In a tight market, businesses must try to squeeze as much value out of their limited resources as possible. This is true for small businesses and large companies and everything in between. Large companies use predictive analytics effectively to gain an advantage here. However, for many small and medium businesses, analytics is never used at all or if employed, it is used as an expensive window dressing. There may be several reasons behind this: but mostly because SMB owners and managers are simply frozen into inaction because of lack of strategic awareness. Adding to this is the fact that there are so many techniques which only serve to increase the apparent complexity of deploying analytics. To demonstrate, let us look at an activity which forms the life blood of any business: customer relationship. There are three principal areas where a business can benefit from using data and analytics to build efficiencies:
- Customer acquisition – businesses can use data to better understand their current customers by doing Customer Profiling and Segmentation. Once you have a good idea of your current customer base, it then makes complete sense to develop targeted campaigns to acquire new customers. Customer response modeling is another activity which helps here. Decision tree techniques are commonly used to target potential customers with a laser like focus.
- Customer retention – it is a well known fact that it is cheaper to retain and sell to existing customers than to acquire new ones. Therefore customer retention is a very important business function. Here again, a business must be alert to the signals it is receiving from customer behavior data. Churn modeling, can identify who is likely to stop doing business and can help develop strategies to check this.
- Customer life time value – In line with the Pareto principle, for many businesses, 80% of the profit is derived from 20% of customers. The trick is to identify which customers belong to this 20%! When you develop campaigns to attract new customers, it is important to know if these customers will add value to the company in the long term. Once you know which customers are bringing value to the company, you can devise retention and churn prevention strategies to keep them with you.
Large companies pioneered the application and deployment of analytics because they have resources to access data, tools and expertise. Today data and tools are within the reach of even the smallest company. What is needed are professionals who can understand the business problems, and bridge the gap between technology and solution.
A technique which is commonly used to address two of the three problems listed above is the decision tree analytics method. It is easy to implement, fairly accurate and the best part is its ease of use. No executive who is shown a decision tree needs explanation of how it works. A picture (of a decision tree) is surely worth a thousand words – in this case probably dollars!
If you want to understand how to quickly build a decision tree model using available data and open source (meaning “free”) tools, download our free ebook – Decision Tree Digest here: