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Data & Intelligence

Customer-Centric Business Intelligence: Capturing Customer Data

In order to create a customer-centric organization that capitalizes on the power of Business Intelligence, companies must identify the goals they would like to achieve and incorporate them into a formal business strategy.  The strategy map found in the balanced scorecard approach is a widely-used method for achieving this challenging task.

Ultimately, understanding your customers is key to building strategy.  In order to drive firm value, companies must track customer performance based on a single view of each customer as opposed to reviewing a random collective of siloed data points across the organization.  Using Business Intelligence tools, customer groups can be segmented and compared with regard to their ability to drive value. When attempting to acquire new customers, a company must identify prospects that will generate positive customer lifetime values that exceed acquisition costs.  Likewise, maintaining relationships with current customers translates into identifying those customers whose predicted future value is higher than the investment necessary to maintain that relationship.  Doing otherwise would essentially translate into paying your customers for doing business with you.  This seems so wrong, yet so many companies do it.  Why?  Because they are not tracking customer data correctly.

Tracking this level of detail in your traditional “spreadsheet mart” is a challenge.  Tracking this data using Business Intelligence tools will allow you to truly compete with analytics.  Ultimately, defining customers in this way provides a company with a valuable financial tool.  When an organization fulfills unmet needs in a growing market of profitable customers, then financial returns, and increases in market share, will result. 

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The Future of Big Data

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Finding Your Most Profitable Customers

At the most basic level, customer transactional data can be used to identify profitable customers via the whale curve (read: that graph that tells you 80% of your profit comes from 20% of your customers).  However, a customer-centric Business Intelligence scorecard takes this important practice a step further by creating a company culture that revolves around tracking and growing these vital relationships with profitable customers.  In order to develop a customer-centric scorecard a company must have the ability to access and give meaning to high quality data.  This is done by:

  1. Assessing the size and quality of the current customer mix 
  2. Determining if more high value customers are entering the customer mix as compared to prior periods
  3. Using this data to determine any baseline trends with regard to customer mix, size, and quality over time. 

Using this actionable data, companies can make more informed decisions with their valuable resources.  Many companies sacrifice investment in existing customers in order to generate new business.  However, new customer acquisition is notoriously expensive.  It costs six times more to attract a new customer than to maintain and expand a relationship with an existing customer.  Many companies, such as Kroger, Panera, and Shell are increasing firm value by increasing loyalty among existing customers instead of expending resources on developing new customer relationships.  They realized this value through Business Intelligence.

Predictive modeling is one of the main tools companies can use to identify customers with the most profit potential and customers that are most likely to end their relationship with the company in the near future.  This is done by comparing current customer data patterns with past customer behavior.  This comprehensive understanding of customer behavior can be integrated with the supply chain to determine its full impact on the organization well before it becomes a reality.  A company can route shipments and modify processes around potential problems, as opposed to scrambling to deal with a problem once it works its way into the supply chain.  Additionally, prices can be established in real time using predictive modeling so that a company can yield the most profit from each customer transaction.

Using analytics on clean customer data is a pathway towards success.  Stay tuned to future posts in this series where we will discuss viewing customer trends using Business Intelligence dashboards and adjusting future strategy based on information gleaned from patterns in customer data.

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Melody Smith Jones

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