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ROI for a CRM analytics implementation

In this tip, Tom Pisello helps a bank manager calculate the ROI for an analytics implementation including data mining tools.

Can you explain the role of data mining tools in a CRM analytics implementation at a bank? How can the ROI be calculated in this project?
The ROI (ratio of net benefits divided by investment costs) can be calculated by examining a couple of benefits to be delivered, versus the cost of the analytics implementation.

On the benefits side, the following are suggested for examination and inclusion in the analysis:

1. Reduction in manual data collection, quality checking and reporting – the analytics can automate manual processes of employees or IT having to create reports

  • Improving efficiency and productivity in the process of finding and using information and developing reports
  • Decreasing the costs perhaps of creating and distributing reports via paper (now on-line)
  • Decreasing the current IT analytics and database costs and tools, as well as IT support, by consolidating databases / analytic / reporting engines.

    2. Improvement in information effectiveness – the analytics can help improve the effectiveness of the information and its use in making business decisions:

  • Helping to avoid spending on bad marketing / customer care programs
  • Avoiding risks such as analyzing quality issues, customer service issues or customer churn
  • Revenue improvement opportunities – for example indicating which customers are the best to focus on

    On the cost side, be sure to estimate total cost of the project and ongoing cost of ownership. These costs should cover hardware, software licensing, application customization, implementation labor / services, report customization labor and user / IT training investments initially, and on-going support contracts, application evolution and administration labor / services.

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