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This document discusses how businesses can use analytics to address common problems in sales, marketing, operations, and services. It provides examples of the types of metrics that can be analyzed for each area, such as cost per sale, customer conversion and retention rates, and cost per service call. The document also lists some of the capabilities involved in sales, marketing, operations, and services. It then gives examples of value reported from analytics initiatives, such as increasing conversion rates by 25% and decreasing acquisition costs by 30%. However, it notes that additional missing information could allow for a deeper understanding.
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Business Insights
- 2. Business Problems Addressed 1. Sales: What is the current cost per sale–sales costs/sales revenue? 2. Marketing: What Is our current customer conversion rate, and what impact would a one-point increase in the conversion rate have on revenue? 3. Service: What is our current customer retention rate and what is the annual revenue impact for every point increase in this rate? 4. Operations: What is the average cost per service call and what are the cost components? Truck rolls? Service agents? Other?
- 3. Set of Capabilities Involved: SALES: LOWER COST PER SALE MARKETING: INCREASE CUSTOMER ACQUISITION OPERATIONS: REDUCE INVENTORY COST SERVICES: HIGH CUSTOMER RETENTION
- 4. Value reported from Analytics Initiatives and how it was attained Conversion rate increased by 25% and customer acquisition cost decreased by 30% The firm reduced customer churn by 50 %, increased lifetime value of their customers and regained lost revenue Boosted customer acquisition rates by targeting the most valued. Segments, raised the average purchase size through cross-sell offers, increased average lifetime value of customers through greater customer loyalty and repeat purchases.
- 5. Missing Info that would have allowed deeper understanding
- 6. Task 2
- 7. Pre-Processing steps on House Price Dataset
- 8. House Price Visual Exploratory Analysis Pie chart shows the distribution of total house price for each view. View ‘0’ is at the highest level, followed by view 3, and view 1 is at second highest level.
- 9. Avg House Price relative to view Shows the Distribution of Avg House Price with respect to the view, on monthly basis
- 10. Avg House Price relative to water-front Avg House Price of water-front ‘0’ is much higher compared to water-front ‘1’
- 11. Avg House Price Relative to View Avg House Price for View -3 and 4 are at highest level compared to view 2 and 5.