Business Analysis

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Why Business Analysis

Through Business Analysis and Data mining, we help spot sales trends, develop smarter marketing campaigns, and accurately predict customer loyalty. This will allow you to face difficult business situations with more confidence. You can determine where to diversify and when because you'll have the intelligence to make smart decisions. Best of all, your intelligence will be on your desktop in a neat report (not scattered in files and notes). Specific use cases of business analysis and data mining include:

  • Market segmentation

  • Identify the common characteristics of customers who buy the same products from your company.


  • Customer churn

  • Predict which customers are likely to leave your company and go to a competitor


  • Fraud detection

  • Identify which transactions are most likely to be fraudulent.


  • Direct marketing

  • Identify which prospects should be included in a mailing list to obtain the highest response rate.

  • Interactive marketing

  • Predict what each individual accessing a Web site is most likely interested in seeing.

  • Market
    basket analysis

  • Understand what products or services are commonly purchased together; e.g., beer and diapers.


  • Trend analysis

  • Reveal the difference between a typical customer this month and last.
How ?
  • 1
  • We analyze your business strategy and your strategic goals, to provide a set of critical success factors and key performance indicators with which you can monitor your corporate performance.
  • 2
  • We map your strategies and goals to a business/IT solution that measures your progress in achieving your goals while evaluating the underlying strategies (Business Strategy, Marketing Strategy and Operations Strategy).
  • 3
  • We deep-dive into your data to answer complex business questions and provide insightful intelligence on your business and the market you are operating in.
  • 4
  • We distinguish between four types of analytics:
    Decisive analytics: supports human decisions with visual analytics the user models to reflect reasoning.
    Descriptive Analytics: Gain insight from historical data with reporting, scorecards, clustering etc.
    Predictive analytics: predictive modeling using statistical and machine learning techniques
    Prescriptive analytics: recommend decisions using optimization, simulation

References

  • http://www.laits.utexas.edu/~anorman/BUS.FOR/course.mat/Alex/
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