Customer Measurement Problem 11


Jump To Page – Intro, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, Conclusion

Customer Measurement Problem 11 MISSING INTEGRATIVE OPPORTUNITIESMany organizations have seen a proliferation of available data and metrics in recent years. Largely enabled by technology, the availability of information has helped to establish more metrically oriented managerial perspectives – e.g., balanced scorecards, Key Performance Indicators (KPIs) and so on. In fact the confluence of sophisticated software and hardware solutions allows massive numbers of metrics to be measured, organized, stored and accessed, many in real-time (more about this in Problem Twelve). Perhaps the abundance of data at least helps to explain the existence of this eleventh problem. As challenging as it may seem to know where to start in bringing big-picture order and integration to this proliferation of metrics, there is no doubt that many companies are missing yet another opportunity. That is particularly true when it comes to integrating customer-related metrics.

Here again, the notion of customer lifecycle offers a very helpful organizing lever. Consider the collection of events that take place across the customer lifecycle. Data systems typically exist at all the major mile markers. There may be a marketing communication contact system, a sales/prospect management system, a project tracking system for sold products/jobs, any number of transactional survey metrics measured across key stages of customer experience (e.g., delivery, installation, technical support, etc.), overall relationship assessments typically gathered through customer satisfaction survey processes, financial systems tracking purchase data, problem and complaint tracking systems, inbound contact tracking systems, and more. How is all this customer-centered data being coordinated, merged, analyzed, and leveraged to strengthen customer relationships? Often it simply is not.

Many companies have very disparate systems in place with no coordinated common customer identifier present through out all the systems. In fact, the quality of information housed in some of these systems is severely lacking. It is amazing to see how many companies have shortcomings in organizing available information on their own customers. This is a problem, again, of missed opportunity.

Imagine the data mining possibilities if all customer data streams were linkable by a common customer identifier. Imagine what could be done if all available data were organized temporally, from initial prospect contacts through the entire event history of the customer lifecycle. Imagine if survey data and event metrics were coordinated, tracking not just that an experience took place, but also connecting the experience with explicit evaluation of the experience through survey processes. The power of that kind of integration, particularly when event data is linked with perceptual data and financial data, is largely untapped. The unrealized possibilities are enough to thrill any data miner.

This kind of integration should not be considered only in terms of aggregate-level analysis. A very powerful aspect of this kind of integration is the promise that it offers in managing customer relationships intelligently at the individual customer or account level. Any marketing action, any sales or service contact, any outbound activity at all could be so much better focused for any given individual customer when equipped with the stockpile of all available customer data for that particular customer/account. The potential is great, but largely unrealized in many organizations. Steps must be taken to unify all customer data streams. The technological tools exist to help do so. It is a matter of seeing the bigger-picture integration possibilities, then leveraging available technologies to help make them happen.

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