statistical modeling, to understand traffic flows and congestion patterns and advise on options to improve travel times for Amazon.com Local delivery drivers.
  • Pharmaceutical Sales Representative — uses QlikView on an iPad to access current industry sales trends and doctor prescription history while on a sales call with a busy physician.
  • Healthcare Chief Medical Officer — uses Tableau Software to analyze all aspects of hospital performance including population management, emergency room effectiveness and Affordable Care Act compliance.
  • Crime Analyst— uses Microstrategy to maintain a consolidated view of crime levels and optimize staffing allocations to dispatch police into high crime areas.
  • Retail Store Manager — uses QlikView to analyze which products are selling best which impacts store assortments and which products get featured vs which ones get discontinued.
  • Telecom Customer Service Agent — uses Spotfire to monitor call center statistics and how it translates into customer satisfaction and retention.

DataLeverage

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2
Jul

Enabling SoLoMoMe + Omni-channel Analytics


At the Analytics Executive Forum, I facilitated a session on Omni-channel analytics. It struck me how every leading consumer facing firm seems convinced that mobile is becoming the dominant B2C interaction channel.  Mobile is the gateway to insight based marketing and the “always addressable customer”….

Insight-based interactions –  The company knows who you are, what you prefer, and communicates with relevant, timely messages, using the power of analytical intelligence to detect patterns, decode strands of information and create meaningful offers and value.

The “always addressable customer.” This is a consumer who fits the bill on three fronts simultaneously: (1)

  • Owns and personally uses at least three connected devices; (2)

Goes online multiple times throughout the day;  (3) 

  • Goes online from at least three different physical locations

The opposite of insight-based is “spray-and-pray” marketing – The company has very limited knowledge about who you are, forgets what you prefer, and tries to reach you with off-target communications that alienate you – based on fragmented data, poor data quality and  inadequate integration, resulting in confusing, chaotic interactions.  A good example: “I have 2 million frequent flyer miles with your airline and still do not get any recognition, respect or value from this loyalty.”

As companies architect new insight based mobile use cases I suggest that they look at what is coming next. With IOS 7, Apple is delivering several new features – Passbook, Beacon.

Retailers, banks and other customer facing firms/brands better pay attention. 100+ million iPhones are automatically getting this feature with the new OS upgrade making this a mega-disruptor in the coveted target segment everyone is chasing. Read more »

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